Home Page Search Final Report Interim Report Evidence - Transcripts - Witness Statements - Submissions - CCNR Report and associated documents - Statistical Reports and associated documents - Background Papers - Expert Papers Inquiry Seminars About the Inquiry Help		Daily transcripts Hearing summary 3rd November 1999 Today, analysts commissioned by the Inquiry and members of the Inquiry’s Expert Group, who have assisted with the evaluation, fed back their findings from the analysis of six relevant data sources. Brian Langstaff QC, Counsel to the Inquiry, opened the hearing this morning by explaining that the statistical review, analysis and synthesis of six key data sources relevant to the work of the Inquiry is part of the exploratory phase of the Inquiry's strategy for using statistics to inform its investigation of children's heart surgery at Bristol. He highlighted the need to place figures in context and stressed that today’s evidence is one part in the jigsaw of the Inquiry’s investigation. The following analysts and members of the Inquiry’s expert group presented their findings to the panel during the course of the days hearings: Professor Michael Campbell, Professor of Medical Statistics, University of Sheffield, explained how to convey complex statistical concepts and identified the techniques used during the analyses. Professor Stephen Evans, Principle Consultant Statistician, Quintiles, reported on reported on the analysis of local data relating to children who received cardiac surgery under the terms of reference of the Bristol Royal Infirmary Inquiry. Dr Paul Aylin, Senior Clinical Lecturer, Imperial College School of Medicine, London, reported on the analysis of Hospital Episode Statistics. Professor Gordon Murray, Professor of Medical Statistics, University of Edinburgh, reported on the analysis of the UK Cardiac Surgical Register and the South West Congenital Heart Register. Dr David Spiegelhalter, Senior Scientist, MRC Biostatistics Unit, University of Cambridge, presented a synthesis of all the statistical sources concerning the nature of the outcomes of paediatric cardiac surgical services at Bristol relative to other specialist centres from 1984 to 1995. Dr Eric Silove, Paediatric Cardiologist, Birmingham Children’s Hospital, Mr Leslie Hamilton, Paediatric Cardiac Surgeon, Newcastle Upon Tyne Hospitals, members of the Inquiry’s Expert Group, also attended the hearings to comment on the presentation of the reports.

FULL TRANSCRIPT

   1              Day 70, Wednesday, 3rd November 1999
   2   (10.00 am)
   3   THE CHAIRMAN: Good morning, everyone. Good morning,
   4     Mr Langstaff. An apology is due from me that we are
   5     starting somewhat later than we should. I accept
   6     responsibility for that. We had a number of things we
   7     had to deal with elsewhere. Forgive me. We are now
   8     ready to hear you, Mr Langstaff.
   9          INTRODUCTION TO TODAY'S EVIDENCE
  10   MR LANGSTAFF: Sir, thank you. Sir, today, as I have
  11     indicated on more than one occasion, we are renewing
  12     the acquaintance in evidence with statistics. Back in
  13     July we examined the way in which this Inquiry would
  14     deal with statistics and to an extent the part that
  15     statistics would play in the Inquiry, and outlined
  16     a strategy which involved an exploratory phase. This is
  17     today to be the report of that exploratory phase.
  18        At the outset the Inquiry outlined the process
  19     which statistical analysis would take. Figures can be
  20     seductive. It is tempting to regard the numbers of
  21     operations and the numbers of deaths recorded in any
  22     statistical analysis of Bristol as answering
  23     the question whether care was adequate or not. That
  24     would be entirely wrong.
  25        After all, if 40 years ago 8 out of 10 patients

   1     suffering from a particular condition died, that might
   2     be regarded if the condition were particularly complex
   3     as not being a cause for investigation and
   4     recrimination, but rather a cause for saying, "In this
   5     operation for this condition in this hospital we managed
   6     to save 2 out of 10", and be a cause for celebration.
   7     Figures have to be placed in context.
   8        Although the evidence you will hear today will
   9     emphasise statistics and analyses of figures and
  10     databases, it is important from first to last that
  11     the context be remembered. The statistics are only part
  12     of the jigsaw. Figures alone can never say whether they
  13     represent an adequate state of affairs or not. They can
  14     only be part of the picture. They can suggest that an
  15     explanation is called for; they cannot themselves give
  16     the explanation.
  17        From first to last today it must be remembered
  18     that the Inquiry will approach its task set out in its
  19     terms of reference of assessing the adequacy of care in
  20     four principal ways. First is the evidence, written and
  21     oral. Part of the adequacy of care is, for instance,
  22     the way in which parents and children were treated as
  23     people. How can figures tell us that?
  24        Just as figures can tell us little about
  25     the approach of clinical staff to patients, because that

   1     is a matter for qualitative assessment by the Panel, so
   2     too a qualitative assessment can be made on the basis of
   3     the evidence provided as to the level of care and its
   4     adequacy delivered at Bristol.
   5        Second, there is evidence given by experts and
   6     others as to the adoption of procedures and policies
   7     which in their expert view from long experience in
   8     the field might have made a difference. This too is
   9     part of the picture.
  10        Third, there is a mosaic of individual cases and
  11     individual stories which makes up the pattern of care.
  12     The Inquiry has already heard from many parents, each
  13     telling from their own individual perspective of
  14     the care given to their son or daughter. This is
  15     invaluable. It is part of the picture.
  16        In each of those three areas which I have already
  17     dealt with statistics play no part.
  18        Next the clinical case note review which we will
  19     look at in evidence tomorrow forms a basis for
  20     a representative snapshot of the care given to children
  21     at Bristol over the years with which the Inquiry is
  22     concerned. We shall hear more of that.
  23        Finally, and you will by now I hope appreciate
  24     that it is part and part only of the picture, part of
  25     the complex jigsaw that makes up the picture of adequacy

   1     of care, there is that which the figures can tell us; if
   2     you excuse the expression, "a health warning".
   3        Figures in this area must be treated with
   4     caution. If I take a coin and toss it once, there is
   5     a 50 per cent chance that it will come down heads and a
   6     50 per cent chance that it will come down tails. If
   7     I toss it twice therefore it should come down heads on
   8     one occasion and tails on the other. If it however came
   9     down twice as heads, one could not safely conclude that
  10     I was using a double-headed coin. That is life.
  11        The true chance of it coming down heads or tails
  12     would still be 50 per cent and it would remain 50
  13     per cent on the next occasion, no matter what the run of
  14     heads or the run of tails had been. If I take the coin
  15     and toss it ten times, then on average, but only on
  16     average, you might expect it to come down heads five
  17     times and tails five times. But, if it came down eight
  18     times one way and twice the other, you would not
  19     immediately say there is something wrong with the coin.
  20        Everyone has in daily life experience of tossing
  21     a coin. If, however, all the evidence that we had to go
  22     on to compare two coins was that one when tossed ten
  23     times came down heads on eight occasions and the other
  24     when tossed ten times came down heads up on four
  25     occasions, if that was all we had to go on, it might be

   1     tempting to think there was some real difference between
   2     the coins that made one more likely to come down heads.
   3        Yet the truth, as we know from everyday
   4     experience, will be that there was actually no
   5     difference at all between them, despite the twofold
   6     difference on the figures.
   7        I should say that I am grateful to our experts for
   8     giving me this everyday simple example in order to
   9     make two serious points about figures. First of all
  10     there is an inevitable variability about figures which
  11     can be very misleading. Secondly, any picture which is
  12     painted by figures must necessarily be general.
  13        We in this Inquiry must never forget when
  14     a general picture is painted, and perhaps particularly
  15     when it is painted by statistics, that at the centre of
  16     the figures are cases of individual children, some of
  17     whom will have been treated and will thankfully have
  18     survived, some of whom will have been treated and sadly
  19     will either have suffered subsequently in consequence of
  20     the treatment or of the condition which led to the
  21     treatment and others who will have lost their lives,
  22     whether because of the underlying condition for which
  23     they suffered or because the hospital failed to care for
  24     them as it might have done.
  25        Statistics are only part of the picture and any

   1     figures are variable. It is false to treat a particular
   2     figure as being any more than within a range of likely
   3     figures. They can distract attention from
   4     the individual case which matters.
   5        But perhaps most important of all is the message
   6     which our statisticians have given us repeatedly:
   7     statistics on their own cannot show by demonstrating let
   8     us suppose low mortality rates at Bristol that surgical
   9     competence or any other factor was the cause of that
  10     success. If it shows the opposite, it cannot show what
  11     the cause was of the high mortality rate. What
  12     the statistics can do is show that there was
  13     a difference. They cannot on their own show what was
  14     the reason for that difference.
  15        We will explore in evidence today six data sets.
  16     The evidence you will hear will first of all be that of
  17     Professor Campbell, who will explain far better than
  18     I can possibly hope to do and much more authoritatively
  19     some of the statistical concepts which underlie
  20     the examination which others have conducted.
  21        Secondly, we will hear from Professor Stephen
  22     Evans as to his analysis of three local data sets:
  23     the patient administration system in Bristol;
  24     the Inquiry's own examination of the clinical case
  25     records and what they have shown -- bear in mind that

   1     some 2,000 cases have been looked at, coded and
   2     analysed, and his is that analysis -- and the surgeon's
   3     logs from Mr Wisheart and Mr Dhasmana.
   4        We shall then hear from Dr Aylin as to
   5     the hospital episode statistics a national data set.
   6     That will be related by him and by Professor Gordon
   7     Murray to the Cardiothoracic Surgical Register of
   8     the United Kingdom. Both those data sets provide
   9     something of a national picture. Professor Murray will
  10     also compare the Cardiothoracic Register with a register
  11     kept locally by cardiologists, the South Western
  12     Congenital Heart Register.
  13        Each of them in turn will present their findings
  14     to you, each of them will be asked some questions at
  15     the end of their presentation, and each of them expects
  16     to show you various slides to demonstrate the points
  17     that they have to make.
  18        At the end of the day we shall have a synthesis of
  19     those various different data sources prepared for us by
  20     Dr David Spiegelhalter. He will indicate what in his
  21     view, and I expect the other statistical analysts to
  22     contribute to this in discussion, is the way forward and
  23     what the Inquiry needs to do next in order to examine
  24     what it is that the statistics are actually telling us
  25     so far as they can.

   1        One of the difficulties with having six data sets
   2     is that there are inevitably different ways in which
   3     each of the groups that compile those data sets have
   4     gone about their task. If you take six people looking
   5     at the same data but separately, they will approach it
   6     in different ways. They will group, for instance,
   7     certain ages, they will take certain age ranges, they
   8     will look at certain operations in a certain way and
   9     immediately you have a problem of comparing one data set
  10     with another because the classification, the approach of
  11     each to the underlying data, is different.
  12        So if any message is to be learned from
  13     the available data, it is necessary that they look at
  14     that data in the same way if they can. The problems
  15     that occurred to the Inquiry in, as it were, getting
  16     the data sets to speak the same language so that they
  17     could usefully be compared -- and comparison is
  18     important if one is to gain credibility from the data,
  19     given the particular problems that a number of the data
  20     sets had that were identified to us back in July --
  21     the essential problems were those of definition: how
  22     does one define the operative procedure that is used?
  23     Each operation is, as Professor Anderson indicated to
  24     us, to an extent unique because the anatomy of each
  25     heart will be different from the anatomy of each other

   1     heart. So although one may say, "This is a truncus,
   2     this is a case of transposition of the great arteries",
   3     it is never quite so simple.
   4        One of the problems therefore is comparing an
   5     analysis, for instance, of the PAS system locally which
   6     was made by administrative clerks with no particular
   7     clinical expertise looking at the discharge letters and
   8     working out from those what the nature of the operation
   9     was and under which heading which group it should be
  10     placed, comparing that with the surgeon's logs, where
  11     the surgeons have their own view as to how the operation
  12     should be classified and, when one comes to look at
  13     the whole position nationally, assessing how on earth
  14     one compares Bristol with the rest of the country
  15     without knowing for certain that people in one centre
  16     compared to people in another have adopted exactly
  17     the same pattern and the same degree of approach,
  18     the same approach, to similar data.
  19        What the Inquiry decided to do in order to allow
  20     a synthesis was to decide that it was necessary first of
  21     all to class procedures as either open or closed, and to
  22     class them as open if the procedure was one which was
  23     performed on cardiopulmonary bypass.
  24        Secondly, it was necessary to group the procedures
  25     in a valid way, valid both clinically and

   1     statistically. Grouping is important for statistical
   2     purposes. If you go back to my example of each heart
   3     being unique, it would be unhelpful in any form of
   4     analysis or comparison to say, "The most one has in any
   5     particular data set is one case, because every case is
   6     unique." Although it is right, there has to be a measure
   7     of similarity -- only a measure, not complete
   8     similarity -- to enable one to have a sufficient number
   9     to conduct an analysis.
  10        You will hear in a moment or two that the Inquiry
  11     decided, on having taken advice -- and it has to be said
  12     that the advice was by no means entirely consistent,
  13     entirely with one voice -- to rank the procedures under
  14     13 headings; classify them under 13 headings; but,
  15     having classified them, to rank them. Let me
  16     demonstrate what I mean by showing you the first slide
  17     of the day, INQ 13/54. What you have here is a list of
  18     the groupings which the Inquiry has adopted for
  19     the purpose of the various analyses. You will see that
  20     each of the analyses approaches the data sets in
  21     the same way.
  22        There are 13 groups, "G" for group, and then
  23     the number. The second box, OPCS 4, procedure code,
  24     a word of explanation: throughout much of the period
  25     with which we have been concerned the large national

   1     data set hospital episode statistics has described
   2     operations by a mixture of letters and numbers, an
   3     "operation code". The relevant codes are K and L
   4     covering cardiac and vascular conditions.
   5        In the list of codes a separate number is given
   6     for the description of different procedures. Bear in
   7     mind these are procedures and not diagnoses. That is
   8     a distinction which again has to be borne in mind in
   9     comparing data sets, some of which look at diagnoses and
  10     some of which look at procedures.
  11        What is under OPCS 4 procedure codes you can see,
  12     and the detail for the moment does not matter, is
  13     attributed to one or other group and then a description
  14     is given. G2 and G3 demonstrate, as you will hear in
  15     evidence, some of the difficulties of allocating
  16     a particular operation to a particular group. They
  17     demonstrate one of the problems with data sets, because
  18     of necessity once there has been a description in order
  19     to understand data over a period of time the same
  20     description has to be applied to the same procedure
  21     throughout history.
  22        The problem is that life is not like that.
  23     Medicine moves on. Procedures change. They develop.
  24     For instance, when the data sets reported upon
  25     the switch operation in the early 1980s, they would have

   1     been reporting much more on what we know as Mustard and
   2     Sennings operations, interatrial switches for the same
   3     condition than the data set of the 1990s which will be
   4     reporting much more on arterial switch operations about
   5     which we have already heard in evidence.
   6        You will see when the data is examined that it
   7     appears that there is quite a grey area around
   8     the margins as to which operation, which procedure,
   9     should in the data sets that we will look at be put
  10     under which heading. To that extent the data has to be,
  11     it is, uncertain. To that extent, any conclusions that
  12     might be drawn in looking simply at group 2 in isolation
  13     or group 3 in isolation would have to be very cautious
  14     indeed.
  15        It may be that sense can be made by grouping both
  16     or looking at group 2 and group 3 together. But bear in
  17     mind the purpose of dividing it up into 13 groups was to
  18     look at each of the 13 groups individually at
  19     the outset.
  20        The fourth heading across the page, "Primary
  21     procedure ranking", has a number of numbers attributed
  22     to the various operations. The problem here is
  23     essentially a practical one. When the clerk,
  24     the administrative clerk or the person compiling
  25     the data set, comes to record his particular operation

   1     as one or the other, and he looks at the list
   2     of procedures which may have been followed, if he has
   3     one code and one code alone to use, which does he
   4     choose? If you might, for instance, have something
   5     which will be classed as a Fontan type operation, G9,
   6     and if in association with that there needed to be
   7     a closure of an atrial septal defect, which of those two
   8     procedures would be coded?
   9        Here the Inquiry had to take clinical advice from,
  10     it has to be said, the bulk of our expert team of
  11     cardiologists, cardiac surgeons and others who were
  12     identified in a note giving full details of this
  13     procedure published today, had to identify which should
  14     take precedence. That is the ranking procedure that is
  15     indicated by the list which is third from the right on
  16     the chart as you look at it.
  17        So that, if there was a truncus arteriosus, that
  18     would in precedence to any other condition identified be
  19     the grouping that was chosen. You will see that
  20     therefore, if one comes down to the last of the open
  21     operations, there are 13 groupings in total, two closed,
  22     11 open; 11, group 6, closure of secundum and sinus
  23     venosus atrial septal defects. But that is not going to
  24     be coded, except where it occurs on its own as an open
  25     condition.

   1        Of course one of the further problems that anyone
   2     may have in trying to group operations under one of
   3     these headings, the primary procedure groupings, is that
   4     it may just not fit. Take a transplant -- not in fact
   5     performed in Bristol, but bear in mind that there will
   6     be comparisons with other centres where transplants may
   7     have been performed. There are three in the country.
   8     There is no heading under which something such as
   9     a transplant can be placed. As a result, there has to
  10     be a residual coding, and there was indeed in
  11     the national data sets a residual grouping for
  12     procedures which could not be coded under one of
  13     the more precise letters and numbers used by OPCS.
  14        So for our purposes the statistical analysts have
  15     not only looked at 13 procedure groups, but also looked
  16     at open operations, all open operations, whether the 13
  17     or more, 14, 15, 16, 20, whatever it might be, and
  18     compared those with open operations elsewhere, and all
  19     closed operations with all closed operations elsewhere.
  20        When comparing one centre with another there can
  21     of course be a comparison made across each of these
  22     individual groupings, each of the 13, or indeed across
  23     the general open and general closed categories. But
  24     please remember that the boundaries may not always be
  25     clear between one group and another, and there may be

   1     some groups in some centres which are not shown here.
   2        One of the reasons why these particular groupings
   3     were chosen is explained by the far right-hand column on
   4     the chart, "Map to UKCSR". UKCSR stands for United
   5     Kingdom Cardiac Surgical Register. As we already heard
   6     in the Inquiry, this register was throughout the period
   7     that the Inquiry is concerned with, except for a few
   8     months in the middle 1990s, collecting data sent into it
   9     by centres and allowing any one centre to compare its
  10     performance against the national performance of the year
  11     or two before.
  12        The precise data which gave rise to those reports
  13     is of course not now readily available. What we have is
  14     simply the groupings which the Cardiothoracic Register
  15     had. It is a valuable data source, particularly since
  16     it was reported to the Cardiothoracic Register by or on
  17     behalf of the clinicians most closely connected with
  18     the care of the particular child at the time.
  19        In order to make use of that data set there has to
  20     be a means of bringing, if you like, the other data sets
  21     into line with it. This, in my simple understanding, is
  22     what is meant by "mapping", trying to fit the procedures
  23     identified in the other data sets to the diagnoses with
  24     which the Cardiothoracic Surgical Register deals. That
  25     is some explanation as to how one can take the groupings

   1     which you see here and make sense of them in
   2     a comparison with the Cardiothoracic Surgical Register.
   3        The statistical evidence that you will hear was
   4     essentially of two sorts. One will establish Bristol's
   5     performance as best the data can tell us. Secondly, it
   6     will compare that performance with elsewhere.
   7        In looking at the local data, there is some
   8     difference of numbers; bear in mind that the PAS,
   9     patient administration system, is coded by
  10     administrative clerks who are not medically qualified,
  11     the surgeons' logs are not formally validated, but
  12     the data may be in small groups and therefore subject to
  13     large statistical variation -- go back to my example of
  14     tossing the coin -- and much of the data was not
  15     collected for the purpose of assessing the adequacy of
  16     care. That is the local figures.
  17        In comparing data with elsewhere it needs to be
  18     borne in mind that the data may not have been validated
  19     and may therefore be inaccurate. Where a comparison is
  20     based on data from the Cardiac Surgical Register for
  21     the period from 1985 to 1991, there is no cross-check
  22     with the national HES, hospital episode statistics,
  23     system.
  24        Professor Murray will tell you that it is clear
  25     that the primary data quality of the UKCSR is poor, and

   1     accordingly the ordinary degree of variability,
   2     the range within which you might expect figures to fall,
   3     is all the greater. Professor Murray will emphasise
   4     that he had been unable to visit cardiac units elsewhere
   5     in the country to assess the quality of their primary
   6     data, and further work to assess that quality will be
   7     needed before one could assess the weight which should
   8     be placed on the results of comparative analyses.
   9        When comparing Bristol with other centres
  10     a twofold comparison is adopted. A word of explanation
  11     of this before the evidence is called. First, there is
  12     a comparison of Bristol children with all children
  13     elsewhere. This is, you will hear, compares the rates
  14     of mortality which appear on the face of the data with
  15     those collected from the whole of the rest of
  16     the country grouped together.
  17        Secondly, Bristol as a centre will be compared
  18     with other centres. For this purpose the average of
  19     the performance by centre was determined. It is obvious
  20     that no centre will be exactly average. Some will, by
  21     reason of simple chance variability, in any one year
  22     have more or less deaths in any given operation than any
  23     other centre. The greater the number of operations and
  24     the periods considered, the greater the chance that
  25     the centre will both appear to have above average number

   1     of deaths in some procedures and below average in
   2     others.
   3        It may be distressing to many parents to hear
   4     the terms in which our statistical analysts will express
   5     this. They will talk of excess deaths. It is essential
   6     to realise that this is simply a way of expressing an
   7     apparent difference, and it is important to remember
   8     from everything that I have already said that
   9     the difference may not be real and that some difference
  10     is inevitable. It will be most unfortunate if a simple
  11     and ordinary way in which statisticians express
  12     themselves may seem be to callous, unfeeling and
  13     upsetting.
  14        To say, for instance, that in any particular
  15     centre there have been, say, six excess deaths is not
  16     passing a judgment as one would in a court of law
  17     assessing whether there had been clinical incompetence
  18     or not. If this is not understood, there is a very
  19     great risk that someone might ask, "Which were the six
  20     deaths?" or even worse, "Was it my child?" To ask those
  21     questions will be to misunderstand the purpose of
  22     the statisticians expressing themselves as they do.
  23     They are painting a picture with a variability, with
  24     data which may not be entirely reliable in order to
  25     provide a generalised comparison.

   1        If the point needed to be made, you will see that
   2     when they present their papers that quite often
   3     the excess deaths in one or other centre are presented
   4     with a decimal point. To say that there were six excess
   5     deaths in this or that centre might understandably give
   6     rise to the question, "Which were they?" But if the
   7     expression used is, for instance, 6.9, then I hope it
   8     will be clear to all that this is one way of expressing
   9     a difference. It is not an attempt to draw conclusions
  10     in any individual case.
  11        A word about the groupings which make it almost
  12     inevitable that there is likely to be an expression of
  13     excess deaths used in the statistical sense that I have
  14     mentioned in almost any centre. The data have been
  15     grouped in epochs, taking us from January 1984 to
  16     December 1987, epoch number 1; January 1988 to December
  17     1990, number 2; January 1991 to March 1995, number 3;
  18     and April 1995 to December 1995, number 4.
  19        Bear in mind, please, when we come to epoch number
  20     4 that the nature of the operations performed may not
  21     have been of the same type of case, say, mixture as in
  22     the preceding two or three epochs. The data have also
  23     been grouped by age. The ages chosen for the purposes
  24     of analyses are nought to 90 days, 90 days to 365 days,
  25     and 1 year to 15 years.

   1        Again, you come back to points of difference
   2     between the data sets. The Cardiothoracic Register, for
   3     instance, has no cut off in age. There is no way of
   4     knowing simply from the figures presented whether it is
   5     looking at any particular number of children over
   6     the age of 16.
   7        There are therefore in total four epochs, three
   8     age groups, that itself will give you 12 comparisons,
   9     and we have 13 procedure groupings plus the open/closed
  10     difference.
  11        You will hear that there was no significant
  12     difference between Bristol and children elsewhere in
  13     England, and indeed between Bristol as a centre and
  14     centres elsewhere in England so far as closed procedures
  15     are concerned.
  16        So far as open procedures are concerned, you will
  17     hear a considerable amount of evidence. The overall
  18     picture is perhaps best summarised by showing you my
  19     second slide taken from the reports, INQ 15-4. Can we
  20     scroll up a bit, thank you. This comes from David
  21     Spiegelhalter's paper. It shows that over the period
  22     1988 to March 1995 there appears to be approximately two
  23     times the rate of death in open operations across all
  24     age groups combined. You will see immediately that that
  25     is expressed in the third column as excess deaths. You

   1     will notice, to emphasise the point I have made that
   2     this is simply a way of demonstrating a difference, that
   3     the excess deaths recorded have decimal points to them.
   4        You will see from Dr Aylin's evidence, when he
   5     gives it, that the mortality is highest in the youngest
   6     age group, nought to 90 days. Bear in mind that, since
   7     there is also evidence that Bristol operated on a lower
   8     percentage of young babies than other centres did and on
   9     a greater proportion of Downs Syndrome children than
  10     other centres did, these factors may mean that there has
  11     to be further examination of the difference. It would
  12     not be right without further careful consideration to
  13     assume that the fact of difference implied a reason for
  14     the difference.
  15        Dr Aylin will present a comparison of the apparent
  16     mortality rate of Bristol compared to the 11 other
  17     principal centres in England. Bristol is significantly
  18     different. It is an outlier compared with all other
  19     centres, save one which is an outlier in the 1 to 15
  20     year age group. That other centre is known as centre
  21     number 10 in the analyses you will see.
  22        When our statistical analysts did the work, they
  23     did not know which centre it was. However, this Inquiry
  24     has made a commitment to openness. Since it may well be
  25     there are problems and difficulties with the figures,

   1     even beyond those that have so far been identified, and
   2     they need to be stressed, it is important that anyone in
   3     a position to contribute should know the identity of all
   4     the other centres referred to by number in the figures
   5     and diagrams that you will see.
   6        Accordingly let me give you alphabetically
   7     the centres and their identifying numbers. Birmingham
   8     Children's Hospital will be known in the figures that
   9     you will see as centre 11; Freeman Hospital, which is
  10     now part of the Newcastle upon Tyne hospital's NHS Trust
  11     as centre number 9; Great Ormond Street Hospital, which
  12     is now part of the Great Ormond Street Hospital for
  13     children NHS Trust, as centre number 8; Guys Hospital,
  14     now part of the Guys and St Thomas Hospital NHS Trust,
  15     number 5. I should emphasise that these numbers are
  16     arbitrary numbers given by the Inquiry to these
  17     centres. They do not imply any form of ranking
  18     whatsoever. It is not a question of number 1 being
  19     best, number 11 being worst or anything of that sort.
  20        Harefield Hospital, now part of the Royal Brompton
  21     and Harefield NHS Trust, is centre number 10;
  22     Killingbeck Hospital, Leeds, part of the Leeds Teaching
  23     Hospital's NHS Trust, is centre number 3; the Royal
  24     Brompton SHA, special health authority, now part of
  25     the Royal Brompton and Harefield NHS Trust, is centre

   1     number 12; the Royal Liverpool Children's Hospital, part
   2     of the Alderhey Children's Hospital and Royal Liverpool
   3     Children's NHS Trust, as centre number 6; Southampton
   4     University Trust, Southampton University Hospital's NHS
   5     Trust, centre number 7; Glenfield Hospital, Leicester,
   6     not a designated centre, but it did a significant number
   7     of operations, now part of the Glenfield Hospital NHS
   8     Trust, centre number 2; the Radcliffe Infirmary at
   9     Oxford, the Oxford Radcliffe Hospital NHS Trust, centre
  10     number 4; the United Bristol Healthcare NHS Trust,
  11     Bristol Royal Infirmary, as you might expect in this
  12     Inquiry, centre number 1.
  13        You will see that centre number 10 is now part of
  14     the Royal Brompton and Harefield NHS Trust. It was
  15     Harefield Hospital. A word of caution: it would be
  16     unduly alarmist to conclude that Harefield was a poor
  17     hospital or to suggest that this Inquiry had uncovered
  18     something that had not been appreciated to some extent
  19     before.
  20        Moreover, in drawing comparisons between Bristol
  21     and centre 10, it is known that centre 10 performed a
  22     much higher proportion of its procedures on children
  23     over one year of age, a much higher proportion of its
  24     work was outside the 13 procedure groups that I have
  25     mentioned and fell into the other category, and both of

   1     those features are potentially associated with higher
   2     risks and hence with poorer outcomes.
   3        This makes a point which needs to be emphasised
   4     throughout. The purpose of statistics at their best is
   5     to compare like with like. The statistical analysts
   6     have in the case of Bristol done what they can to deal
   7     with the question of case mix. There is not much
   8     information to be given. Because the subject of our
   9     Inquiry is not centrally centre 10 or any other centre,
  10     it would be wrong to assume without Inquiry that
  11     the case mix was the same.
  12        Let me give an example. If a particular hospital
  13     had -- this is purely a hypothetical example, I hasten
  14     to had -- a policy of treating any case, however poor
  15     the outcome was likely to be, even though it might be as
  16     low as 1 per cent, the mortality figures produced by
  17     that hospital would be very different from the other
  18     hospitals faced with the same type of patient which
  19     declined to operate, perhaps on perfectly good clinical
  20     grounds, upon the same group of patients.
  21        The case mix of the patients would be different.
  22     The case mix would in such an example be an obvious
  23     possible explanation for any statistical difference
  24     the figures showed.
  25        I do not suggest that this is essentially

   1     the difference between Harefield and Bristol. I am not
   2     in a position to make a suggestion one way or
   3     the other. But it must be borne in mind that there may
   4     well prove to be a difference which is of the greatest
   5     significance in interpreting these figures.
   6        I should emphasise that the statistical analysts
   7     have not been able to visit the other cardiac units to
   8     assess their primary data quality. Further work to
   9     assess that quality would be required before one could
  10     assess the weight which could be placed upon it.
  11        Moreover, as you will come to see from
  12     the figures, centre 10 is not the only centre which has
  13     some outlying results. Accordingly, the figures should
  14     be treated with some caution. Anyone listening must be
  15     remember that the figures at Bristol have been examined
  16     across a range of data sets and in much greater detail
  17     than has been possible with other centres. That said,
  18     if there is to be any explanation as to the reasons why
  19     Harefield appears to be an outlier as well as Bristol,
  20     that is a matter for Harefield to explain.
  21        The Department of Health knows today this Inquiry
  22     will reveal the performance of the various centres
  23     relative to each other. It is likely to be a matter of
  24     interest in the locality in which each centre is placed
  25     as to how that centre has performed. I would hope that

   1     any comment which is made, perhaps in the press, perhaps
   2     by others who read this on the Internet, must be subject
   3     to the caveats which I have already entered and which
   4     will be entered in the course of the evidence today both
   5     orally and in the written papers submitted.
   6        The Royal Brompton and Harefield Trust has been
   7     told of the figures, as have the other centres.
   8     I should emphasise as one would hope to be the case that
   9     it is open and forthcoming about its figures.
  10        With that introduction, which I hope is not so
  11     obvious as to be simplistic, I shall call the evidence
  12     before you to put further detail on that which I have
  13     given to you in outline.
  14        Sir, the way in which we propose to arrange
  15     matters is that we shall begin with Professor Campbell,
  16     if he would come up to the desk, and for the purpose of
  17     enabling discussion if necessary between all
  18     statisticians, we shall arrange two chairs at the front
  19     and he will be joined by Professor Evans, whose
  20     presentation will be next.
  21        If the expert table to my right could then be
  22     filled, please, by Dr Aylin, Dr Spiegelhalter and
  23     Professor Murray. Sir, it would be convenient I think
  24     to swear each in turn as they come to give their
  25     presentation rather than all now. If therefore we may

   1     begin, please, with Professor Campbell.
   2   THE CHAIRMAN: I think that is right. Thank you for that.
   3     I was just making sure everyone was comfortable and able
   4     to see. Thank you.
   5        PROFESSOR MICHAEL JOSEPH CAMPBELL (SWORN):
   6            Examined by MR LANGSTAFF:
   7   Q. Professor Campbell, your full name, please?
   8   A. Michael Joseph Campbell.
   9   Q. Can you tell us a bit about yourself and why you are an
  10     expert, briefly?
  11   A. I am Professor of Medical Statistics in the University
  12     of Sheffield. Previously I used to work in
  13     the University of Southampton. I have no idea why I am
  14     an expert, except I have written two books. One is
  15     called "Medical Statistics - a Commonsense Approach" and
  16     one is called "Statistics from Square One".
  17   Q. What I am going to ask you to do, you have read through
  18     the statistical evidence which is later to be presented
  19     to us, I think, and you have formed a view of those
  20     matters which may need to be explained first of all in
  21     greater detail to what one might call the wider audience
  22     and any explanation that may be needed for a more
  23     scientific and technical audience. You are in
  24     a position to do that for us, are you?
  25   A. I am.

   1   Q. What role, as you see it, does statistics play in this
   2     Inquiry?
   3   A. I think statistics has a number of roles. I think
   4     the first and probably most important one is to
   5     ascertain the data validity and to make sure that
   6     the data that we are actually examining is
   7     representative of what really actually happened in
   8     the various centres.
   9        Data validity and design of studies is central in
  10     statistics to make sure that we are actually basing our
  11     conclusions on solid evidence. Having collected
  12     the data, the next question that statisticians have to
  13     ask is how these differences could have arisen and
  14     whether the differences are purely due to chance or
  15     whether there is some inherent difference between
  16     different centres that cannot be attributed to chance,
  17     and that is where the statistical analysis comes in.
  18        Finally, I think quite importantly, statistics
  19     need to be able to present these results in a way that
  20     is easily understood by the general public. I think
  21     data presentation is also very important.
  22   Q. So collection, analysis and presentation?
  23   A. Correct.
  24   Q. So far as the analysis is concerned, to what extent in
  25     that analysis does the statistician try to demonstrate

   1     whether the results are beyond what one would expect as
   2     a matter of chance or not?
   3   A. Well, statisticians generally try and set up a null
   4     hypothesis which they then try and ascertain whether
   5     the data are congruent with this particular hypothesis.
   6     The example that you gave earlier on tossing a coin, for
   7     example, you toss the coin a number of times. Your
   8     null hypothesis might be that the coin is unbiased, and
   9     this would be your normal null hypothesis, that
  10     the probability of a head is a half. Then you collect
  11     your data and then you decide, "I assume that the coin
  12     is unbiased. What is the probability of getting
  13     the observed number of heads that I have seen?" This is
  14     where assessing whether the probability is due to chance
  15     or not.
  16   Q. By unbiased we mean that the coin is unweighted or it is
  17     not a double headed coin; there is nothing odd about it?
  18   A. Correct.
  19   Q. The word "bias" is something we may come across. Would
  20     you like to say a couple of words about how
  21     statisticians read the word?
  22   A. There are a large number of ways that you can interpret
  23     bias. I think one of the most important ones in
  24     the Bristol Health Inquiry is whether the way that
  25     the data were presented in Bristol is different from

   1     the way it was presented or collected in other areas.
   2     So, for example, were Bristol more or less scrupulous in
   3     reporting their mortality data and were they more or
   4     less scrupulous in collecting all the babies that came
   5     to the hospital? I think that is where you can get
   6     bias, is where you have differential reporting of
   7     results from different centres.
   8   Q. Suppose, for example, that Bristol were scrupulous about
   9     collecting data on deaths and other centres were not.
  10     What effect would that have upon the apparent
  11     performance of Bristol compared to these other centres?
  12   A. Clearly if Bristol was scrupulous and reported all their
  13     deaths and the other centres did not report all their
  14     deaths, then in fact it would make Bristol appear worse
  15     than the other centres.
  16   Q. And is there, as it happens, some suggestion in what you
  17     have seen of the statistics that Bristol were
  18     scrupulous?
  19   A. There is some suggestion, but it seems difficult to
  20     understand how -- very difficult to understand how there
  21     could be loss from the other centres to explain
  22     the differences that we have actually observed.
  23   Q. We will come back to that in a little while, if we may.
  24     You mentioned that the statistician begins by taking an
  25     null hypothesis, and you demonstrated that in terms of

   1     the coin and say, "What we want to assume is that
   2     the coin is a perfectly ordinary coin with heads on one
   3     side and tails on the other." What conclusion would you
   4     be likely to draw if, let us say, you tossed the coin
   5     100 times and on 98 occasions out of the 100 it came
   6     down heads?
   7   A. You could work out the probability of observing 98 heads
   8     or 99 heads or 100 heads assuming that the probability
   9     of a head was still a half, and you would find that
  10     this probability was actually very small and therefore
  11     you might conclude that the coin was in fact not an even
  12     balanced coin, that in fact it was biased in some way.
  13        So you make up the hypothesis, which is that
  14     the coin is unbiased, and then you look at the data and
  15     then you reject the hypothesis. That is essentially
  16     the statistical method which is very comparable to
  17     the scientific method where you make predictions from a
  18     theory, you then observe the data and then, if your data
  19     and the theory do not correspond, you reject your
  20     theory.
  21   Q. You have a slide for us. I think it is INQ 17-1.
  22   A. I wanted to emphasise here, and in fact since having
  23     discussions with Dr Spiegelhalter I think perhaps
  24     the emphasis is not necessarily warranted too much, in
  25     the different types of statistical inference there are

   1     two basic approaches to statistical inference which are
   2     called the Bayesian approach and the frequentist
   3     approach. I put Thomas Bayes here to show that in fact
   4     Bayesian methods have a long and well-established
   5     tradition and that Thomas Bayes published his results
   6     posthumously and it has been said that it is a shame a
   7     lot of other statisticians did not follow his example.
   8        The important difference is that frequentists tend
   9     to think in terms of repeatedly running a study and
  10     the long-term proportion of successes. So this is
  11     the way you tend to think about probability. You tend
  12     to think of the probability of a boy being born, you
  13     observe a large number of successes or failures or
  14     whatever, and you end up with say 52 boys out of 100.
  15     This means that the probability of a boy being born is
  16     52 out of 100 or 0.52.
  17        What a frequentist thinks after an investigation
  18     is exactly what I said about the coin tossing. They
  19     ask, "What is the probability of getting these data if
  20     my model, if my hypothesis, is correct?"
  21        Bayesians tend to give probabilities of things
  22     that are not directly observable and that they can
  23     attach probabilities to hypotheses such as the true
  24     underlying mortality rate being 10 per cent.
  25     Essentially they have what are called prior probability

   1     before the experiment and posterior probabilities after
   2     the experiment.
   3        They tend to attach probabilities like the
   4     probability that it is going to rain tomorrow is 20
   5     per cent. You attach a probability to that. But you
   6     cannot imagine running tomorrow 100 times to see if it
   7     rains ten times.
   8        They are able to give -- after an investigation
   9     they say, "Given what I believed about my model before
  10     the investigation and given the data I have collected,
  11     what is the probability that my model is now correct?"
  12     This is a very common way of arguing in medicine as well
  13     where a patient comes in to a surgery and the doctor
  14     will assess their possibility of having a certain
  15     disease. They will then question the patient and elicit
  16     certain symptoms and then they will modify their
  17     probability that the patient has a particular disease.
  18     If their probability is sufficiently high, they might
  19     refer them on for investigation.
  20   Q. In the surgeon's case or the GP's case, he may have what
  21     is called a differential diagnosis, have a number of
  22     ideas in his mind and begin to discard them as he gets
  23     more evidence?
  24   A. Yes, correct. He will discard them depending on
  25     the probabilities that he has -- the symptoms he has

   1     elicited from the patient.
   2   Q. You have used words on your slide "prior probabilities"
   3     and "posterior probabilities". The posterior
   4     probability is what?
   5   A. The reason I put this on the slide is the posterior
   6     probability is the measure of how much you believe your
   7     model is actually correct, your hypothesis is actually
   8     true, given that you have collected some data to either
   9     refute or accept this particular hypothesis.
  10   Q. The statisticians in their reports to us have used
  11     a Bayesian approach, not a frequentist approach. Does
  12     it, do you think, make a difference? If so, to what
  13     extent?
  14   A. I have had long, long discussions, especially with
  15     Dr Spiegelhalter on this particular issue. Although
  16     the method is ostensibly Bayesian, in fact you can
  17     demonstrate that in fact it is largely a frequentist
  18     approach.
  19   Q. Best of both worlds.
  20   A. In fact if we go on to the next overhead.
  21   Q. Number 2, please.
  22   A. I said we have two hypotheses, H0, which is that Bristol
  23     is no different from the other centres, and H1 that
  24     Bristol is quantitatively different from the other
  25     centres. The data that was collected is the mortality

   1     from 12 centres.
   2        So what the frequentist can answer is, "What is
   3     the probability of getting our data" -- and
   4     unfortunately I have to put in brackets (or data more
   5     extreme from H0), which means further away from the null
   6     hypothesis -- "assuming that Bristol is in fact no
   7     different from the other centres?"
   8        In the tables that are given in the evidence this
   9     is the probability -- that big P means
  10     the possibility -- of the data given the
  11     null hypothesis, or it is called the P value. In some
  12     of the earlier tables you will find mentions of P
  13     values. That is what the P value is telling us.
  14        What the Bayesian inference can answer is, "What
  15     is the probability that Bristol is different from
  16     the other centres given the data?" That is
  17     the probability of H1, which is the hypothesis that
  18     Bristol is different, given the data. That is also
  19     given in the tables as well, of the probability attached
  20     to the excess deaths or the deaths greater than
  21     expected.
  22        In fact it turns out, because the way the prior
  23     distributions were chosen and also because of the way
  24     that the hypothesis was set up, which was that we take
  25     Bristol out of the equation and we then try to predict

   1     from the other centres what we should have expected in
   2     Bristol, which is the null hypothesis, we can in fact
   3     interpret the probabilities given in the Bayesian method
   4     in a very similar way to the probabilities we get under
   5     the frequentist approach, which I think is a very nice
   6     synthesis.
   7   Q. So essentially which ever approach had been taken is
   8     likely to have produced pretty much the same results,
   9     given the data?
  10   A. That is my opinion, yes.
  11   Q. You mention in the middle of that slide the P value.
  12     I wonder if you would like to say some words by way of
  13     explanation as to what a P value is and what, if any,
  14     comfort or the opposite we may take from it?
  15   A. If we take your example before of tossing a coin 100
  16     times and observing 98 heads, we can work out either by
  17     computer simulation or by mathematics the probability of
  18     observing this particular run of events if we assume
  19     the coin is unbiased. This probability is the P value.
  20     It is convention to reject the null hypothesis, which is
  21     the coin is unbiased, if the P value is sufficiently
  22     small. The usual accepted level for rejection is 5
  23     per cent. So we say that, if there is only a 1 in 20
  24     chance of getting our observed data or, more extreme, if
  25     the null hypothesis is true, then we are going to reject

   1     the null hypothesis.
   2   Q. Would it be the case that if the coin had been tossed 90
   3     to 100 times and come down heads on 94 occasions, not
   4     95, that you could not safely assume statistically that
   5     the coin was biased?
   6   A. It could be that if you tossed the coin 94 times your P
   7     value might be 0.06 -- sorry, if you tossed it 100 times
   8     and it came up heads 94 times, your P value would be
   9     0.06. If you tossed it 100 times and it came up 95
  10     times, your P value would be 0.04. Therefore you could
  11     reject it on the latter case but not on the former.
  12   Q. If we think in terms of tossing a coin, this is the
  13     example we have used, if anything has or is given
  14     statistical significance, does it mean that as a matter
  15     of numbers and mathematical calculation it is
  16     the equivalent of, as it were, tossing the coin and
  17     finding that on less than 5 occasions out of 100 it came
  18     down one way as opposed to the other?
  19   A. Sorry, could you repeat that?
  20   Q. Yes, I was trying to make the example simple. It is my
  21     fault. When we see in the course of the analyses
  22     statistical significance or a P value of less than 0.05
  23     ascribed to a particular data set, does that mean that
  24     you can be as confident that that is not due to chance
  25     as you would be in the case of a coin which had been

   1     tossed and on 95 occasions out of 100 it came down on
   2     one side only?
   3   A. You would have to -- I do not know what the actual
   4     probability of getting a 95 -- perhaps one of my learned
   5     colleagues here could tell me. Very, very small. But
   6     essentially you interpret the probability of -- if you
   7     have a P value of less than 5 per cent, it would mean
   8     that if you were to run the whole scenario 100 times you
   9     would only expect to see this particular event 5 times
  10     out of 100 or less.
  11   Q. Thank you. You heard what I said about excess deaths in
  12     the course of the introductory remarks that I have
  13     made. Broadly, and please do not be frighten to offend
  14     me, was I right in the approach that I took to it?
  15   A. Yes, I believe you were. One important thing to realise
  16     is that statistically speaking excess deaths could be
  17     negative as well as positive. It just means that they
  18     are different from predicted.
  19   Q. So by "excess" we should really read "different number
  20     of" rather than "excessive" in the ordinary colloquial
  21     sense?
  22   A. Yes.
  23   Q. Through the statistics which we will see, then we may
  24     have talk of P values and we have talk of excess
  25     deaths. So far as P values are concerned, there is some

   1     reference that we will see to 95 per cent intervals.
   2     Could you give us an explanation of that?
   3   A. Yes. The authors have been quite careful to refer to 95
   4     per cent intervals. The frequentist approach is to call
   5     things 95 per cent confidence intervals. Essentially
   6     that enables us to -- if we have a 95 per cent
   7     confidence interval, it says -- let us go back to
   8     the coin tossing experiment again, since it seems to be
   9     generally understood.
  10        We observe a certain number of heads, say 80
  11     per cent, 80 out of 100. We can calculate about that 80
  12     per cent an interval. If we actually ran this
  13     experiment 100 times we could each time we ran
  14     the experiment calculate this interval, then 95 per cent
  15     of the intervals that we calculate would include
  16     the true probability of the coin coming up. So if
  17     the coin was actually unbiased, then we would expect
  18     that 95 per cent of these intervals would include 50
  19     per cent or P as 0.5 as the null hypothesis. That is
  20     a 95 per cent confidence interval.
  21        When you go on to 95 per cent interval, then this
  22     is a slightly different approach, but it is essentially
  23     the same. But it means that we have 95 per cent
  24     confidence that the true value, the value underlying
  25     the hypothesis, is somewhere within that interval;

   1     although it is important to realise that most of
   2     the emphasis will lie in the centre of the interval and
   3     not at the extremes.
   4   Q. Excess deaths was the other part that I was going to ask
   5     you about. Is there any sense in which statistically
   6     one can identify which deaths are excess?
   7   A. No, no. Essentially, as I was saying before about
   8     the frequentist approach to probability, out of 100
   9     people you could say that 10 per cent are likely to die,
  10     but there is no way of identifying which particular
  11     10 per cent. It is a bit like the lottery. We cannot
  12     identify in advance who is going to win the lottery.
  13   Q. I said in my introductory remarks that if you take
  14     a comparison amongst 12 centres, given any particular
  15     performance table, one is bound to be best and the other
  16     is bound to be worst. That as a matter of logic must be
  17     right. How do statistics help in describing
  18     the difference so that one may be satisfied either that
  19     the apparent top or bottomness of one centre is chance
  20     or that it is more than chance, probably?
  21   A. This is a relatively new area of statistics, and
  22     Dr Spiegelhalter has been fundamental in doing research
  23     on this. But essentially we can say that if you rank
  24     the centres and one of them is well below what would
  25     have been predicted from the others, then it is unlikely

   1     to have happened by chance and we can put
   2     the probability on it being at the bottom, even
   3     though -- so you might observe something which is at
   4     the bottom, but you might get a confidence interval
   5     which is between say 8 and 12. So it could have been
   6     that in fact in reality it was only 8 out of 12. But
   7     sometimes you can get the confidence interval is only
   8     12, in which case we can be 95 per cent sure that if we
   9     had run this thing a large number of times it would have
  10     come out at the bottom 95 per cent of the time.
  11   Q. Because the gap or the difference is so great that it is
  12     likely to be repeated on that number of occasions?
  13   A. Correct, yes.
  14   Q. Professor Campbell, I have asked you a number of
  15     questions. Is there anything that you would wish to add
  16     by way of introductory remarks, familiar as you are with
  17     the data which is going to be introduced, so that we
  18     have a proper perspective of what is going to be
  19     presented?
  20   A. I suppose I would re-emphasise the remarks that you made
  21     earlier, that the statistics and the probability are
  22     just part of a jigsaw and that one of the most important
  23     things is that we have very few explanatory variables
  24     because of the way the data was collected; we do not
  25     have things such as the clinical condition of

   1     the babies. So we cannot provide any explanation as to
   2     why these -- the way that the data have evolved. Simply
   3     we can point to the fact that it is most unlikely to
   4     have arisen purely by chance. So I think it needs to be
   5     just part of a general picture.
   6   MR LANGSTAFF: What I am going to do now is to suggest to
   7     our chairman that we have a short break, perhaps 10 or
   8     15 minutes, and then Professor Evans will introduce
   9     the Bristol picture and the Bristol rates and present
  10     that to us.
  11   THE CHAIRMAN: Yes, Mr Langstaff. Just before we break for
  12     15 minutes, that introduction was extremely helpful
  13     I think in setting out the language, the terms of
  14     reference by reference to which we have to read
  15     the material before us. I hope it was helpful to
  16     everyone to hear what these various terms mean so that
  17     we can translate what we see. It was extremely helpful;
  18     thank you. Shall we now break and reconvene at 11.30.
  19   (11.15 am)
  20   (11.40 am)
  21   MR LANGSTAFF: Sir, Professor Evans, may he take the oath?
  22          PROFESSOR STEPHEN EVANS (SWORN):
  23            Examined by MR LANGSTAFF:
  24   Q. Professor Evans, your full names, please, and essential
  25     qualifications?

   1   A. I am Stephen James Weston Evans. I have a BSc and MSc.
   2     I am a chartered statistician. I was Professor of
   3     Medical Statistics at the London Hospital Medical
   4     College, part of London University. I was there for 25
   5     years, and then I was head of epidemiology for
   6     Medicine's Control Agency. I now work locally, not far
   7     from Tonbridge Wells, and I would describe myself as
   8     a statistical epidemiologist.
   9   Q. Did you, for the purposes of this Inquiry, prepare
  10     a report which we have, the first page presently on the
  11     screen, beginning at INQ 12/1?
  12   A. I did.
  13   Q. And does the text of the report finish at INQ 12/33?
  14   A. Yes.
  15   Q. Let us look at this a minute, the very bottom of the
  16     page. Then that is followed by a number of tables and
  17     figures and an annex. The report as a whole ends, does
  18     it, at page 49, INQ 12/49?
  19   A. Yes.
  20   Q. You are prepared to present your findings, are you, to
  21     the Inquiry, and would you perhaps like to do so?
  22   A. Yes. I am happy to do that. I would like to in some
  23     senses preface my remarks, well aware of the parents,
  24     those who are concerned about this Inquiry, concerned
  25     health professionals, and say to them -- I am sure I can

   1     speak on behalf of my colleagues -- we as statisticians
   2     are very aware of the personal trauma that many of you
   3     have gone through and when we talk about children and
   4     procedures and deaths and numbers, we do so in the
   5     knowledge that each one of those is someone who is
   6     important. When we talk about surgeons and centres and
   7     health professionals, we are aware that they are
   8     important.
   9        It may seem that sometimes our numbers are
  10     expressed in a way that is cold and uncaring. That to
  11     some degree is the lot of the statistician, that they
  12     will be seen in that way, but we would wish to say that
  13     we are aware of your hurts; we are aware of your current
  14     concerns, and we are doing our best to try and help this
  15     Inquiry in the terms of the purposes of the Inquiry, to
  16     come to answers that are as helpful as possible.
  17        So please do remember, when we use terms that may
  18     be distressing, I am sure that we would be happy to
  19     accept from the Panel or others, advice as to how
  20     perhaps we can ameliorate that distress, but we are
  21     conscious of it and we will do our best. But
  22     nevertheless, we are dealing in numbers and these things
  23     may appear hard. You said this yourself at the
  24     beginning, Mr Langstaff, but we wish to reiterate it.
  25        I think that we have to remember that when the

   1     Inquiry was set up, there were about 2,000 sets of
   2     medical records, and each of these consisted of perhaps
   3     one folder, perhaps a number of folders, that related to
   4     the children who had received cardiac surgery between
   5     1st January 1984 and 31st December 1995. It was clearly
   6     impossible to scrutinise all of these records -- they
   7     form a very, very large volume in great detail -- using
   8     teams of medical, surgical and nursing experts, but at
   9     the same time, it was very important to be able to take
  10     into account the records of every child who had received
  11     care under the terms of the Inquiry. This again is
  12     important to the parents. All of the children have been
  13     considered and we have analysed data that relates to all
  14     of them.
  15        The Panel decided to take a sample of these
  16     records and more details, as you have heard, will be
  17     given of this tomorrow. However, if we are to take
  18     a representative sample that reflects the concerns that
  19     led to the Inquiry, it is important to have summary
  20     information available on every child. This was done
  21     using a team of people who are used to summarising
  22     medical records.
  23        One has to remember that the language in which
  24     a medical record is written may vary from time to time
  25     with the same clinician, describing the same sort of

   1     conditions, and will vary between one clinician and
   2     another for the same conditions. They will write down
   3     and use words slightly differently.
   4        But when we come to try and summarise the data, we
   5     have to use a language that is common to all. It may be
   6     that this language is not the most appropriate one for
   7     ordinary conversation. The team of people who are doing
   8     the coding of the records in the hospitals use
   9     nationally and internationally agreed terms for these
  10     operations and diagnoses, and the groupings, as you have
  11     been shown, are labelled using a code number with
  12     a letter and this process is described as "coding". The
  13     people who carry out the task are called "coders". This
  14     process was described in evidence given in July.
  15        In generating a summary for each child, we entered
  16     this summary on to a computer and it is described as the
  17     "clinical coded record" database, the CCR.
  18        To check that these records did cover the relevant
  19     children and to compare the quality of the data recorded
  20     there, we have made comparison with two other sources
  21     and the first, as we have heard, is the Patient
  22     Administration System, known as PAS, a routine computer
  23     system used by the local Bristol Health Trust for
  24     administrative purposes.
  25        It is also the basis for preparing returns to be

   1     submitted to the Department of Health of England,
   2     notably for the production of hospital episode
   3     statistics, and more details of this will be provided by
   4     Dr Aylin.
   5        The third source of local data is the logs of the
   6     operations done at the Bristol Royal Infirmary by
   7     Mr Wisheart and Mr Dhasmana, and they have been
   8     described by them in evidence given to the Inquiry.
   9        These logs used words that were typed or
  10     handwritten and they have also been coded by a coder
  11     from the team who coded the clinical records.
  12        Each of the sources has some basic information on
  13     the children and if we look at my report, INQ 0012/18,
  14     a summary of the information that is in common across
  15     the sources is given at the top there. This has patient
  16     name, date of operation, BRI number, whether the patient
  17     died, the surgeon, the date of death, the diagnosis, the
  18     age (derived from the date of birth that we recorded for
  19     the CCR and the PAS) and OPCS codes for operative
  20     procedures.
  21        So there is other information in each of the
  22     sources, but we have concentrated on the information
  23     that is in common across the sources because we want to
  24     carry out comparisons.
  25        So we had three purposes of bringing together

   1     these sets of data, and I think my first overhead slide,
   2     which is number 50, described the purposes.
   3        If we can have that rotated and enlarged, the
   4     purposes of our looking at these sources of data was
   5     firstly, as we have said, to describe the overall care
   6     and to describe the children receiving that care in
   7     Bristol. That was an important purpose.
   8        The second one was to allow us to carefully select
   9     a sample to allow for detailed examination of the
  10     medical records in that sample, because we could not do
  11     it for all 2,000.
  12        If we are to do it for a sample, we have to select
  13     that in such a way that every child concerned has an
  14     equal chance, as every other similar child, of being
  15     included in the sample.
  16        The other thing that is important is that when we
  17     begin to make national comparisons, and Dr Aylin and
  18     Professor Murray will be making national comparisons, we
  19     need to be sure that the local data really reflect what
  20     actually is recorded nationally as far as we can. So we
  21     want to check that the Patient Administration System is
  22     a reasonable reflection of the care given and the
  23     outcome of the care.
  24        We also want to make sure that the surgeons' logs,
  25     which were the underlying source for the UK cardiac

   1     surgeons' register, should also have similar results as
   2     the medical records.
   3        If we look at the processes of care, I think it is
   4     probably at this point helpful to look at Annex 1 of my
   5     report on pages 47 and 48. We will look at page 47
   6     first of all.
   7        If we look here, we see that there can be
   8     a child -- and each child must have been admitted to
   9     hospital to be included in any of the sets of data.
  10     They have to be admitted to the hospital.
  11        A child may have a single admission. Within that
  12     admission, for all practical purposes, they must also
  13     have an operation. Within one operation, when they go
  14     to the operating theatre, they may have more than one
  15     operative procedure carried out by the surgeon.
  16        These operative procedures are what are coded
  17     using the Office of Population Census and Surveys coding
  18     system. They use labels. This is the language that is
  19     used to describe the operations that the children had.
  20        If you go to the next page, we see that some
  21     children, of course, did not only have one operation, or
  22     one admission. Within an operation, they have more than
  23     one procedure. During a single admission to hospital,
  24     they may actually have more than one operation. You
  25     have here an example with two operations, and in each of

   1     those two operations, if we scroll down a little
   2     further, we have two procedures.
   3        So the question is, what should we count? It is
   4     not going to be easy to count children in a way that is
   5     comparable nationally. In the hospital episode
   6     statistics, what they count is essentially an episode of
   7     care, and Dr Aylin will explain a little more about
   8     that. In terms of the cardiac surgeons register, they
   9     record operations. They do not identify individual
  10     children. So we have to make a decision as to how we
  11     are going to do our counting. It is very difficult to
  12     count only children. We could count admissions, except
  13     that, in the clinical coded notes, we do not have dates
  14     of admission and discharge. Nor do we have them in the
  15     surgeons' logs, but we do have operations, and so what
  16     we have done is, where we can count admissions, we count
  17     them; where we can only count operations, we count
  18     them. Hence, as Mr Langstaff was explaining, in
  19     a situation here, where we have two operations and in
  20     each of them we have two procedures, we do not want to
  21     count both those procedures, so we need to have a system
  22     whereby we decide which of these procedures we should
  23     count.
  24        So we can see a slightly more complex situation
  25     further down, where there are two admissions and, if we

   1     scroll down, each of those can have two operations and
   2     two procedures.
   3        If we look at the language that has been used for
   4     doing the coding of these operations, as Mr Langstaff
   5     said, K codes are for the heart and the L codes are for
   6     arteries and veins, what he described as "vascular"
   7     operations. For example, I have not got an immediate
   8     example for you, but KO 1 stands for transplantation of
   9     heart and lung. Then there are a series of individual
  10     codes under that that go KO 1.1, which is
  11     allotransplantation of heart and lung; KO 1.2 is
  12     revision of transplantation of heart and lung; KO 1.8 is
  13     "other specified"; KO 1.9 is unspecified.
  14        We have these detailed codes. The language that
  15     is then used for that is not necessarily exactly the
  16     same language that a surgeon will write down. They do
  17     not write these codes down. They use their medical
  18     terminology, and somebody has to translate that medical
  19     terminology into these codes.
  20        For example, if we look at KO 4, that is the
  21     overall code for correction of tetralogy of Fallot. But
  22     KO 4.1 is correction of tetralogy of Fallot, using valve
  23     right ventricle outflow conduit, so there is a level of
  24     detail there.
  25        We will come to some of these groups of operations

   1     where we have to use the greatest detail, and some where
   2     we can use a broader category.
   3        The consequence is, in doing this translation
   4     between whatever is written, on the surgeons' logs or in
   5     the medical notes, or perhaps in a discharge letter that
   6     is coded by the Patient Administration System, there
   7     will be inevitable differences in the way the
   8     translation happens. If I was speaking in French and
   9     somebody were carrying out simultaneous translation, you
  10     would realise that my use of French could be translated
  11     in more than one way in English and in some instances in
  12     French we have "tu" and "vous", both of which in English
  13     are "you", but they have subtly different meanings in
  14     French. We do not have any longer in English "thee" and
  15     "thou" that would reflect the "tu" of French. So we
  16     may find that there are things written in the record
  17     that are incapable of being translated.
  18        Having gone on at considerable length about that,
  19     we need to see that the Cardiac Surgeons' Register does
  20     not have those kind of operation codes. If we look at
  21     table 2.1 in Dr Aylin's report of his report INQ 13,
  22     page 54, which we have already seen, and there is
  23     a similar table 6 of Professor Murray's report, we will
  24     see these operation codes. I hope this has perhaps made
  25     it a little clearer. So group one is KO 4, tetralogy of

   1     Fallot, and that means KO 4.1, point 2, point 3 and so
   2     on, and point 8 and point 9, and that is a broad
   3     grouping. If we look down to group 8 for truncus, that
   4     is specifically LO 1.1. So that if something was coded
   5     LO 1.8, which is an unspecified operation, it will not
   6     then get counted.
   7        So you can see the subtle differences here.
   8        This makes it amazing that there can be any
   9     comparability between the records. I expected, when
  10     I looked at these data, to find that when I started
  11     looking at the numbers, I would not get much agreement.
  12        There are also a larger group of procedures, as
  13     Mr Langstaff said, classified by whether they were open
  14     or closed.
  15        Again, if we look at INQ 13/82, again from
  16     Dr Aylin's report, here we see a list of procedures
  17     beginning at KO 2.1 which was an open procedure, and
  18     K 15.1 and K 15.2 that were closed procedures, and then
  19     on the right-hand side is K 16.1 and point 2 and so on
  20     all the way to point 8 which are excluded. It does not
  21     mean the children were not counted, we have looked at
  22     those, but in terms of classifying whether an operation
  23     was open or closed, we were unable to decide on the
  24     advice of the clinicians whether it was unequivocally
  25     open or closed. It could be either.

   1        So, if we classed it as open we may make
   2     a mistake, if we class it as closed we may make
   3     a mistake. If we leave it out, we are reasonably sure
   4     we are comparing similar things.
   5        That explains, when we then move on to my next
   6     slide, essentially, which comes from my report OO12/43,
   7     in the top half of that page, we will see a figure and
   8     this shows us something of the data that we have.
   9        We see here a diagram that shows to us that in the
  10     Patient Administration System, which only ran from
  11     1st January 1988 -- it does not cover the whole period
  12     of the Inquiry -- we have nearly 2,000 children who were
  13     identified as being admitted under the care of
  14     cardiologists or cardiac surgeons, or paediatric
  15     cardiologists, or paediatric cardiac surgeons, and we
  16     have 2,000 children.
  17        We see there that they have nearly 4,000
  18     admissions. You can see that the number of operations
  19     and the number of admissions is rather similar; this
  20     number here is similar to this number here. So that
  21     when we decide to count operations or admissions, we are
  22     not making a big error. The number of operations per
  23     admission is close to 1 in the children we have.
  24        But in each operation, there are perhaps 1.5 or
  25     a little more procedures: nearly 6,000 procedures

   1     received by those 2,000 children. Of course some
   2     children received only one procedure and some received
   3     a very large number indeed. There is enormous
   4     variability in that number.
   5        We when come to group these, if we group them by
   6     open and closed, it turns out that a lot of the
   7     admissions cannot be grouped by either open or closed in
   8     an unequivocal way.
   9        Most of them are open. There are a smaller number
  10     that are closed. If we look at the procedures, we can
  11     classify those by, for example, in the black here, these
  12     are non-cardiac procedures, so that a child who is
  13     admitted for cardiac surgery may have a procedure that
  14     is not cardiac.
  15        We also have a large number of procedures that are
  16     not grouped, which are nevertheless cardiac, and, for
  17     example, cardiac catheterisation, or contrast radiology
  18     of the heart, were not grouped, but yet those are
  19     recorded in the records and recorded in the Patient
  20     Administration System, and many of them will have had
  21     those, but they are not sufficiently serious procedures,
  22     and will nearly always be accompanied by other
  23     procedures, and then this rather smaller number, which
  24     makes it look as though we are only looking at a few,
  25     but we are looking at the principal procedures that

   1     children who had heart surgery had. This is the pattern
   2     we see for the Patient Administration System.
   3        If we now move on down to the next page, page 44,
   4     to the top half of that, we see the same pattern for the
   5     clinically coded records. Here we cannot have
   6     admissions, we can only have operations. We see down
   7     here in procedures we have quite a reasonably large
   8     number that are non-cardiac, a considerable number that
   9     are not grouped and then still a large number that are
  10     grouped.
  11        If we move on down to the bottom of that page, we
  12     will see the same thing for the surgeons' logs, on
  13     a slightly different scale. We have got rather smaller
  14     numbers; we are talking about only something like 1,300
  15     children, with slightly more operations, but we now see
  16     that among these the classification is that the vast
  17     majority are open operations, and so they should be,
  18     because to go to the BRI meant that you were going there
  19     to have open-heart surgery; you did not need to go to
  20     the BRI if you were only having closed surgery.
  21        Here we see the procedures, the distribution of
  22     them is rather different; we have a very small number of
  23     non-cardiac procedures that are recorded. We have
  24     relatively few not grouped because the catheterisation
  25     and the contrast radiology of the heart would not have

   1     been done there generally, and most of our procedures
   2     are grouped.
   3        So we end up comparing them and on the surface of
   4     it, it looks as though they are very different.
   5        The other thing we need to be aware of, and if we
   6     can go back a little to the previous page, page 43, to
   7     the bottom half, we need to think about how we have
   8     classified whether a child was alive or dead. Many of
   9     the children will have died relatively quickly after an
  10     operation, and this curve here shows us that immediately
  11     after the operation, there is a certain mortality. This
  12     shows us that all the children are alive here, but by
  13     this point (indicating) 95 per cent; 5 per cent have
  14     died quite rapidly.
  15        Then the deaths go on occurring during the first
  16     30 days. They do not stop occurring at the end of 30
  17     days; they go on happening, and you can see that the
  18     curve continues there. But we, in most of the sources
  19     of data, do not have long-term follow-up of the
  20     children. We have that in the medical notes, we have it
  21     to a degree in the Patient Administration System, and we
  22     have it in Bristol rather better than we have it
  23     elsewhere.
  24        But we have chosen to make sure that we can make
  25     comparisons between children in one centre and another.

   1     We have chosen the 30-day. This is something that
   2     surgeons do not only for children but also in other
   3     operative areas, not only in paediatric cardiac surgery
   4     but elsewhere. But we need to be aware that sometimes
   5     we will be talking about children alive, meaning they
   6     had survived for 30 days. Sadly, they may have died
   7     a short time after that or in some instances they may
   8     have survived until 15 and have died at that point.
   9        So when we talk about that, we need to be aware
  10     that we have perhaps left some things out.
  11        Remember the Patient Administration System covers
  12     1st January 1988 to the end of 1995, but the coded
  13     records and the surgeons' logs cover the whole period.
  14     As Mr Langstaff said, we divided time into epochs and if
  15     we look at page 45, we see only open operations.
  16        If we go to page 39, which is table 5.1, if we go
  17     to the top, we see here this is from the surgeons'
  18     logs. We have age at which the operation took place,
  19     grouped into 0 to 90 days and so on, and 1 to 15 years
  20     and we see that the death rate is really a great deal
  21     higher, very sick children are operated on between 0 and
  22     90 days, so their death rate is much higher than older
  23     ages.
  24        So when we make our comparisons, it is important
  25     not only to make comparisons that are for similar

   1     operations; they have to be for similar ages, because
   2     the death rate is varying.
   3        If we move further down to table 5.1 -- and I am
   4     coming shortly to an end, Mr Langstaff -- we see here
   5     comparisons for the three major data sources, the
   6     Patient Administration System, the clinical coded
   7     records, and the surgeons' logs.
   8        We find here that although the period of time is
   9     really rather different, for tetralogy of Fallot we have
  10     as it happens exactly the same death rate, even though
  11     the numbers differ somewhat. The Patient Administration
  12     System we would expect to be less in that it covers
  13     a shorter period of time.
  14        We look at the intra-atrial transposition
  15     operations. We have 10 per cent, 5 per cent and 1 per
  16     cent. There is a bit of a difference there, and we may
  17     need to examine that. You may recall that there is some
  18     difficulty in distinguishing between those and the
  19     arterial switches that people do not necessarily code
  20     them correctly and we see here also differences, 38 per
  21     cent, 30 and 41 per cent. If we were to average those,
  22     it turns out that we would have rather better
  23     comparability of the data.
  24        The other problem is that these are not making
  25     a comparison for the same epochs. If we can go to my

   1     second overhead, which is my last one for the moment,
   2     which is, I think, page 51, if we can rotate that, we
   3     have here a similar table where we have the 11 groups
   4     only. We are just looking at the open operations
   5     because the surgeons' logs do not cover the closed ones,
   6     and we look at the Patient Administration System, the
   7     clinical coded records and the surgeons' logs, we find
   8     that the death rates are relatively similar, except in
   9     groups 2 and 3 and we find considerable agreement and
  10     down the bottom here, in terms of the totality, we have
  11     similar numbers of deaths and similar numbers of
  12     operations.
  13        The general conclusion from this is that we cannot
  14     use any of these sources of data to decide exactly what
  15     happened to individual children. It would be dangerous
  16     to go to one of those sources and say, "That gives us
  17     the truth about that".
  18        The medical records should give us a full idea,
  19     but do not forget, we have had to translate from a pile
  20     that may be one foot high into one or two sheets of
  21     information using our translation process to get the
  22     codes. That process is inevitably subject to error.
  23        When we look at it, the comparability of these
  24     different sources -- I think we can probably finish with
  25     the overheads now -- is really remarkably good. We will

   1     see that later on. If we return to our purposes and we
   2     perhaps -- I am sorry, we could perhaps go to my
   3     conclusions which are on page 32, I can read out
   4     a little bit from paragraph 6.3 there in the middle:
   5        "The exercise of coding the medical records was
   6     a considerable task, and although the individual coding
   7     has been of high quality, there have been many minor
   8     problems with the data.
   9        "The Patient Administration System does seem to
  10     provide an adequate method for an overview of the amount
  11     of care and the mortality."
  12        It is very difficult to cross-check these. One of
  13     the things that came across to me was the number of
  14     changes of names of children. The family tragedies that
  15     are involved in that are really very considerable, and
  16     I think that one has to be aware of that. We are
  17     talking about children and families here that are very
  18     affected, but nevertheless, when we look at the whole
  19     thing, the coding and entry and so on has not been
  20     perfect.
  21        From a clinical perspective, as I have written at
  22     the bottom of the page there, each child is unique and
  23     not simply to be pigeon-holed, but we have to make
  24     comparisons, either over time or between surgeons in
  25     a unit, or between units, and if we are to do that, we

   1     have to put things into categories. We cannot make
   2     progress without it and there will be imperfection. The
   3     great majority of the children who received care did not
   4     die, but there is also very strong evidence, to me, that
   5     these different sources of data suggest that none of
   6     them is perfect and none of them has a major problem in
   7     the way that it has described the deaths in the care.
   8     I am sorry to go on rather.
   9   THE CHAIRMAN: Thank you very much, Professor Evans.
  10   MR LANGSTAFF: Professor Evans, to what extent do the
  11     figures produced from one data source, in your view,
  12     support and give strength to the figures from another
  13     data source?
  14   A. I think the first thing to remember is that if they did
  15     not, then the exercise of national comparison would be
  16     a waste of time. So it is a necessary condition, but
  17     not a sufficient condition that the comparison is valid.
  18        They do complement one another. In looking at the
  19     details those numbers have errors in them. There are
  20     errors when people have typed them into the computers.
  21     There are errors in programming, doing the grouping,
  22     that sort of thing, and we still have to try and get
  23     that better. They are not perfect, even though they
  24     have been put in that report. But as I have looked at
  25     it more and more, the more detail I have, the more they

   1     agree with one another and that is encouraging. If they
   2     did not, we would be wasting our time doing an analysis
   3     of the data, but it has not said that we should believe
   4     the numbers perfectly.
   5   Q. An alternative way of looking at it might be that the
   6     data that we had simply was not good enough and had not
   7     been collected in a way that was good enough to enable
   8     any valid comparison to be made?
   9   A. I certainly approached the data with that as
  10     a possibility, but I do not hold that view any longer.
  11     I am amazed at how consistent they are and this will
  12     come in Professor Murray's and Dr Spiegelhalter's view
  13     of these things. The consistency is very much greater
  14     than I would have expected.
  15   Q. Can I ask you about specific tables? If we go to
  16      INQ 12/35, table 4.3, what we are looking at there is
  17     from the PAS system so it only covers 3 epochs, because
  18     the Patient Administration System as you point out gives
  19     us data only from January 1988 onwards.
  20        If one compares the death rate from 1988 to 1995,
  21     13 per cent and 11 per cent, with the death rate from
  22     April 1995 to December 1995, 2 per cent, there is a very
  23     obvious drop. First of all, is that a drop in rate
  24     which is consistent across the data sources?
  25   A. Yes.

   1   Q. Secondly, in looking at the material before you, did you
   2     notice any difference in the mix or nature of the
   3     operations being performed during that last period
   4     compared to the two earlier epochs?
   5   A. Yes. There were certainly very many fewer operations
   6     overall. There are obviously only 132 in total in the
   7     PAS for that period. We are only talking about a short
   8     period. The earlier epochs cover several years and this
   9     only covers part of the year, so the overall numbers are
  10     smaller, and some of the high risk operations almost
  11     disappeared in 1995; they were not there. So we are not
  12     comparing like with like across those epochs, the last
  13     epochs.
  14   Q. Does it follow that it would not be a safe conclusion to
  15     say, "April 1995 the surgeon was changed, and look what
  16     a difference it made to the death rate"?
  17   A. I think that one ought to examine the question of
  18     whether that is so, but I think that those figures on
  19     their own should certainly not be used to draw that
  20     conclusion.
  21   Q. If you would turn, please, to INQ 12/41, this is
  22     a comparative table which you have derived from the
  23     surgeons' logs which compares the rate attributable to
  24     operations which were conducted by Mr Dhasmana and
  25     Mr Wisheart.

   1        The first question needs to be asked: is there any
   2     statistical basis for ascribing any particular success
   3     in the sense of survival, or failure if in the sense of
   4     death, to the surgeon as opposed to the whole process
   5     involving the whole of the surgical team?
   6   A. I do not think that I have data to answer that
   7     question. If we look at the overall rates, they are
   8     similar for the two. There are individual operations
   9     where there is a difference, for example, with truncus
  10     arteriosus, just over halfway down the table, but these
  11     are based on very small numbers.
  12        The consequence is that you cannot be certain of
  13     the differences. They are compatible with differences,
  14     but overall, there is no evidence for a systematically
  15     higher rate with one surgeon than another.
  16        That would be compatible with some system failure,
  17     if Bristol were shown to be different to other centres,
  18     but it does not mean it is system failure and you cannot
  19     use these data alone to draw that conclusion.
  20   Q. Can I take you to INQ 12/38? The last table we looked
  21     at, as indeed this table, comes as the "SL" suggests
  22     from the surgeons' logs. Am I right in thinking from
  23     your earlier description that these descriptions are not
  24     lifted straight, as it were, from the wording in the
  25     surgeons' logs, but go through a process whereby the

   1     information in the logs has been coded and the same
   2     coding process applied to that as to other data?
   3   A. Yes.
   4   Q. So the surgeon himself may -- and may with force -- say
   5     "That is not how I would have described this particular
   6     operation"?
   7   A. Yes. I think that that is so. What we have here in
   8     this table, of course, though, is totals, and perhaps
   9     the interesting thing is that during the first three
  10     epochs there is no evidence of any particular trend, and
  11     while in the fourth epoch it appears to be much lower,
  12     we are based on very small numbers and there is some
  13     suggestion that the type of operations changed in that
  14     period.
  15   Q. You are talking of table 4.10 there, I think?
  16   A. I am sorry, yes.
  17   Q. Can we scroll down so we see what you are looking at
  18     there?
  19   A. I am saying that in those three periods, the 12, the
  20     15 per cent and the 13 per cent, they are from
  21     a statistical point of view rather similar.
  22   Q. Can I ask you to go back up the top of the page, which
  23     deals with individual operations? What I was asking
  24     you, and I think you were accepting, is that the
  25     description which an individual surgeon might give to

   1     whether a particular operation should be classed as one
   2     or other of these groups, that may very well be said by
   3     a surgeon, might it, with force, because the nature of
   4     your data is to put it through a coding process where
   5     coders look at the data and make of it as best they can
   6     from their particular perspective?
   7   A. Yes. I think that one of the things is that in the
   8     surgeons' logs there we see a very different death rate
   9     for inter-atrial transposition of the great arteries,
  10     the second line of that table, from that for other
  11     transposition which is the arterial switches.
  12        To me, that demonstrates that the coding of the
  13     switches within the surgeons' logs was very much better
  14     than it was in, for example, the Cardiac Surgeons'
  15     Register, where the difference between the second and
  16     the third group, there was some confusion between them.
  17        My view is that this is reasonably reliable. It
  18     has not been done for the surgeons' logs, but for the
  19     clinically coded records, we actually carried out
  20     a re-sample and a re-look at the data, and found
  21     considerable consistency.
  22        So while a surgeon may say, for any one case this
  23     is not reliable, the overall pattern, I think, would
  24     have to be said to be reliable.
  25   THE CHAIRMAN: Mr Langstaff, I for one did not quite

   1     understand that last answer. I wonder whether Professor
   2     Evans could go through it again? I am looking at "that
   3     demonstrates that the coding of the switches within the
   4     surgeons' logs was very much better than it was, even
   5     for example if the Cardiac Surgeons' Register, where the
   6     difference between the second and the third group, there
   7     was some confusion between them."
   8        That is what you said.
   9        That induces in me a degree of confusion also.
  10   A. Yes, I am sorry, because I have read the report on the
  11     Cardiac Surgeons' Register that has not yet been given
  12     in evidence, and I think it will become clearer when
  13     that does, but what was said by Mr Langstaff in his
  14     opening remarks was that the coding of the switches
  15     between the Mustard and Senning and the arterial
  16     switches, sometimes got confused. The consequence of
  17     a confusion of that kind would lead to the death rate in
  18     each of the groups ending up looking similar. Whereas
  19     in fact, the death rate in the inter-atrial
  20     transposition is very low, and the death rate in the
  21     arterial switches is rather high, and that is shown by
  22     the coding of the surgeons' logs, implying that that has
  23     been done relatively reliably, rather than muddling
  24     between the two.
  25   THE CHAIRMAN: That is very helpful, I am grateful.

   1   MR LANGSTAFF: You say in fact, it is as we see in the
   2     surgeons' log. How can you say that when all you have
   3     to go on is figures?
   4   A. I think that the point is that if the death rates in the
   5     two had both been 8 per cent, which you might see if
   6     there was a lot of error, if you are randomly putting
   7     down one of those codes and assigning deaths to it, we
   8     would then see that the difference in the risk of those
   9     two different operations would be blurred and they would
  10     move together.
  11        Just from the figures, I can see a big separation
  12     in those, and in those it looks that the coding of those
  13     particular operations was done reasonably in the
  14     surgeons' logs and the surgeons' logs, in their words,
  15     also, were clear. Your problem of translation can be
  16     caused by failure to describe clearly, but it looks as
  17     though the combination of the translation, the coding
  18     and the original statement in the surgeons' logs, was
  19     sufficiently clear for distinctions to be made between
  20     them.
  21   Q. You, from your perspective, are reporting upon death
  22     rates here at Bristol shown by the process that you have
  23     gone through by a comparison of three different sets of
  24     data.
  25        Am I right in thinking that you, in your report,

   1     do not make any comparison with national rates and so we
   2     have no way of knowing from your data alone how these
   3     particular rates may compare or do compare with
   4     elsewhere?
   5   A. No, you are absolutely correct: no national comparison
   6     was made.
   7   Q. The next area which I want to explore with you is
   8     whether you, as a statistician, had any input into the
   9     90 day cut-off, the grouping of the age from 0 to 90
  10     days, and then from 91 to 365?
  11   A. I had a little input into it, in that, within our data,
  12     we could group it by individual day for each of these
  13     sources, because we had exact dates of death and we had
  14     exact dates of operation. So we could look at that.
  15        Certainly my looking at the data was that in the
  16     first month, the first 30 days, which is traditionally
  17     regarded by many as being the highest risk time, this
  18     was not substantially different from the risks in the
  19     first 90 days, in the data that I looked at.
  20        So it seemed more sensible to compare that.
  21        Outside paediatric cardiac surgery, death rates
  22     fall very dramatically after the first week of life. So
  23     there is a tendency to want to group things in the first
  24     week, or at least the first month of life and not the
  25     rest. In paediatric cardiac surgery, in looking at the

   1     data -- and I think perhaps others may be able to
   2     comment on that -- there is a pattern that suggests that
   3     the death rate in operations that are during the first
   4     90 days are relatively similar to one another, rather
   5     than just in the first 30 days.
   6   Q. I do not know whether there is a comment from my right,
   7     and our panel of experts, as to the degree of
   8     justification there is for having a 0 to 90 degree
   9     category, which plainly on the figures that you produce,
  10     shows a much higher death rate, and therefore, perhaps,
  11     may have a tendency to mislead by skewing, given what
  12     you say about early deaths being inevitably more likely
  13     than later ones.
  14        Do we have a comment that any of you would wish to
  15     make?
  16   THE CHAIRMAN: I think the way you ended that sentence
  17     slightly itself skewed our understanding, Mr Langstaff,
  18     with respect. Professor Evans, would you comment on the
  19     question?
  20   A. Can I just comment that the alternatives were to group
  21     0 to 30 days and 30 days to 1 year. Had we done that,
  22     we would have found a rate in the 0 to 30 days that was
  23     high, and perhaps slightly higher than the 0 to 90 days,
  24     but only slightly higher. If we had the 30 days to
  25     1 year, that would muddle a group who had a high rate

   1     from 31 days to 90 with a group that had a notably lower
   2     rate from 91 days to the end of the year.
   3        So grouping it in the way that says "I will only
   4     put 30" ends up muddling things and not exaggerating the
   5     effect. We have not, by having the group at 90 days,
   6     exaggerated any effect.
   7   MR LANGSTAFF: I see nods from my right so that is
   8     a comment, I think, in itself.
   9        Professor Evans, thank you very much indeed for
  10     your presentation. Sir, I am in your hands. I think it
  11     may be convenient to proceed with Dr Aylin's
  12     presentation following on from that, as it does quite
  13     naturally, and review where we are at, say, 1 o'clock to
  14     a quarter past 1?
  15   THE CHAIRMAN: Yes.
  16   MR LANGSTAFF: I do not know if you are happy to change
  17     places, so Dr Aylin is nearer the screen, if he wishes
  18     to use it?
  19        Dr Aylin, can you remain standing so you can take
  20     the oath?
  21             DR PAUL AYLIN (SWORN):
  22            Examined by MR LANGSTAFF:
  23   Q. Dr Aylin, you have given evidence to us before. Have
  24     you, for the purposes of this part of the Inquiry's
  25     proceedings, prepared a report which we find at

   1     INQ 13/1?
   2   A. Yes, I have.
   3   Q. Does it conclude with a number of tables and figures
   4     which begin at 13/53 --
   5   A. Yes, that is correct.
   6   Q. -- as the screen now shows us, and ends with
   7     a statistical appendix setting out the details of the
   8     statistical methodology you used, ending at page 86?
   9   A. Yes, it does.
  10   Q. You, I think, have prepared a presentation for us of
  11     your investigations. Would you like to give us the
  12     benefits of that, please?
  13   A. Yes. I would like to talk about our analysis of
  14     Hospital Episode Statistics, which was commissioned by
  15     the Inquiry. The report that we presented is in five
  16     sessions, essentially. First of all we looked at the
  17     quality of hospital activity data available to us. Then
  18     we looked at outcomes of surgery in terms of mortality
  19     and one or two other outcomes that we looked at,
  20     comparing the United Bristol Healthcare NHS Trust with
  21     the rest of England.
  22        We also looked at comparisons of UBHT with
  23     individual centres in England as well.
  24        We were asked also to look at activity rates and
  25     referrals, and patterns of these, and also we attempted

   1     to examine co-morbidity or co-existing disease and case
   2     mix in Bristol, and comparing it with the rest of
   3     England.
   4        I will just briefly go over the review of hospital
   5     activity data. There are two main bodies of data that
   6     we could have looked at. The first was HIPE, the
   7     Hospital Inpatient Enquiry, which ran from 1985 up until
   8     1986. This was only based on a 10 per cent sample, and
   9     we felt that the numbers involved in the very small part
  10     of the time period that was covered by the Inquiry was
  11     not suitable for analysis.
  12        The next major set of data was the Hospital
  13     Episode Statistics, which was brought in in 1987, and it
  14     is running to this day.
  15        During its introduction in 1987 and for the
  16     following few years, the literature that we reviewed on
  17     this suggested that the data quality was very poor.
  18        The other problem with the data quality was that
  19     the surgical codes that we were interested in, OPCS 4
  20     codes, were not fully established nationally until 1991.
  21        So we felt that because of this patchy
  22     implementation of the coding for operations and
  23     procedures and because of the poor quality of data
  24     before 1991, that the HES data before 1991 was not
  25     suitable to inform the Inquiry. So this analysis

   1     concentrates on Hospital Episode Statistics, beginning
   2     from the financial year 1991 to 1992, and going up to
   3     December 1995.
   4        I am just going to tell you a little bit about the
   5     methods we used for pulling this data off the national
   6     data system.
   7        We extracted all episodes between the period of
   8     1st April 1991 to 31st December 1995 for all children
   9     aged under 16, with a mention of a K or an L code.
  10     I can illustrate the process of this, if we go to
  11      INQ 13/96, I can show you some of the figures involved
  12     in this selection process.
  13        Can we just move down the page a little bit?
  14        If we look at the top, the first extract was based
  15     on years and as I say, we picked out all episodes in
  16     children aged under 16 which had a mention of a K and L
  17     procedure, and we also looked at all other episodes that
  18     belonged to children which we had pulled out beforehand.
  19        I ought to explain about the Hospital Episode
  20     Statistics, that they are based on episodes of care, and
  21     an episode of care is a continuous spell -- a continuous
  22     episode of care spent under a consultant.
  23        It may be possible that you have one or more
  24     episodes of care within an admission.
  25        Can I just show you slide 97? This just

   1     illustrates how we managed to bring episodes together.
   2        Can we scan down a little bit? This is just
   3     a little diagram that may help to explain about episodes
   4     of care.
   5        One of the problems with Hospital Episode
   6     Statistics is that we do not have a patient identifier
   7     on the data that we had obtained, so we were not able to
   8     identify, through an identifying code, individual
   9     children.
  10        What we had to use instead was to use date of
  11     birth, sex and postcode, to try and link episodes of
  12     care to children, and link them together. We also had
  13     the date of admission, and we were therefore able to
  14     link episodes of care into admissions.
  15        This is a hypothetical example of one admission
  16     with three episodes of care, and there may have been an
  17     operation in the first episode, and a subsequent
  18     episode 2 and episode 3. That series of episodes, which
  19     we will call an "admission", ended in either a discharge
  20     home, a transfer to another hospital, or, in some cases,
  21     a death. Our linkage system was not perfect because we
  22     used date of birth, sex and postcode. During the course
  23     of an admission there may be a postcode change or there
  24     may be an error in data entry of a date of birth or sex
  25     or postcode which would make us unable to be able to

   1     link episodes together to form an admission.
   2        In certain admissions, we were unable to find the
   3     final episode and therefore we were unable to ascertain
   4     whether a patient went home or was transferred or died
   5     and in that case, the outcome of the admission was
   6     unknown.
   7        I just want to go back to that page 96 now,
   8     please, and take you through this a little bit further.
   9        For this first extract, we pulled out all episodes
  10     of care which were linked to episodes which had a K or
  11     an L procedure in children aged under 16, for the
  12     financial years 1991/92 to 1995/96.
  13        For most of the tables and the analyses that we
  14     are going to present, they relate to epoch 3, which is
  15     1st April 1991 to 31st March 1995 and so this
  16     subselection here refers to this particular period in
  17     time.
  18        We identify 216,000 episodes out of those 289,000
  19     episodes.
  20        At this point, we started to link the episodes
  21     together, to form admissions. We identified 41,000
  22     admissions, with a mention of a K or an L procedure.
  23        There were many other episodes that may have been
  24     related to the same child but did not have a mention of
  25     a K and L procedure, so we may have an admission in the

   1     early part of the period of a child who had a procedure
   2     with a K or an L code mentioned.
   3        Subsequently there may have been an admission for
   4     asthma or another surgical procedure later on in this
   5     period which we were not interested in, so we discarded
   6     those, so we kept all admissions with a mention of K or
   7     L procedures and that came to 41,000.
   8        We were then able to divide these up into
   9     admissions to UBHT, Bristol, and those admissions to the
  10     rest of the English admissions.
  11        Then, at this lowest point, we used the procedure
  12     groupings which we have talked about a little bit
  13     earlier, and the broad classes of procedures, the open
  14     and closed classes of procedures, to extract these more
  15     relevant procedures from the overall numbers of
  16     admissions with K and L codes.
  17        So these admissions that were discarded had
  18     mentions of K and L codes that were not included in our
  19     13 key procedure groups, or in our open and closed
  20     operations.
  21        I must say, I just want to make a point of
  22     clarification on the way in which the procedure
  23     groupings were actually used. On the HES database,
  24     there are four fields for operation codes and these use
  25     the OPCS 4 operation coding systems. There may be just

   1     one procedure mentioned or there may be two, three or
   2     four procedures mentioned. If we are looking at an
   3     admission with a number of episodes, there may be
   4     a number of procedures in each of the episodes.
   5        The grouping systems were devised by our team and
   6     the other teams that are talking today, in order to make
   7     sense of these OPCS 4 coding systems.
   8        So the 13 procedure groupings and the broad class
   9     of "open" and "closed" were not known to the coders when
  10     coding the data; they just put the individual OPCS 4
  11     code in there. It was us that used the groupings in
  12     order to be able to have broadly clinical similar groups
  13     of operations so that we could make comparisons.
  14        The ranking system was devised by us in
  15     collaboration with the surgical experts, to enable us to
  16     pick a primary procedure out of a number of procedures,
  17     so the most important procedure out of a number of
  18     procedures in a particular admission.
  19        So these were developed by us for the analysis,
  20     and are not known to the coders in the hospitals who
  21     code these things up.
  22        Once we had our extract of data, we analysed the
  23     data in a number of different ways. If we could go to
  24     slide 100. I am going to present to you, if we could
  25     move up a little bit, four or three main kinds of

   1     analysis, and I am going to talk a little bit about
   2     confidence intervals again, although we had a very good
   3     explanation earlier this morning.
   4        We looked at mortality rates for individual
   5     operations in individual age groups for our procedure
   6     groups of operations. We looked at the proportion of
   7     admissions which ended in a death as far as we could
   8     tell.
   9        You remember I talked to you about linking
  10     episodes together and in a few percentages of episodes,
  11     we were unable to find out what actually happened at the
  12     end of the admission. We were unable to find out
  13     whether they were discharged home or transferred or
  14     died.
  15        In calculating our mortality rates, we have
  16     excluded those unknown outcomes in our analysis, so we
  17     simply, in calculating mortality rates or the proportion
  18     of admissions that ended in death, looked at those
  19     admissions where we have known the outcome.
  20        We have calculated these rates both for UBHT and
  21     for the rest of England as a whole, and I will present
  22     those in a minute.
  23        We also looked at the ratio between mortality at
  24     UBHT and the rest of England. For instance, if we had
  25     10 deaths out of 100 admissions in the UBHT, and, say,

   1     50 deaths out of 1,000 deaths in the rest of England,
   2     the ratio of the mortality rates between the UBHT and
   3     the rest of England would be 2, that is, 10 per cent
   4     mortality in UBHT and 5 per cent in the rest of
   5     England. So we gave the ratio of that and expressed
   6     that as a mortality ratio.
   7        We also calculated excess deaths according to the
   8     Bayesian principles that have been described before, and
   9     if we could go to slide 102, we looked at the difference
  10     in performance or in mortality between UBHT and
  11     a typical centre, quantified by predicting the numbers
  12     of deaths expected if UBHT had the typical mortality
  13     rate, or the mortality rate of a typical centre, and
  14     compared this to the observed numbers of deaths, so we
  15     worked out the numbers of deaths we would expect if UBHT
  16     had the mortality rate of a typical centre in the rest
  17     of England, and then we had the actual observed numbers
  18     of deaths and worked out this difference. This we
  19     expressed as the excess deaths.
  20        This estimate takes into account the variation in
  21     mortality rates between the other 11 centres.
  22        So this is perhaps a slightly more sophisticated
  23     analysis. This is a Bayesian figure that we come out
  24     with, whereas the mortality rates and mortality ratios
  25     are Frequentist calculations.

   1        Also for the mortality rates and for the excess
   2     deaths we gave a confidence interval, a 95 per cent
   3     confidence interval, which reflected our uncertainty of
   4     the true mortality rate. When comparing a mortality
   5     rate between Bristol and the rest of England, if the
   6     95 per cent confidence intervals did not overlap, we
   7     could be fairly confident that the difference in
   8     mortality was not due to chance.
   9        Now I would like to start presenting some of the
  10     results. If we could go to the graph on page 73,
  11      INQ 13/73. If we could rotate that around, it is
  12     a shame that the copy has not come out too well, but
  13     I think we can still see the main results here.
  14        Along the bottom of the graph, you can see the
  15     various procedure groups and there are the 13 procedure
  16     groups, and these are open and the 12 and 13 are closed
  17     procedure groups.
  18        In the remaining two bars we have the broad
  19     classes of open and closed procedures. The open
  20     procedures include many of these open procedures
  21     mentioned in the groups 1 to 11, and the closed
  22     procedures also overlap on to groups 12 and 13, so they
  23     are not exclusive by any means, those two different
  24     kinds of classifications.
  25        The bars that you see here and here and here

   1     (indicating) represent the mortality rate, the mortality
   2     experienced by the rest of England, excluding UBHT. You
   3     can see the mortality percentages up on the left-hand
   4     corner.
   5        So, for instance, if we look at group 3, other
   6     transposition of the great arteries, you can see that
   7     the national mortality is round about 10 per cent.
   8        The little diamonds which you will see here
   9     represent the mortality in UBHT for this particular
  10     period of time, and this graph refers to children aged
  11     under 90 days.
  12        The figure next to the little dot represents the
  13     number of valid cases, i.e. the cases where we knew the
  14     outcome, so that gives you an idea of the kind of
  15     numbers that we are dealing with.
  16        For the sake of clarity, we have not put
  17     confidence intervals on this graph for the national
  18     rates, but I will show you a table next which includes
  19     those confidence intervals.
  20        Let us take a look at this graph. As we go down
  21     the groups here, we can see that there were no
  22     admissions with a mention of a Fallot, a tetralogy of
  23     Fallot operation in children under 90 days during this
  24     time period in Bristol.
  25        If we look at inter-atrial TGAs, we can see that

   1     there was only one case and this case, unfortunately,
   2     died, and that gives a mortality of 100 per cent, but
   3     this is a very small figure. When you are talking about
   4     very small numbers of cases of admissions, perhaps less
   5     than 5, certainly, it is very difficult to make
   6     inferences from these figures because we are talking
   7     about very, very small numbers, and one death might make
   8     a lot of difference to the mortality.
   9        The figure that stands out in this graph is the
  10     group 3, "other transposition of great arteries". We
  11     can see here that in the rest of England, the mortality
  12     is 10 per cent. If you look at the mortality rate in
  13     UBHT, based on 10 cases, 9 out of those 10 cases died
  14     and that gives us a mortality of 90 per cent. Round
  15     about this estimate, we have given confidence intervals,
  16     and you can see these two bars there, which, as I said,
  17     reflect our uncertainty about this mortality rate and
  18     give a range of values in which we can be fairly
  19     confident that the true estimate lies.
  20        So from this we can say that this is unlikely to
  21     be due to chance, this mortality.
  22        If we look at group 4, TAPVD, we can see that the
  23     mortality rate there is 50 per cent compared to
  24     a mortality in the rest of England of somewhat less than
  25     20 per cent -- I think it is 16 per cent.

   1        The confidence intervals come very close to the
   2     national mortality, and actually, if you plot the
   3     confidence intervals of the national mortality, these
   4     two confidence intervals overlap, so we cannot be
   5     confident that this mortality rate has not occurred by
   6     chance.
   7        If we go down the rest of the operations, they are
   8     based on very, very small figures of one and two
   9     admissions, and our uncertainty in the mortality rates
  10     based on those small figures is reflected in the large
  11     confidence intervals.
  12        If we go to the broader class of open and closed
  13     operations, we can see that in the broad class of open
  14     operations, the mortality for UBHT is over 60 per cent
  15     while, in the rest of the country, it is under 20 per
  16     cent.
  17        The confidence intervals clearly do not overlap
  18     and therefore we can be fairly confident that this
  19     difference in mortality is unlikely to be due to chance.
  20        For closed operations, the mortality in Bristol is
  21     very, very similar to the rest of the country.
  22        Could we call up table 2.2 on INQ 13/55, please?
  23     This is the table on which this graph is based.
  24        In the first column we can see the total numbers
  25     of admissions for UBHT and elsewhere combined for this

   1     period in time, 1st April 1991 to 31st March 1995, of
   2     children aged less than 90 days.
   3        In the second column here we have figures for
   4     Bristol, for UBHT. In the first subcolumn, we can see
   5     the total numbers of admissions, with mentions of these
   6     13 procedure groups, and our open and closed classes of
   7     operations.
   8        In the second column, we can see the numbers of
   9     admissions for which we knew the outcome, and in
  10     brackets, there is the percentage of that against the
  11     total number of admissions. We can see perhaps looking
  12     at the open operations, if we run along here, we knew 30
  13     outcomes out of a total of 37 total admissions, meaning
  14     that 81 per cent of our admissions we knew the outcome
  15     to.
  16        The third column here is the number of deaths for
  17     each of these operation groups, and the fourth column is
  18     the mortality and in the next column, we have given the
  19     95 per cent confidence intervals for each of those.
  20        In the third larger column, we have the same
  21     figures for operations carried out in hospitals other
  22     than UBHT and we have valid numbers, we have the numbers
  23     that have died, we have the percentage that have died,
  24     the mortality and the confidence intervals around this.
  25        In the last column, we have expressed the ratio of

   1     the percentage that died in Bristol to the percentage
   2     that died elsewhere, as a ratio, as a mortality ratio.
   3        So just in summary, if we can go to page 103,
   4     [INQ 13/103] for children under 90 days for open
   5     procedures and I am just going to talk about the broad
   6     open class of procedures here, mortality was 63 per cent
   7     in the UBHT with a confidence interval of 44 to 80 per
   8     cent, which was four times higher than elsewhere in
   9     England, whose mortality was 16 per cent, with
  10     confidence intervals 14 to 18.
  11        In our analysis where we estimated the number of
  12     excess deaths for this group, using Bayesian methods, we
  13     estimated that there were 13.9 excess deaths out of
  14     a total of 19 deaths that occurred in Bristol for
  15     children aged under 90 days.
  16        To the next page, 104. For specific procedure
  17     groups, other TGAs, transposition of the great
  18     arteries -- this was group 3 -- had a mortality of
  19     90 per cent, although this was just based on 10 cases,
  20     which was 9 times higher than elsewhere, where the
  21     mortality was 10 per cent, with a confidence interval,
  22     8 to 13 per cent.
  23        We estimated that there were an excess of 7.8
  24     deaths with an interval of 5 to 9 out of a total of 10
  25     deaths in this group.

   1        One thing to emphasise is that many of the other
   2     groups also had high mortalities, but they were based on
   3     only one or two cases, and it is difficult, if not
   4     impossible, to draw statistical inferences from those
   5     very small numbers.
   6        For closed procedures, if we go to page 105, just
   7     to summarise, mortality, GBHT was 5 per cent, the same
   8     as elsewhere, running at 5 per cent.
   9        If we can go to the next age group, 90 days to
  10     1 year and if you can put up the graph on page 74, and
  11     rotate that around? We can see that the groups with
  12     a high mortality are AVSDs and ASDs in groups 5 and 6.
  13     Where you can see that the mortality of group 5, for
  14     atrial ventricular septal defects is over 40 per cent in
  15     Bristol and at under 10 per cent in the rest of the
  16     country.
  17        For ASDs, the mortality rate was over 60 per cent
  18     in Bristol and less than 5 per cent in the rest of the
  19     country.
  20        All the other operations again are based on fairly
  21     small numbers, apart from these closed operations and
  22     also this closure of VSD. The small numbers, the
  23     confidence intervals are fairly wide and tend to overlap
  24     the mortality rate in the rest of the country.
  25        For open classes of procedures, you can see that

   1     the mortality rate is round about 20 per cent in Bristol
   2     and well under 10 per cent in the rest of the country.
   3     I will give you the exact figures in a minute, although,
   4     for closed operations, again, the mortality was exactly
   5     the same as it was in the rest of the country.
   6        Could we have table 2.3 on page 56? Again, this
   7     just shows the figures the graph is based on. I will
   8     not dwell too much on that, except to look at perhaps
   9     just the open procedures here, and we can see that there
  10     was a mortality of 19 per cent in Bristol, with
  11     confidence intervals 13 to 28 per cent, compared to
  12     a mortality in the rest of the country of 7 per cent
  13     with confidence intervals of 5 to 8 per cent, with
  14     a ratio of the mortality in Bristol compared to
  15     elsewhere of 3. The mortality rate was three times
  16     higher.
  17        So just to summarise the children aged under
  18     90 days to 1 year, if we could go to page 106, as I have
  19     just said, the open class of operations, the mortality
  20     was three times higher than elsewhere in England, and
  21     our estimated numbers of excess deaths were 14.4 amongst
  22     a total of 22 deaths, with a 95 per cent interval
  23     between 7 and 20.
  24        To page 107. The procedure groups which stand out
  25     as having a high mortality in this age band, 90 days to

   1     1 year, was AVSD procedures, and closure of atrial
   2     septal defects as well.
   3        For AVSDs, the mortality was 43 per cent, which
   4     was 4.6 times higher than elsewhere in England, with an
   5     estimated 7 excess deaths amongst a total of 9 deaths in
   6     that age group, and for closure of ASDs, the mortality
   7     was 63 per cent, which had a very much higher mortality
   8     than elsewhere, which was 4 per cent. That is 17 times
   9     higher, although you must remember that these are based
  10     on relatively small figures.
  11        The estimated excess numbers of deaths was 4.7 out
  12     of a total of 5 deaths.
  13        If we go to page 108, again we note that closed
  14     procedures had a very similar mortality in Bristol as
  15     elsewhere, at 4 per cent.
  16        For children aged 1 to 15 years, if we could call
  17     up graph 75 on page 75, and rotate that, you will note
  18     that none of the mortality rates for any of the
  19     operation groups or the broad open or closed classes of
  20     procedures had a significantly higher mortality than the
  21     average compared to the rest of England, although you
  22     will note in the open class of operations the confidence
  23     interval is very close to the national rate.
  24        For all ages, we were able to add up the total
  25     excess deaths which, for each of the age groups, for

   1     each of the procedure groups, and for the open and
   2     closed classes of operations, which included minus
   3     numbers and plus numbers, representing the difference in
   4     the deaths that we would expect, and if we go to
   5     page 110, I can just summarise the figures here. So for
   6     all children aged under 16 years, based on the 13
   7     procedure groups, there were 35.3 total excess deaths
   8     out of 67, and that should be UBHT rather than BRI.
   9        With a confidence interval of between 21 and 48,
  10     a 95 per cent interval of 21 to 48.
  11        That is based on the 13 procedure groups. If we
  12     look alternatively at the other classification of open
  13     and closed class of procedures, we will find a similar
  14     figure of 32.9, total excess deaths, out of 69 in the
  15     UBHT, with a 95 per cent interval of between 9 and 49.
  16        For the moment I have spent quite a bit of time
  17     presenting data on mortality, but we wanted to look at
  18     other outcomes in a very limited way, limited by the
  19     limitations of the HES data, but we wanted to look at
  20     complications from surgery.
  21        There is a diagnosis code based on the
  22     international classification of diseases, the 9th
  23     revision, and this is a series of codes which is used to
  24     code for the diagnosis for each admission. There are
  25     several of these codes which refer to complications from

   1     surgery.
   2        If we could go to page 58 and first of all look at
   3     table 2.5, so the top table, the ICD 9 codes for these
   4     complications are 997.0, which indicates complications
   5     to the central nervous system, which includes brain
   6     damage, cardiac complications, which is ICD 9 code 997.1
   7     and respiratory complications, 997.3, and also urinary
   8     complications, 997.5, which would include renal
   9     failure.
  10        We can see, looking at the central nervous system
  11     figures here, that out of -- this is looking at all
  12     ages, 0 to 15 -- 505 admissions, 8 admissions had
  13     a mention of complications from surgery to the central
  14     nervous system. That is 1.6 per cent of admissions,
  15     with confidence intervals of 0.7 to 3.1.
  16        If you look at the rate of complications mentioned
  17     elsewhere in hospitals other than UBHT, we can see that
  18     there are 28 admissions with a mention of this
  19     complication, a 0.4 per cent rate of complications, or
  20     rates of recorded complications, I should say, on this.
  21     We can see the confidence intervals here are 0.2 to 0.5.
  22        Because these two confidence intervals do not
  23     overlap, we can be reasonably sure that these
  24     differences are not due to chance. What they are due to
  25     we do not know.

   1        We can go down the other complications here as
   2     well. We can see that for cardiac complications the
   3     rate is 11.1 per cent compared to 4.3 per cent, which
   4     has significantly more -- there is a significant
   5     difference there. For respiratory complications, again,
   6     there is a significant difference in the complication
   7     rate between Bristol and elsewhere. For renal failure
   8     or urinary complications the differences are not
   9     significant. So that is for open procedures.
  10        If we look at table 2.6, we can see the same table
  11     for closed procedures. The complication rates are
  12     a little lower than in open procedures. We can see that
  13     there are, certainly for cardiac and for -- for cardiac
  14     operations there is a significant difference in the
  15     complications. But, otherwise, there is no significant
  16     difference in the -- I am sorry, and also for
  17     respiratory. But otherwise there is no significant
  18     difference.
  19        One of the problems with looking at this diagnosis
  20     code is that it is not possible to distinguish between
  21     pre-existing disease or illness and complications
  22     resulting from the operation in question. So these
  23     complications may have existed as a result of another
  24     previous operation, an unrelated operation. We are
  25     unable to tell whether the diagnosis was made before the

   1     operation or after the operation. So that is one
   2     warning with this data.
   3        The other warning, and we will see some evidence
   4     of this a little bit later, is that Bristol may have
   5     been slightly better at recording diagnosis, and this
   6     may help to explain this difference. So it may be
   7     a data quality issue rather than an actual complication
   8     rate from the operation.
   9        We also looked at length of stay as a possible
  10     indicator of outcome. If we could go to table 2.7 on
  11     page 58, this table 2.7 gives the proportion of patients
  12     going home for each week after admission. We can see,
  13     for Bristol and for elsewhere. We can see that this is
  14     the first seven days after admission. In Bristol only
  15     2 per cent go home within the first week for open
  16     operations. Elsewhere, 27 per cent go home in the first
  17     week.
  18        If we look at closed operations, we again see
  19     a big difference in the proportion of patients going
  20     home in the first week. For Bristol, we have 14 per
  21     cent of patients going home in the first week, and
  22     elsewhere we have 50 per cent of patients going home in
  23     the first week.
  24        If you look at the other weeks of admissions,
  25     there is not so much of a difference, and actually the

   1     main difference appears to be in the first week after
   2     admission.
   3        There could be several explanations for this. We
   4     only looked at length of stay from admission, and it may
   5     be that Bristol may have had a longer period of time
   6     before the operation, a longer pre-op' time than
   7     elsewhere, which would account for less going home in
   8     the first week. It may also be true that one might
   9     argue that having a longer length of stay meant that
  10     Bristol hung on to their patients for longer and perhaps
  11     that might be an indication of better care or not so
  12     good care. It is very difficult to say, so I can only
  13     present the figures here and perhaps someone else might
  14     be able to interpret that in the light of other
  15     information.
  16        I have talked about outcomes and we have looked at
  17     mortality, we have looked at length of stay and we have
  18     looked at complication rates.
  19        One of the other things that we were asked to look
  20     at was activity, or operation rates.
  21        One of the problems of looking at operation rates
  22     for a geographical area, for a catchment area, is that
  23     you need to define a catchment area for the hospital.
  24     You need to know the population that each centre was
  25     working on in order to get a rate of operations.

   1        There are problems with defining catchment areas
   2     for hospitals. There are some guidance on
   3     administrative catchment areas, but these can sometimes
   4     be a little vague, referring to parts of health
   5     authorities or parts of a region, and are sometimes
   6     difficult to interpret.
   7        So we wanted to look at activity for each of the
   8     centres, each of the 12 centres that we looked at, and
   9     therefore we decided to define our catchment areas in
  10     two different ways.
  11        We looked at a geographical catchment area based
  12     on geographical proximity to each centre. So we looked
  13     at each Health Authority across the country and
  14     whichever centre that Health Authority was closest to,
  15     we said that was within that centre's catchment area.
  16        We also looked empirically at where the majority
  17     of patients from each Health Authority were treated and
  18     defined catchment areas in that.
  19        I will just show you a map, although it does not
  20     come up very clearly on this reproduction. If we go to
  21     page 80 and rotate. Sadly it does not come up very well
  22     at all. The originals were actually produced in
  23     colour. But you can see the different centres dotted
  24     around the country, and this is Liverpool, Freeman
  25     Hospital, Killingbeck, Glenfield and the number of

   1     hospitals that we looked at. Then this small section is
   2     enlarged to give the four London hospitals: Harefield,
   3     Royal Brompton, Great Ormond Street and Guy's.
   4        This map of England is divided up into health
   5     authorities, and each health authority is shaded
   6     according to its geographical proximity to the centre.
   7        You will notice that Wales is not shaded here, and
   8     that is because the data that we were able to use was
   9     based on admissions to English hospitals. Admissions to
  10     Welsh hospitals are recorded using a different system
  11     called PEDW, or the patient episode database in Wales.
  12     We did not have access to that, and therefore we did not
  13     include Wales in our analysis.
  14        In fact in the activity based analysis we excluded
  15     all Welsh children who were treated in Bristol, simply
  16     because we did not have the denominator for the rest of
  17     Wales. But in all the other analysis we have included
  18     all Welsh children treated in Bristol. But just for the
  19     activity analysis, we have excluded those so we can get
  20     rates.
  21        Could we go to table 4.1 on page 62 --
  22   Q. Could I ask, Dr Aylin, if it would be convenient to deal
  23     very quickly with this and then have lunch, or whether
  24     you prefer to come back to this after a lunch break?
  25   A. I would prefer to get it all over and done with. I can

   1     go through it fairly quickly.
   2   Q. Can we deal with this table, and then we will have
   3     a break, please?
   4   A. All right, yes. Page 62, please.
   5        This table gives us activity based on the
   6     populations as we have defined geographically for each
   7     of the main centres. Because London has a very
   8     complicated catchment area arrangement and it is almost
   9     impossible to define a catchment area for London, we
  10     have grouped London into one large centre and one large
  11     catchment area.
  12        This first column represents the number of
  13     admissions for which we did not have a postcode, so we
  14     were therefore unable to identify where they had come
  15     from.
  16        This second column is the number of admissions.
  17     The third column is the population. When we are looking
  18     at children aged under 1 year, we base the population on
  19     the numbers of live births per year.
  20        Looking at activity, the first column is the
  21     centre activity. So that is the rate of operations
  22     carried out by Bristol in this first line on the Bristol
  23     population, and the same for the other centres. That
  24     gives an operation rate for open operations carried out
  25     by Bristol on its own catchment area of population,

   1     which is 0.72.
   2        If we look at the second column we can look at the
   3     total number of operations, so that is operations
   4     carried out by Bristol and other centres on the Bristol
   5     catchment area, which is 1.09.
   6        Interestingly to note here, for Bristol the centre
   7     rate activity for open classes of procedures was
   8     relatively low compared to the other centres in the
   9     country. This was mainly, it seems, because many
  10     patients were actually going out of the geographical
  11     catchment area. We can actually see the number of
  12     patients who went out of the area to be treated, and
  13     that is 73. Very interestingly, one can note that no
  14     patients came in from other catchment areas to Bristol
  15     to be operated on by UBHT.
  16        That is interesting, as all the others do seem to
  17     have a flow in and out. So the one thing to note from
  18     this table is that there seemed to be a low centre rate
  19     activity, that is numbers of operations carried out by
  20     Bristol, which is probably explained by patients going
  21     out of the area to be operated on by other centres.
  22        Table 4.3 looks at another age band; those
  23     patients over 1 year. That is on page 64. But the main
  24     thing to note is that for open operations for children
  25     under 1 there seem to be a low operation rate by Bristol

   1     and many of the patients seem to go out of the catchment
   2     area.
   3        For children aged 1 to 15, you can see a similar
   4     flow in that 90 patients went out and only 9 patients
   5     came in.
   6        So I think in terms of activity, I think we can
   7     pause there. Thank you.
   8   MR LANGSTAFF: Dr Aylin, thank you very much thus far. We
   9     will take a break. I know the Chairman will want to
  10     have one now. Can I say before the break is announced
  11     that there may well be, from those who are in the
  12     immediate vicinity, questions that they may have which
  13     it may be appropriate should be addressed to you through
  14     me when you have finished your presentation. If that is
  15     the case, I would be grateful to hear of them so I can
  16     deal with any question or queries that arise. But thank
  17     you thus far.
  18   THE CHAIRMAN: Shall we break now until 2 o'clock? Thank
  19     you, Professor Evans and Dr Aylin. We will come back
  20     and continue after the break.
  21   (1.25 pm)
  22            (Adjourned until 2.00 pm)
  23   (2.00 pm)
  24   MR LANGSTAFF: Sir, Dr Aylin had just dealt with the
  25     catchment areas, with activity rates and inflows and

   1     outflows from the various different centres.
   2   A. I think that has covered activity for the moment. The
   3     next section of our report attempted to look at case
   4     mix, or disease severity, and co-existing diseases.
   5        It is important to look at this because high
   6     mortality or low mortality can be explained in a number
   7     of different ways, through chance and we have looked at
   8     our analysis incorporating confidence intervals in that,
   9     through aspect of data quality, perhaps I will talk
  10     a little more about that when I sum up, and perhaps more
  11     importantly about the severity of the cases actually
  12     seen.
  13        This is why we looked at case mix.
  14        The first thing we looked at was age at operation,
  15     to get an idea of the proportion of children in each age
  16     group that UBHT was operating on, compared to the rest
  17     of England.
  18        If we go to table 5.1 on page 69, [INQ 13/69] we
  19     can see this is the age breakdown of children operated
  20     on with open procedures between the time period that we
  21     were looking at.
  22        We can see that under 90 days here, in Bristol
  23     only 7 per cent of the total number of operations was
  24     made up of children under 90 days in the UBHT, compared
  25     with 22 per cent elsewhere. So that is for open

   1     operations.
   2        For closed operations which we can see in
   3     table 5.2, we can see that the proportions are very much
   4     more similar, with 40 per cent of the patients that UBHT
   5     saw under 90 days, compared to 45 per cent elsewhere.
   6        There does appear to be a different age mix in
   7     open operations for this period of time.
   8        We also looked at the diagnosis given to the child
   9     on the Hospital Episode Statistics data set, and the
  10     primary diagnosis recorded in each episode. If we can
  11     go to table 5.3 on page 70, table 5.3 gives the most
  12     common primary diagnosis given in admissions with open
  13     procedures between the time period that we are looking
  14     at.
  15        Actually, certainly as far as the general pattern
  16     is concerned, the only difference that really stands out
  17     to my mind is this category here (indicating) which is
  18     the other ill-defined and unknown causes of morbidity,
  19     or ICD code 799. This is often used as a dump code
  20     where diagnosis is not clearly recorded either on the
  21     notes or by the coder, and instead of putting no
  22     diagnosis on there, this rather vague catch-all
  23     diagnosis of 799 is given.
  24        You can see here that in Bristol in the UBHT, none
  25     of the patients seen at Bristol were given this code for

   1     open procedures, this is for all ages 1 to 15, whereas
   2     elsewhere, approximately 9 per cent of cases were given
   3     this rather vague code, which suggests to me that in
   4     Bristol, coding was of a higher quality than elsewhere.
   5        The other diagnoses seemed to have fairly similar
   6     proportions, and so, as far as that is concerned, it
   7     does not look as though the diagnosis are greatly
   8     different in Bristol than elsewhere, but the 799 code
   9     sticks out. You can see that to a lesser extent in
  10     table 5.4, which looks at closed procedures and for all
  11     ages, you can see very few, only one admission has this
  12     code of 799, compared to 7 per cent elsewhere, again
  13     suggesting better diagnostic coding.
  14        The last thing we looked at was co-existing
  15     disease and we looked at admissions with a diagnosis of
  16     Down's syndrome. If we could go to table 5.5 a little
  17     bit lower down on that page, we can see within the open
  18     category that in Bristol 10.3 per cent of admissions had
  19     a diagnosis of Down's syndrome, with confidence
  20     intervals 7.8 to 13.3, whereas elsewhere 7 per cent had
  21     a diagnosis of Down's syndrome, with confidence
  22     intervals 6.4 to 7.5.
  23        The confidence intervals do not overlap here, so
  24     there is a significant difference there, but as we have
  25     already mentioned earlier, it does seem that Bristol was

   1     slightly better at recording their diagnosis and this
   2     may explain this difference.
   3        For closed operations, there is a difference
   4     between the diagnosis, but the confidence intervals
   5     overlap, so there is no significantly statistical
   6     difference there.
   7        We looked at deprivation as well, socio-economic
   8     deprivation, because for each admission we had
   9     a postcode. We could look at the area in which that
  10     postcode was and use 1991 census data to try and
  11     determine the kind of area that the admission came
  12     from. There is a well-used score of socio-economic
  13     deprivation called the Carstairs score and we used five
  14     divisions of this score, with division 5 or quintile 5
  15     being the most deprived group of areas, and Carstairs 1
  16     or the first quintile being the least deprived of
  17     areas.
  18        The idea behind this was, in many diseases the
  19     outcome for these diseases is worse for people living in
  20     deprived areas rather than less deprived areas. We
  21     thought if Bristol was operating on many more people
  22     from deprived areas, this may perhaps account for a high
  23     mortality.
  24        Let us just look at table 5.6 on page 71, first.
  25     We can see our Carstairs scores down here, 1 to 5, so

   1     these are admissions from most deprived areas and
   2     admissions from least deprived areas, and the in-between
   3     scores, and we have worked out the percentage of
   4     patients from each of the areas that were operated on by
   5     Bristol.
   6        You can see that Bristol, out of all its cases,
   7     only operated on 11 per cent of its patients which were
   8     from the most deprived areas, whereas elsewhere 22 per
   9     cent came from the most deprived areas.
  10        This may be a result of several things. It may be
  11     that there are just less deprived people in the Bristol
  12     catchment area and that may explain why there are less
  13     operations there. I do not know. But there are several
  14     explanations for that.
  15        Table 5.7 looks at mortality rate for open
  16     procedures by Carstairs quintile for all centres
  17     combined excluding Bristol, to try and get an idea of
  18     whether, if you come from a deprived area, you have
  19     a greater chance of dying.
  20        Actually, the figures do not suggest this. The
  21     figures down the five Carstairs quintiles, 1, 2, 3, 4
  22     and 5, certainly for open operations are quite similar,
  23     so it does not look like the mortality is any different
  24     if the patient comes from a less deprived area or from
  25     a deprived area.

   1        If we look at table 5.8, this is for closed
   2     operations and mortality. We can see that figures are
   3     fairly similar up in the most deprived area, where there
   4     is a slightly higher mortality there.
   5        That is essentially our analysis. I just want to
   6     sum up a little bit and talk about one or two of the
   7     problems with the data. First of all, I just wanted to
   8     talk about our mortality analysis. There were
   9     differences in mortality, quite large differences in
  10     mortality, for open operations in children under 1 year,
  11     particularly in children aged under 90 days.
  12        It seems, looking back at other studies that have
  13     looked at how well mortality is recorded on HES data,
  14     that the fact of death is well recorded on HES data, but
  15     we are a little bit concerned about the admissions in
  16     which we did not know whether the patient had been sent
  17     home or whether the patient had died.
  18        Certainly for some of the operation groups this
  19     was not an insignificant percentage.
  20        It could be that if Bristol were very good at
  21     recording mortality and everyone who died was actually
  22     recorded on there, then all these other admissions when
  23     the outcome was not recorded may have survived. What
  24     would make things worse was that elsewhere, if other
  25     centres in the country were not so good at recording

   1     mortality and did not pick up all the cases that had
   2     died, then Bristol might appear to have a high mortality
   3     rate than elsewhere, simply because it was better at
   4     recording deaths.
   5        We actually did a little experiment and looked at
   6     this, and assumed that in Bristol all the cases where
   7     the outcome was unknown survived and for the rest of the
   8     country, we assumed that all the cases where we did not
   9     know the outcome had died. Then we did a re-analysis of
  10     this data.
  11        In doing that, in fact in being generous to
  12     Bristol in saying that it had picked up all its deaths
  13     and all the missing cases had survived and the opposite
  14     with the rest of the country, we still noted these
  15     differences in open operations in children under 90
  16     days; they were still there.
  17        So we think that actually mortality is probably
  18     quite well recorded. As far as complications are
  19     concerned, the complications from surgery we do not
  20     think are very well recorded. I think one could think
  21     of reasons why hospitals would not be recording that
  22     diagnosis in the HES data set, because often this
  23     diagnosis comes out some time after the admission. So
  24     we are not completely confident about what the
  25     complication rate actually tells us.

   1        For the length of stay as well, that can be
   2     affected by many things, not just quality of care but
   3     administrative procedures. This was length of stay from
   4     admission to discharge, and it may be that there could
   5     have been a longer period before the operation for
   6     administration, for blood tests and things which may
   7     have accounted for this length of stay.
   8        So again with length of stay, I think that has to
   9     be interpreted with a great deal of caution.
  10        For our activity rates, which we found were on the
  11     lowish side for open operations and the patient flows --
  12     patients tend to go out of the catchment area rather
  13     than into the catchment area -- again, the methods by
  14     which we defined catchment areas, using the two methods
  15     empirically and geographically, did tend to change these
  16     results, and because of the difficulty in defining
  17     catchment areas, we would be rather cautious about
  18     interpreting those results.
  19        As far as case mix is concerned, we were only able
  20     to look in a very limited way at case mix, and I think
  21     there is more work that needs to be done on case mix,
  22     and possibly HES is not the right data set to explain or
  23     to go into detail about case mix.
  24        Certainly, as far as the Down's syndrome, it did
  25     seem as though Bristol was better at recording diagnosis

   1     and that could account for the higher proportion of
   2     patients with Down's syndrome. That seems to be shown
   3     in the primary diagnosis tables which we looked at,
   4     which did suggest that UBHT was better at recording
   5     diagnosis.
   6        I think that is all I have to say.
   7   MR LANGSTAFF: Not quite all you have to say, I hope,
   8     because there are one or two questions for you, which
   9     I hope may not detain you long.
  10        There is a large chunk at the start of your
  11     report, and I should have told you at the outset of your
  12     evidence -- I am telling you now and you understand, and
  13     I know, that your report is of course received and taken
  14     as read, and you have been highlighting certain parts of
  15     it, but there is a large chunk at the start of your
  16     report which explores the quality of the data.
  17        What, in your view, are the weaknesses of the
  18     data, in just two or three sentences?
  19   A. I think there may be problems with misclassification of
  20     procedures, in that the coding process in the PAS
  21     systems which feed into the HES systems, and the
  22     difficulty in interpreting some of the diagnosis on the
  23     clinical records, and the procedure coding, could lead
  24     to some misclassification of procedures.
  25        So I think that is one problem that we have to

   1     bear in mind.
   2   Q. That presumably is not only as across every centre;
   3     even if they had coders of equal experience dealing with
   4     matters in exactly the same way, you do not know, do
   5     you, necessarily, whether coders did have the same
   6     experience and did operates in the same way?
   7   A. I think that is one of the problems, but to add to the
   8     misclassification problem, if there was random
   9     misclassification, if high risk operations were coded as
  10     low risk operations and some low risk operations were
  11     coded as high risk operations, that would tend to blur
  12     the findings that we find. Actually, if the coding was
  13     perfect, we may see even greater differences in
  14     mortality than we see here, because the picture is
  15     somewhat clouded by misclassification. That is not
  16     necessarily an argument to discount the findings in this
  17     report.
  18   Q. Are there, do you think, any particular weaknesses, not
  19     so much in the data as in the analysis which you have
  20     conducted?
  21   A. This HES data has not been used very often for this kind
  22     of work. This is a first. I think actually this
  23     analysis has to be seen in the context of all the other
  24     analyses that will be presented to you and have been
  25     presented to you.

   1   Q. Are you saying that without those other analyses, one
   2     might not be able to draw firm conclusions?
   3   A. I think the findings are quite strong, and before
   4     I started the analysis, I was not sure that I was
   5     actually going to find anything here, but the findings
   6     are so strong, I think it would be difficult to account
   7     for the findings in terms of data quality, in terms of
   8     case mix.
   9   Q. I was going to ask you about both of those things:
  10     strength and data quality. In terms of strength, for
  11     instance, you showed us slide 13/107, the bottom of the
  12     page, please, where the point figures might suggest that
  13     closure of ASD had a mortality nearly 18 times higher
  14     than elsewhere, which is a startling finding, if it be
  15     right?
  16   A. Yes.
  17   Q. One would have to read that subject, would one, to the
  18     confidence intervals, which might suggest that in fact
  19     the difference might be between 24 per cent at the
  20     bottom of one range and 10 per cent at the top of the
  21     other?
  22   A. Yes, that is true.
  23   Q. So it may in fact be only 2.4 times?
  24   A. Yes. We have to be very careful about the point
  25     estimates there and take into consideration the range of

   1     values, because these are based on fairly small numbers.
   2   Q. On the same theme, you showed us a bar graph, 13/73.
   3     Turn it sideways. We are comparing, here, are we,
   4     Bristol against first of all the average of other
   5     centres?
   6   A. This is the average for the whole country.
   7   Q. So this is not other centres. But each of those bars
   8     would, itself, have to have a range, as it were an
   9     extension bar?
  10   A. Yes.
  11   Q. In order to demonstrate whether or not there was or was
  12     not 95 per cent statistical confidence that the results
  13     were different?
  14   A. Yes. The national figures are also based on numbers
  15     which may fluctuate from year to year and therefore we
  16     need a confidence interval around that.
  17        We have not included it on the graph, but we have
  18     included it on the tables.
  19   Q. It is the clarity for presentation that needs to be
  20     emphasised. Rightly you mentioned it at the time, but
  21     I give it emphasis now in this question.
  22        You do give us some data. Let us look at
  23      INQ 13/61. I am not going to ask you about this in
  24     detail, because Dr Spiegelhalter will have that
  25     pleasure, but you set out here 12 other centres, or 11

   1     other centres, and their rates in respect of operations?
   2   A. These are excess numbers of deaths, yes.
   3   Q. In relation to those, you have drawn attention
   4     nationally, something like 9 per cent of all operations
   5     are ascribed to what you call a "dump code",
   6     unclassified?
   7   A. Yes -- no. No. The procedures, the diagnosis was
   8     assigned to a dump code, yes.
   9   Q. May it be the case that variability as to which centre
  10     is dumped and therefore had poor quality data may be
  11     quite great? So some centres may diagnose very well and
  12     record very well; some may not?
  13   A. Yes, that is true.
  14   Q. To the extent one is looking at a centre which may not,
  15     there may be quite a degree of variability around the
  16     results of an individual centre?
  17   A. That is true, although we are looking at the variability
  18     of diagnosis coding and probably variability of
  19     procedure coding, but the fact of death I think is
  20     probably fairly well recorded. So you would get less
  21     cases perhaps if you were trying to pull out all
  22     operations that you were interested in, because some
  23     people may have had operations that would not be coded
  24     to that in the records and you would not therefore be
  25     able to pull them out and look at them.

   1   Q. Is this a question for you or for Dr Spiegelhalter:
   2     Bristol, as we have explored in the evidence, had
   3     relatively low numbers of operations. Some other
   4     centres did, too, and some had much higher numbers. We
   5     have been told that there was a feeling that less in
   6     number meant less success in terms of having mortality
   7     rates.
   8        Are you able to form any view as to whether your
   9     data justifies that conclusion or not? If so, should
  10     one not perhaps be comparing Bristol with those other
  11     centres of comparable size?
  12   A. We have not looked at that in the data. We have not
  13     compared Bristol to other centres of comparable size.
  14     That is a possibility. We are still talking about
  15     rather large differences in that particular age group of
  16     under 1s and I am not sure that would explain the
  17     difference. I think probably you might need a clinician
  18     to comment on that better than myself.
  19   Q. The last thing I need to ask you about is this: when we
  20     dealt with complications, you very fairly indicated that
  21     one cannot say, from looking at the data, whether the
  22     incidence of complication is recorded in respect of
  23     Bristol patients meant that they came to Bristol in
  24     poorer condition and were operated upon, or whether they
  25     were operated upon and thereby, or afterwards, developed

   1     poorer condition; or whether it is a mixture of the
   2     two. The data simply does not tell you. Have I got
   3     that right?
   4   A. Yes.
   5   Q. But you did indicate that the statistical difference
   6     there may be a product of the better data quality which
   7     Bristol had.
   8        If that is true for morbidity, why is it not true
   9     for mortality?
  10   A. As I said before, from other literature and I have
  11     recorded something in my report, quoted one study which
  12     looked at recording of mortality. Henderson et al
  13     looked at data from six health districts between 1979
  14     and 1985 -- this is an old study -- but found that
  15     98.2 per cent of hospital records which had specified
  16     that death occurred in hospital could be matched with
  17     the corresponding death certificate.
  18   Q. That was 1985 and before, so that is looking at the
  19     pre-HES data set?
  20   A. Yes, and it is looking at the clinical records rather
  21     than the actual coding system.
  22   Q. So one would need to match HES up with national records?
  23   A. I think to be sure, if it was possible to link HES
  24     records with mortality records and follow up all these
  25     cases to see whether they had died or not, that might be

   1     an interesting analysis to do and could lend perhaps
   2     some support to the analysis of the data.
   3   Q. Interesting, I have no doubt; useful for the Inquiry?
   4   A. Yes, I think it would be useful.
   5   MR LANGSTAFF: Sir, I do not know whether the Panel have any
   6     questions?
   7   THE CHAIRMAN: We have a number of detailed matters which we
   8     may deal with by exchange of correspondence and put in
   9     the public record over time. I think it would be
  10     advantageous to move along at the present moment. Thank
  11     you very much indeed.
  12   MR LANGSTAFF: Thank you, Dr Aylin. Would you like to
  13     remain at the front, as it were, while we hear from
  14     Professor Murray?
  15          PROFESSOR GORDON MURRAY (SWORN):
  16            Examined by MR LANGSTAFF:
  17   Q. Professor Murray, your full name, please?
  18   A. Gordon Douglas Murray.
  19   Q. And as before, briefly your qualifications?
  20   A. I am a Professor of Medical Statistics at Edinburgh
  21     University. I have an MA, a Diploma in Mathematical
  22     Statistics, a PhD. I am a chartered statistician and
  23     although I am not clinically qualified or trained, I am
  24     a Fellow of The Royal College of Physicians of
  25     Edinburgh.

   1   Q. You prepared a report for the purposes of this Inquiry,
   2     together with Audrey Lawrence and John Pollock, which we
   3     find at Inquiry 14/1, do we?
   4   A. That is correct.
   5   Q. After a number of tables and figures and appendices, it
   6     finishes on page 78. Would you like to tell us what you
   7     found?
   8   A. I would like to present the results of the work that was
   9     undertaken by myself and colleagues at Edinburgh
  10     University.
  11        We were commissioned by the Inquiry to look at two
  12     of the relevant data sources. There was the United
  13     Kingdom Cardiac Surgical Register and the South West
  14     Congenital Heart Register.
  15        For both of these sources, we were asked to
  16     comment on the data quality and for the UK register,
  17     which is a national register, we were asked to look at
  18     surgical activity and outcomes in Bristol relative to
  19     elsewhere in England.
  20        I shall be presenting a summary of our findings.
  21     The report and my presentation this afternoon will very
  22     much focus on data quality. I will talk about activity
  23     and outcomes at Bristol relative to elsewhere, but
  24     I think Dr Spiegelhalter's report looks at this far more
  25     comprehensively than we have been able to do, and

   1     I think I would defer to Dr Spiegelhalter's report for
   2     most of that analysis.
   3        The two data sources we were looking at have been
   4     described in some detail already at the Inquiry, but
   5     I think it is probably useful just to give a quick
   6     summary.
   7        The UK register was a voluntary system, an
   8     anonymous system that was run by the Society of
   9     Cardiothoracic Surgeons of Great Britain and Ireland.
  10     It was established in 1977, and cardiac units each year
  11     submitted summaries of their activity and of the
  12     outcome.
  13        If we could maybe turn to page 14/63, [INQ 14/63],
  14     this is an example of the form that was used to record
  15     the information. There was information on adult
  16     surgery, but I am not looking at that at the moment.
  17     I am focusing on the congenital surgery. For each unit
  18     for each year, there were three pages similar to the one
  19     we see here. We can see that the data are broken down,
  20     first by age, so we are looking at children under 1
  21     year, and then for individuals over 1 year. One aspect
  22     we have already discussed is that there was no upper age
  23     limit so there are adults included, unlike the other
  24     data we have been looking at. As well as that breakdown
  25     by age, there was a breakdown by open versus closed

   1     surgery.
   2        We have had a lot of discussion this morning about
   3     the problems in classifying open versus closed. This
   4     essentially does not apply to this particular data
   5     source, because that is not something that we as
   6     analysts imposed upon the data. It is actually there;
   7     it is an intrinsic part of the data collection and the
   8     surgeons themselves have assigned cases as being
   9     actually open or closed.
  10        Within any of these categories, the open, closed,
  11     under 1 year, we have a huge number of diagnostic
  12     groups. A number of these diagnostic groups are then
  13     split further by the type of procedure that was done,
  14     whether it was palliative or corrective.
  15        So, within each of these categories, the surgeons
  16     returned the number of cases and the number of deaths.
  17     So, for example, in the form, for ASD, individuals aged
  18     over 1 year, undergoing open surgery, there were 19
  19     individuals treated that year, none of whom died.
  20        So that is another key difference between this
  21     source and other data sources; we are not actually
  22     getting data on identifiable individuals, we are getting
  23     aggregate figures, saying how many of a particular type
  24     of case and of those, how many died. So essentially,
  25     that is the information we were dealing with there.

   1        That was actually a computerised database, and
   2     that was maintained by the cardiologists working at
   3     Bristol as against the surgeons who were responsible for
   4     the Cardiac Register. That database was used to record
   5     all patients who were referred from the South West
   6     Region to the Bristol cardiologists.
   7        That system actually dates back to 1966, and was
   8     certainly maintained up until May 1993, when the
   9     consultant largely responsible for running the system
  10     retired, and beyond 1993, up to the end of the Inquiry
  11     period, the data were still updated to some extent, but
  12     clearly the extent to which it was updated has decreased
  13     over time, as the one individual who wholly owned the
  14     system was no longer working there.
  15        So those were the sources we were looking at. Our
  16     first task was to examine the data quality, and when
  17     thinking about quality, it can be very helpful to
  18     separate out two different aspects, and it is what we
  19     have called the "primary quality" versus the "secondary
  20     quality".
  21        The primary quality essentially relates to the
  22     context under which the data were collected. Were the
  23     individuals collecting the data suitably trained? Were
  24     they suitably motivated? Were there clear written
  25     procedures explaining how the data ought to be

   1     recorded? How did one handle ambiguous codings? Were
   2     the data checked when they came in? Were they
   3     validated? Were they actually fed back to the
   4     individuals who collected the data so they could be
   5     validated and feed back comments? Were the data
   6     actually used? If one collects data and sticks them in
   7     a filing cabinet, they are not going to be checked; they
   8     are not going to be used.
   9        This aspect of data quality is crucial. If one
  10     wants to collect reliable data there needs to be
  11     adequate systems. The staff needs to be trained,
  12     motivated. You need good validation, the data actually
  13     to be used, so any problems that are there are found and
  14     resolved.
  15        One of the problems with primary data quality is
  16     that one cannot actually observe it simply by looking at
  17     the data themselves. I can be given a large body of
  18     data and that tells me nothing about the motivation of
  19     the individual who collected it. I like to visit the
  20     cardiac units and speak to the people involved in
  21     collecting the data, find out more about the background,
  22     but I was not able to do that systematically, so instead
  23     we have had to rely on information already presented to
  24     the Inquiry and also on a large number of fairly
  25     informal conversations that we had with people who are

   1     active in the area and knowledgeable about the
   2     background.
   3        The secondary quality issues really relate to
   4     things one can observe by looking at the data
   5     themselves. If, for argument's sake, the sex of the
   6     individual ought to be recorded, is it always recorded?
   7     Are dates always in sequence? So would a date of
   8     operation come after a date of birth, for instance? So
   9     one can look at the consistency and the completeness of
  10     the data.
  11        Those were the two aspects of quality that we
  12     looked at.
  13        If I start with the Cardiac Register, again here
  14     based on evidence that has already been presented to the
  15     Inquiry as well as our conversations, I think that it is
  16     very clear that the primary data quality was rather
  17     poor. In particular, the guidelines that were available
  18     for the data collection process were rather limited.
  19     There was next to no attempt to validate the data. The
  20     feedback to the centres that provided the data was
  21     fairly slow and not very systematic, and certainly,
  22     speaking to a large number of individuals involved in
  23     the process, they had the perception that the data were
  24     going into a black hole; nothing useful was going to
  25     emerge, so where was their motivation to collect

   1     reliable data?
   2        I think one can get into a vicious circle: if the
   3     data are not useful and they are not used, then why
   4     bother collecting them? I think that perception
   5     actually pervades a lot of the routine Health Service
   6     data. It goes beyond the Cardiac Register.
   7        I do not know the HES data particularly well
   8     because I have worked much more with the Scottish
   9     equivalent, the Scottish morbidity records, but I know
  10     a lot of my clinical colleagues in Scotland are very
  11     sceptical about these systems, again because they have
  12     no sense of ownership and they feel they are putting
  13     data into a black hole and there is no motivation for
  14     them to collect reliable data.
  15        If we turn instead to the data from the South West
  16     register, again, superficially, the primary data quality
  17     there is not ideal. There did not seem to be very clear
  18     written guidelines, but what distinguishes it from the
  19     national register is a very clear sense of ownership.
  20     There was essentially one consultant who drove this
  21     process for over 30 years and the staff working with him
  22     were also very stable over that whole period, so clearly
  23     there would be a consistency through the very fact it
  24     was the same individuals collecting the data.
  25        There were a number of specific problems that we

   1     encountered. With the Cardiac Register, one problem was
   2     the anonymity codes. The whole system was set up on the
   3     basis of anonymity and this was done by the Secretary to
   4     the Society allocating an anonymised code to each return
   5     before they were passed on for analysis.
   6        As we got to work with the data, it became
   7     apparent that there seemed to have been a change in
   8     those anonymous codes.
   9        We looked at this in quite a bit of detail and the
  10     Society also looked quite hard, but we could not find
  11     any documentation to support that change in coding,
  12     although the individual who is doing the analysis did
  13     recall that somewhere in the mid-1980s there was
  14     a change. It is our very strong belief from looking at
  15     the data that there was a change in those codes going
  16     from 1984 to 1985, and this has required us essentially
  17     to discard the data from 1984. We cannot be certain
  18     which return goes with which centre. I think from 1985
  19     onwards we are in a much more secure position.
  20        Another specific problem which I think relates to
  21     both data sources and we have discussed it at some
  22     length already today, is the question of reporting
  23     mortality. The guidelines that did exist for the
  24     national register said that the units ought to record
  25     all deaths within 30 days of operation. That is a very

   1     standard definition for mortality.
   2        Mr Keogh, in his evidence that he presented to the
   3     Inquiry on Day 38 explained that this actually changed
   4     and later on, I think very recently, the register has
   5     gone for in-hospital mortality rather than 30-day
   6     mortality.
   7        That is obviously much easier to track. It is
   8     interesting too, that Mr Wisheart in his evidence, on
   9     I think Day 41 to the Inquiry, actually implied that the
  10     definition he was using was deaths within 30 days or
  11     beyond 30 days, but during the same admission. So if,
  12     for argument's sake, Bristol was using that definition,
  13     it would tend to over-report mortality; other centres
  14     were maybe using in-hospital mortality which would tend
  15     to under-report.
  16        So I think there is a real possibility, a real
  17     risk of systematic differences in the way that mortality
  18     has been reported in different units.
  19        Again, Mr Stark's evidence on Day 50, he was
  20     obviously very concerned about the reliability of the
  21     mortality data and he clearly believes that it is
  22     under-reported systematically in the register.
  23        Again, just to elaborate on how difficult this
  24     problem is, I think there are also questions that there
  25     may be double-counting. The surgeons filling in the

   1     register were not meant to double-count procedures, but
   2     just thinking about how the return could have been
   3     completed, I think there is the potential for certain
   4     patients who had undergone several procedures, maybe to
   5     have each procedure counted each time, as it were, and
   6     if that patient died, maybe that death could have been
   7     recorded two or three times.
   8        Again, this is very anecdotal, but yet another
   9     surgeon we spoke to suggested that in his unit, deaths
  10     were only reported to the register if they were clearly
  11     a direct result of the operation, so we are not looking
  12     at all mortality but operative deaths.
  13        You would think death is so obvious and so easy to
  14     define, but that is not the case. There are all sorts
  15     of nuances in the way it can be detected, recorded, so
  16     I think we must be aware that there is a real question
  17     mark there.
  18        Looking at data quality, there was another
  19     exercise we were able to do which I think was very
  20     valuable and that was to compare the UK register with
  21     the report that was produced by a Working Party of the
  22     Royal College of Surgeons.
  23        In 1992, they were asked to prepare a report by
  24     the Department of Health, to look at supra-regional
  25     funding, and the Working Party from the College of

   1     Surgeons approached each of the different cardiac units
   2     and asked them to report on their activity from 1988
   3     through to 1991.
   4        I think it is an interesting commentary on the
   5     register that they did not actually go there to get
   6     their data because the information they wanted was
   7     precisely what was available in the national register.
   8     But that is not what they did: they gathered data
   9     independently and if we could turn to page INQ 14/39,
  10     this is a comparison which we did looking at the returns
  11     to the national register, that is the ones under
  12      "return", versus the ones that were made to the Working
  13     Party.
  14        The original of this was in colour, which helped
  15     things a little. If we can see, for example, here is an
  16     example of a centre where there is a fairly large
  17     discrepancy between the information that was returned to
  18     the Working Party and the information that was returned
  19     to the UK register.
  20        If we could page down to the bottom of that table,
  21     it takes a little work, but there is actually only one
  22     centre, centre J here, that returned identical figures
  23     to the UK Registry and to the Working Party.
  24     Interestingly, that is Bristol, which may be another
  25     indication that Bristol were somewhat fastidious in

   1     their data collection. Here, just an example, another
   2     centre, there in the last two years of their reporting,
   3     they are reporting substantially more activity to the
   4     Working Party than they did to the UK Register.
   5        I think that is just an example of how
   6     intrinsically difficult it is to report and record
   7     activity.
   8        You see two exercises which should have produced
   9     exactly the same information but raised some quite
  10     surprising discrepancies.
  11        If I could go on now to look at page 45 of my
  12     report, please, [INQ 14/45] this was a comparison
  13     between the returns to the UK register and the HES
  14     data. I want to just focus on a small part of the
  15     table. What I am doing there is looking just at the
  16     activity reported, the numbers here are the numbers per
  17     centre returned to the UK register and the corresponding
  18     numbers reported to HES. The column here to the right
  19     gives the ratio of those two numbers. You can see just
  20     by eye that the UK returns tend to be larger than the
  21     HES returns. 10 of the 12 centres report more activity
  22     to the register than was recorded through HES.
  23        You can see typically a centre will be returning
  24     maybe 20 to 30 per cent more activity to the other
  25     register than to HES. Centre 3 is a striking exception

   1     to that, which, according to HES, is far more active
   2     than the data returned to the register.
   3        I have similar information there on deaths, and
   4     also looking at the relative reporting of deaths. There
   5     is a lot of information there, but essentially the
   6     reporting of mortality rates is more consistent than the
   7     reporting of activity, but it certainly does raise in my
   8     mind some concerns.
   9        I would imagine that the HES data are recorded
  10     more consistently from centre to centre, and so the
  11     variability here probably reflects the difference in the
  12     rigour with which the data was returned to the register,
  13     but that is speculation, it is not something supported
  14     by the data.
  15        If we could move on to page 47, please
  16     [INQ 14/47], this is looking at similar information but
  17     for Bristol alone. If we home in here just in the
  18     children aged under 1 undergoing open surgery, again, we
  19     see a fairly consistent pattern of more activity
  20     reported through the register than through HES. The
  21     numbers of deaths are actually rather similar, of the
  22     two different mechanisms.
  23        One part of the explanation for the
  24     over-reporting, as I have already mentioned, is that for
  25     the UK register there is no upper age limit, whereas the

   1     HES analysis was restricted to 15, but obviously that is
   2     not a problem (we were looking at under 1s) that we
   3     should be getting similar activity. That is not what is
   4     being observed.
   5        If we turn now to look at the South West register,
   6     this was specific to Bristol. One of the major
   7     strengths of that register is that the records related
   8     to individual children. We were not looking at
   9     admissions, procedures or episodes. There is none of
  10     this possible worry over double-counting. The register
  11     was looking at children and following them through time,
  12     maybe reporting multiple operations. So intrinsically,
  13     it has the possibility to give good data with far less
  14     ambiguity to do with possible double-counting, although
  15     again, it is very likely to be under-reporting mortality
  16     because there were no systematic procedures to follow up
  17     patients once they were discharged.
  18        If we could look at page 50, please, of my report
  19     [INQ 14/50] this is a comparison between the UK register
  20     and the South West register. I have done this according
  21     to the consensus groups that we have already heard about
  22     in quite a bit of detail.
  23        Looked at sort of in the whole, just looking at
  24     the sort of volume of activity being reported according
  25     to the South West register and according to the national

   1     register, there was actually pretty good agreement.
   2        Here I am looking at the fine detail and obviously
   3     the agreement is far from perfect. There are a number
   4     of the consensus groups where there is reasonable
   5     agreement, but there are others where there are striking
   6     discrepancies. One of the areas where there is
   7     particular interest is obviously to do with the switch
   8     procedures, the G2 was the earlier, the intra-atrial
   9     operation and the G3 was the switches. You can see
  10     there is almost a complete discordance there.
  11        This was a pattern that came out in quite a lot of
  12     our comparisons, so we went on to look at this in much
  13     more detail.
  14        If we could turn to page 51, please, this will
  15     need to be turned on its side. This is a very busy
  16     table with a lot of information in it, so I will try and
  17     take you through it slowly, because I think it shows
  18     quite an important caveat about the consensus groupings,
  19     especially in relation to the UK register.
  20        If we start with the South West register, what we
  21     see -- these are, if you want, the old-fashioned, the
  22     Mustard, the Senning procedures, and we can see that
  23     from 1984 onwards, the numbers are reasonably
  24     consistent. We have the numbers here with the number of
  25     deaths in brackets, so the numbers of deaths are small,

   1     but suddenly it seems to go out of fashion and the
   2     numbers drop off quite dramatically. As that is
   3     happening, the number of switches is gradually taking
   4     off.
   5        So we can see that the Mustard, the Senning
   6     procedure that was the appropriate way to tackle
   7     transposition of the great arteries in the mid-1980s
   8     became the switch operation. So we are seeing a change
   9     in practice.
  10        If we look, for instance, at the coded clinical
  11     records, we see a very similar, very consistent
  12     pattern. The numbers are slightly down relative to the
  13     South West register, but we see this same pattern, the
  14     Senning, the Mustards, dropping off, being replaced by
  15     switches and similarly in the surgeons log, the older
  16     operation going out of fashion to be replaced by
  17     switches.
  18        All three sources are showing the relatively high
  19     number of deaths that go with the switches.
  20        If we look at the Cardiac Register, we really do
  21     not see anything remotely like that. There seems to be
  22     no activity to speak of under the column that was meant
  23     to be the Sennings, the Mustards, and it looks as if
  24     switches have been going on right from the start. The
  25     problem there is that the national register was based on

   1     diagnoses rather than operations. We tried to tease
   2     these out by saying that the Mustard and Senning was
   3     a palliative operation for the TGA and the switch was
   4     the definitive, the corrective operation, but that
   5     clearly was not the perception. Clearly, at the time
   6     these data were being reported, the Senning and the
   7     Mustard was regarded as the curative procedure.
   8        So we have completely lost that distinction with
   9     the UK register, because we have diagnoses and not
  10     procedures.
  11        If you were to lump those two groups together, you
  12     get the children with transposition of the great
  13     arteries, and the figures become remarkably consistent,
  14     but we have lost that distinction between the different
  15     operative approaches.
  16        So that is a limitation we have to be aware of.
  17     It is a problem in getting the UK data to map directly
  18     on to the other data sources so we can compare like with
  19     like.
  20        If, for argument's sake, the UK register showed
  21     that certain procedures had an excess mortality in
  22     Bristol, those procedures we would not necessarily
  23     expect to match up with problem areas in HES, because we
  24     are not quite comparing like with like.
  25        If I can try and momentarily regroup and say what

   1     does this tell us about data quality, the first thing,
   2     a priori, we would not expect the register to reveal
   3     reliable data and in particular, there is a real
   4     possibility of mortality being recorded systematically
   5     differently between different centres. But if we go on
   6     from there and look at the outcomes in the different
   7     centres, and if we could start, maybe, on page 54 of my
   8     report, again, that will need to flip around
   9     [INQ 14/54].
  10        I would be the first to say this is a very
  11     simplistic way of looking at these data. What I have
  12     done here is to look at the activity in Bristol and
  13     compare it with all the activity outside Bristol, just
  14     pooling it together as if there were one centre, i.e.
  15     not Bristol.
  16        This completely masks any variability from any
  17     centre outside Bristol. This rightly is called the
  18     "naive analysis" in Dr Spiegelhalter's report. I hope
  19     it does not reflect my naivety that I am showing you
  20     this because I think it is helpful, but it is not the
  21     definitive way to look at this data. What I am saying
  22     will be very much superseded by what Dr Spiegelhalter
  23     will tell you later. There are still some very striking
  24     patterns.
  25        If we look, for instance, here the open surgery in

   1     the children aged under 1, the mortality rate at Bristol
   2     over the Inquiry period is sort of remarkably stable at
   3     around 25 per cent, whereas outside Bristol, it starts
   4     at a similar figure, but almost halves over the Inquiry
   5     period. So there seems to be a pattern outside Bristol
   6     for outcomes to improve, but that is not seen in
   7     Bristol. There are some odds ratios and confidence
   8     intervals here essentially saying that that difference
   9     is more than can be explained by chance. Whatever the
  10     explanation is, chance is not a good explanation.
  11        If we look at the individuals aged over 1, the
  12     mortality rates are lower, but we still see a similar
  13     pattern with rates in Bristol that are relatively high
  14     against a national pattern of falling mortalities. The
  15     numbers of deaths for children or for adults undergoing
  16     closed procedures are much smaller, so it is difficult
  17     to say anything definitive there, but even here, the
  18     point estimate, the mortality rates, the observed rates,
  19     are slightly higher in Bristol, but the numbers there
  20     are really too small to make very much of that.
  21        If we could move on to page 55, please,
  22     [INQ 14/55], and if we could page down just a little,
  23     this is lumping everything together over time, so I am
  24     running from 1985 right up to the financial year
  25     1994/95, but picking out the children aged under 1.

   1     This is really telling us the same story as we have seen
   2     before. For the open surgery, a substantially higher
   3     mortality rate in Bristol than elsewhere, and the same
   4     trend amongst the closed procedures.
   5        I have already explained the difficulty of looking
   6     at the consensus groups with the Bristol detail, but
   7     there is still a reasonable consensus. The particular
   8     areas where we are seeing an excess are groups 4, 5 and
   9     6. That was the TAPVD, the AVSD and closure of ASD.
  10     These are actually the same areas of concern that seem
  11     to be cropping up in the other data sources.
  12        So in spite of all the limitations I have been
  13     talking about, there is a remarkable consistency of the
  14     sort of signal that is coming through against the noise.
  15        If we are to move on to the next page, page 56,
  16     again, if we could page down, this is now the same
  17     information but for individuals aged over 1 year, and
  18     the mortality rates are much lower in that age group,
  19     but again, we see this pattern of a mortality rate in
  20     Bristol that is at least 50 per cent higher, whether we
  21     are looking at the open or the closed surgery. The
  22     numbers with the closed surgery are too low to draw firm
  23     conclusions, but the open surgery, again, this is too
  24     big a difference to be explained by chance. There is
  25     not a huge consistency now in the areas where the excess

   1     seems to be occurring, but one area is the Fallot and,
   2     again, group 5, the AVSD. That is coming out again,
   3     just as we saw with the earlier data.
   4        Those are very much descriptive, very much "naive"
   5     ways of looking at the data, but I think they are
   6     informative.
   7        If I could move on to the next page, 57, this is
   8     an analysis which I do not think I could possibly
   9     describe as naive, because it is based on a methodology
  10     devised and published by Dr Spiegelhalter!
  11        This is the ways of ranking the different
  12     centres. I want to focus on two lines here. This is
  13     looking at the open surgery in the children aged under
  14     a year, taking the whole time period for which the UK
  15     data are available. We can see that Bristol is ranked
  16     12 out of the 12, but the confidence interval for that
  17     ranking actually spans from 10 up to 12, so they are
  18     certainly in the lower quarter of the distribution, but
  19     even with these data, there is no firm evidence that
  20     their mortality rate is lower than all other centres.
  21        If we are to look at the open surgery --
  22   THE CHAIRMAN: Interrupting you just for a minute, do you
  23     mean higher rather than lower?
  24   MR LANGSTAFF: The mortality rate being higher is what you
  25     meant to say, I think, rather than lower?

   1   A. Yes, apologies. If we look at the open surgery in the
   2     individuals aged over a year, out of the 12 centres,
   3     Bristol comes out as being 11th out of 12, and in fact,
   4     the confidence interval is from 8 to 11, so it actually
   5     excludes the possibility of Bristol being 12th out of
   6     12. This is highlighting the Harefield problem that has
   7     already been discussed.
   8        So although there is fairly strong evidence that
   9     the reported mortality rates from Bristol are higher
  10     than national norms, they are not necessarily an extreme
  11     outlier on the basis of this analysis.
  12        If I try and pull things together now in terms of
  13     my interpretation of what we have been looking at,
  14     I think the first thing we have to say is that if you
  15     are simply to take the data from the UK register on face
  16     value, then there is very strong evidence that the
  17     mortality rate at Bristol is higher than the norm
  18     elsewhere. There are at least three explanations why
  19     that might be the case. It could genuinely be that the
  20     clinical care delivered at Bristol was poorer than
  21     anywhere else. But it could indicate systematic
  22     differences in the way the data were collected and
  23     reported, or it could indicate systematic differences in
  24     case mix. Maybe the children being operated on at
  25     Bristol were systematically more ill than elsewhere.

   1        There are a number of holes, I think, in the
   2     data. In my own opinion, by far the most serious one
   3     relates to the reporting of mortality. I think there
   4     could very well be systematic differences, but
   5     fortunately, that is the hole that is most easily
   6     addressed. There are national registries of mortality,
   7     and these data must be linked to get rid of that as an
   8     explanation.
   9        It might explain part of the difference, possibly
  10     not all. We need to know how much of the difference can
  11     be explained in that way.
  12        Another concern in my mind is this discrepancy
  13     between the activity reported by HES and that reported
  14     by the Register and by the South West Congenital Heart
  15     Register as well. I do not know whether HES is
  16     under-reporting or whether the other sources are over
  17     reporting. The way that the South West Register was
  18     developed, it seems very unlikely that it would
  19     over-report, because it is based on children, so that
  20     raises the question in my mind, is it HES that is
  21     under-reporting, maybe through quite substantial
  22     miscoding? Maybe we are not picking up children who
  23     have been through and been operated upon. I think that
  24     needs further work.
  25        The South West Register would be a good starting

   1     point, because the children there, they are actually
   2     named, they have dates of birth, they are easily
   3     traceable and they could be linked to other sources to
   4     see if there is a systematic problem with HES, at least
   5     for the Bristol data.
   6        The final problem we have to wrestle with is case
   7     mix. I think all the statisticians working on the data
   8     agree that we do not have a good handle on case mix.
   9     I think all I can say in mitigation is all the
  10     experience I have in looking at adjustments for case mix
  11     in lots of medical contexts is that they tend to be
  12     subtle. We are looking here for observed differences of
  13     maybe 50 per cent or even 100 per cent and in general,
  14     case mix adjustments do not lead to, you know, effects
  15     of that size. So I do not believe that case mix is
  16     a complete explanation of what we are observing here.
  17     It might explain part of it, but I think that there is
  18     a need to look further to try and get a handle on case
  19     mix.
  20   THE CHAIRMAN: Thank you very much indeed. Mr Langstaff?
  21   MR LANGSTAFF: Does it follow from those last remarks that
  22     your preferred explanations of the perceived difference
  23     are either that it is a question of data collection
  24     differing, or there is some other explanation, other
  25     than case mix, and other than chance, and other than

   1     data collection, for the apparent difference to
   2     Bristol's disadvantage in the data that you have
   3     collected?
   4   A. My own view, which is very much subjective, not
   5     evidence-based, is that we are probably over-estimating
   6     the extent of the excess mortality. I think the extent
   7     is such that it is probably not explained by an artefact
   8     of data collection or case mix. A two-fold difference,
   9     and not only that, but one where there are systematic
  10     patterns. The fact that mortality outside Bristol fell
  11     systematically over time, but in Bristol it did not, it
  12     is difficult to think of a mechanism, a systematic flaw
  13     in the data recording that would generate that effect
  14     spuriously.
  15        So I believe that there is a real difference, but
  16     probably, the magnitude of that difference is being
  17     influenced by various biases, some of which we could get
  18     a handle on; others of which we can never quantify.
  19   Q. One of the handles that you are recommending, I think
  20     you agree with Dr Aylin, is that we need to have some
  21     idea of deaths?
  22   A. Yes. I think that is absolutely mandatory, that that is
  23     looked at.
  24   Q. Can I ask you to go to a table you have not shown us,
  25     which is on page 52, table 15?

   1   THE CHAIRMAN: Mr Langstaff, while that is being found, can
   2     I just again explore an answer? You said "my own view,
   3     which was very much subjective, and not evidence-based,
   4     is that we are probably over-estimating the extent of
   5     the excess mortality."
   6        You go on then to explain why it may it not be due
   7     to an artefact, and so on.
   8        Do you mean we are probably not over-estimating?
   9   A. I think we are over-estimating. I believe --
  10   Q. Notwithstanding what you then say?
  11   A. Notwithstanding that. There are a lot of indications
  12     that Bristol was meticulous in collecting data, and the
  13     whole problem in this area is that to be meticulous one
  14     is penalised.
  15   MR LANGSTAFF: Do I take it from what then followed that
  16     although there is a degree of over-estimation,
  17     nonetheless, one is left with a real difference?
  18   A. That is what I believe. That is my interpretation of
  19     the data.
  20   Q. Table 15: can we go down to the very bottom, death
  21     rates? You here are looking at five different data
  22     sources as they appeared to you. Each of these data
  23     sources would be collected in the various different ways
  24     you have described, subject to, depending on who was
  25     collecting it, different systematic problems?

   1   A. Yes.
   2   Q. If one looks at the one line in which all five report
   3     death rates, albeit that they have different levels of
   4     activity recorded, can you say, as an expert, whether
   5     those rates are dissimilar -- after all, there may be
   6     something of a 20 per cent difference between UKCSR and
   7     HES -- or whether they are surprisingly similar?
   8   A. I think they are strikingly similar.
   9   Q. To what extent, if at all, does that answer any problems
  10     that you may have in terms of your worries about the
  11     difficulty of data collection for any one source?
  12   A. I think there is a very important issue there, in that
  13     although we are looking at five sources, we are not
  14     looking at five independent sources. If, for argument's
  15     sake, the culture at Bristol is that one is fastidious
  16     about following up patients so that all deaths are
  17     recorded, then every data collection system in Bristol
  18     is going to have good mortality, whereas, say in
  19     centre X there is a culture that "we get rid of the
  20     patients and we are not interested once they are out of
  21     the care of the surgeons", then every single data source
  22     from that centre will tend to report low mortality.
  23        So it is the same core of people who are
  24     collecting these data from all the sources. There are
  25     different individuals involved, there are people coding

   1     data differently and so on, but fundamentally, it is the
   2     same children of which we are collecting data, and if
   3     there are good data available at a centre, all the
   4     sources will tend to reflect that, or, if there are poor
   5     data, all the sources will tend to reflect that.
   6        So the reinforcement could be illusory to some
   7     extent.
   8   Q. So the secretary of the department or surgeon who sends
   9     off the returns to the UKCSR will be likely to have the
  10     same approach in your experience as the administrative
  11     clerk who looks at the HES data and makes the data
  12     entry, PAS is probably similar to HES, and they in turn
  13     are similar to the information to be gained from the
  14     case notes themselves? That is the thesis, is it?
  15   A. Yes --
  16   THE CHAIRMAN: I did not think that was the thesis.
  17     I thought the thesis was, if, for example, at X you have
  18     the clerks who are not part of the culture who are
  19     over-reporting, or you have staff who move patients on
  20     rather than report them as mortality statistics,
  21     compared with an institution where that does not happen,
  22     then that will taint the data throughout?
  23   A. Yes. I mean, if we say for argument's sake that the
  24     cardiac surgeons see every patient five weeks
  25     post-operatively, you could say a unit might have that

   1     as a policy. Then that unit is going to be remarkably
   2     good at picking up 30-day mortality. If there is no
   3     systematic follow-up, or only appropriate patients are
   4     followed up, then they could miss 30-day deaths.
   5   THE CHAIRMAN: It may be that there is no difference between
   6     Mr Langstaff and myself, save that I misunderstood his
   7     intervention. I apologise both to you and to him.
   8   MR LANGSTAFF: That is a good note, I think, to end your
   9     evidence on, unless there are further questions from the
  10     Panel?
  11   THE CHAIRMAN: Mrs Maclean?
  12            Examined by THE PANEL:
  13   MRS MACLEAN: It is really following on from your points
  14     about meticulous record-keeping and its potential
  15     impact. We have been addressing ourselves to the
  16     thought that there may be an impact following on from
  17     miscoding as open or closed. I would be interested in
  18     your comments on the possible consequences. For
  19     example, if a procedure is miscoded as closed, then the
  20     effect on the death rate for open procedures would be to
  21     reduce it, and similarly if a procedure was miscoded as
  22     open, the effect would go in the same direction.
  23        So again, is this an example of the kind of
  24     penalising effect of meticulous coding? I would be
  25     interested in your comments on our thoughts.

   1   A. Yes, certainly, any errors of coding tend to blunt
   2     distinctions and groups are brought together, so as you
   3     say, the open cases would appear to have lower
   4     mortality; the closed cases would appear to have higher
   5     mortality. That is an example.
   6        I was thinking much more of, you know, the figure
   7     with which deaths are sought, complications are sought,
   8     these sorts of issues. If one is scrupulous about
   9     recording complications, then your unit will have a much
  10     higher complication rate than a unit that does not do it
  11     with the same rigour.
  12   MRS MACLEAN: Thank you.
  13   THE CHAIRMAN: There are no further questions from the
  14     Panel.
  15   MR LANGSTAFF: Sir, I wonder if there may be a very short
  16     break, perhaps no more than five minutes? I think it is
  17     principally for the convenience of the stenographers,
  18     before we proceed with the last session of the
  19     afternoon, in which Dr Spiegelhalter will present his
  20     figures.
  21   THE CHAIRMAN: Yes. Shall we take a short break of about
  22     five minutes? I understand that some of the witnesses
  23     do have to get away later in the day, so let us make it
  24     a short break of five minutes.
  25   (3.25 pm)

   1               (A short break)
   2   (3.30 pm)
   3   MR LANGSTAFF: Dr Spiegelhalter, would you stand to take the
   4     oath, please?
   5          DR DAVID SPIEGELHALTER (AFFIRMED):
   6            Examined by MR LANGSTAFF:
   7   Q. Dr Spiegelhalter, we have heard from you before in this
   8     Inquiry so I only need, I think, ask you: is the report
   9     which is shown on your screen the first page of a report
  10     which you have produced for us?
  11   A. Yes.
  12   Q. Of which the tables and figures, INQ 15/102, is the end?
  13   A. Yes.
  14   Q. What you have done is synthesised the statistical
  15     sources we have been exploring today and we explored
  16     last July, in order to come to some overall statistical
  17     view at this stage of this Inquiry's investigation into
  18     the adequacy of care in Bristol?
  19   A. Yes. If I could try to put that in context, if I could
  20     have the Inquiry document INQ 15/104, please, this
  21     briefly summarises the statistical strategy that was
  22     laid out last July. It highlights Phase II, the
  23     exploratory investigation of available data sources,
  24     which is what we are engaged in at the moment. I put
  25     this up partly to emphasise that at this stage we can

   1     neither confirm any apparent divergencies, as we would
   2     call them in performance, that may be found at this
   3     stage, and in particular, we are not seeking to explain
   4     these away. This will be the subject of further
   5     investigation.
   6        If I could have 106 [INQ 15/106], this attempts to
   7     protect myself slightly against the acknowledged
   8     limitations of the synthesising exercise that I have
   9     been engaged in.
  10        First of all, I should say, we are incredibly
  11     grateful to the analyst teams who have been producing
  12     all the data. It has been a pleasure to work together
  13     on this difficult problem, but there are definite
  14     limitations. I am only going to be talking today about
  15     short-term mortality and the whole issue of morbidity
  16     and long-term complications will not be dealt with.
  17     I think we fully acknowledge that mortality is an
  18     inadequate measure of performance for comparison.
  19        As we have already heard today, we have imperfect
  20     data sources that we are attempting to learn from, and
  21     risk stratification, although we have been trying to do
  22     our best by breaking children up into age groups,
  23     stratified by type of operation and by period or epoch
  24     of when the operation took place, it is still very
  25     limited. We acknowledge that further clinical

   1     stratification would be an advantage.
   2        We are also careful to avoid at this stage saying
   3     anything about what might have been known at the time of
   4     the operations. We are acting completely in hindsight,
   5     trying to work out what actually went on and we will not
   6     be covering at all what could have been known at the
   7     time from the sources of information.
   8        Again to emphasise at this stage, we are not
   9     giving any causal reasons for any differences that are
  10     found.
  11   Q. It is sometimes said that a statistical survey is best
  12     done prospectively rather than retrospectively. How far
  13     is that then true of a situation such as this?
  14   A. I think in the situation, even more than any other
  15     situation, that is true, and I think when we look at all
  16     the data sources, I think we can see that having six
  17     data sources essentially covering much the same issue
  18     shows a certain redundancy and that if good information
  19     systems have been set up in the first place, we would
  20     not have to try to do this exercise now.
  21        Again, that is with the value of hindsight.
  22        If I could jump to page 45, a table in my report,
  23     although it is rather dense, that tries to summarise --
  24     if it is readable, I would like to talk about the first
  25     couple of lines in that. It tries to summarise very

   1     briefly the six sources of information that we have
   2     heard about already today and there is no point in my
   3     repeating what has been said.
   4        If we look at the top two lines if I can just
   5     point with the pen, we can see that the purposes of the
   6     different systems vary enormously from PAS which is an
   7     administration system that feeds returns to the national
   8     HES system, to the code of clinical records, which are
   9     medical records completed by medical personnel, to the
  10     surgeons' logs which were used for their own personal
  11     record for audit and for constructing returns to the
  12     Cardiac Register, essentially owned by the surgeons, to
  13     the South West Congenital Heart Register, which was for
  14     epidemiological information and clinical backup,
  15     essentially owned by the cardiologists. The Hospital
  16     Episode Statistics, the national administration system,
  17     not a clinical system, now in fact being used by the
  18     Department of Health as a basis for its own high-level
  19     and clinical performance indicators.
  20        That is derived from Patient Administration
  21     Systems in various hospitals.
  22        Finally, the Cardiac Register, which was derived
  23     from a professional body for comparative but anonymous
  24     audit and that was essentially owned by the surgical
  25     team in Bristol.

   1        The rest of the table shows the fact that these
   2     different systems had different definitions of activity,
   3     different times at which they are available, different
   4     possibilities for different ages.
   5        Perhaps I draw attention to the comment at the
   6     bottom: none of these six sources have established
   7     validation procedures or ability to have systematic
   8     follow-up, even as people have mentioned a couple of
   9     times already today, even to record deaths.
  10        That is just a summary showing diversity of
  11     sources, and I suppose I should say, quite a statistical
  12     comment, none of these sources are the kind of data that
  13     normally statisticians would be very happy doing their
  14     research on, or even making a statement about at all.
  15   Q. May I then ask why you have done it?
  16   A. We were requested to do so by the Inquiry team, who are
  17     very persuasive.
  18   Q. But did you think it was a valid exercise to attempt
  19     it?
  20   A. Given that these are the only available sources of data,
  21     I think we all went into it with great trepidation, and
  22     frankly, as some people have mentioned, with
  23     considerable expectation that these would come up with
  24     very different answers since none of these systems would
  25     normally be considered reliable enough for making secure

   1     statements about mortality rates.
   2   Q. Do you still, having done the analyses, have that same
   3     view, jumping ahead, perhaps?
   4   A. Jumping ahead, I would say that I, like others, have
   5     been surprised certainly in terms of the fact that for
   6     Bristol we have all these sources, have been surprised
   7     at the degree of agreement between them.
   8   Q. Has that changed your view as to the degree of reliance
   9     that might be placed on the degree of reliability of
  10     these sources when combined?
  11   A. Yes. If there had been huge disagreement between these
  12     sources, it would make any generalisation from them,
  13     even if one source showed divergent performance, rather
  14     difficult to feel confident about. We are looking for
  15     corroborative evidence. As Professor Murray mentioned,
  16     we should not assume the systems are totally
  17     independent. There are obviously connections between
  18     them. The ethos of good data collection will obviously
  19     influence them all in common.
  20        If we go to page 48 of my report, this is a rather
  21     dense table. Could we just concentrate on the first
  22     part? Could we go back to the table?
  23   THE CHAIRMAN: I think there is a general premise that only
  24     one of you can touch it. Tony will do it at the back.
  25   A. If we can get back to the table, if we concentrate on

   1     the first area of it, where it says "number of
   2     admissions", but could we include the left-hand column
   3     as well, that has the type of operation, the G1, and so
   4     on.
   5        The aim of this table is to compare all the six
   6     sources in the third epoch, that is when they are all
   7     available, that is 1991 to March 1995 -- maybe it is
   8     readable in its current form, so perhaps we should leave
   9     it as it is, then I can try to highlight things.
  10        First of all, I am going to look at this area
  11     here. We are looking at the 13 types of operation and
  12     procedure groups and the open and closed. This is just
  13     the number of admissions or operations, as some of the
  14     data sources are recording. These are the numbers. So
  15     the Fallot type operations, these are just 54 from PAS,
  16     56 from the clinical records, 63 from the surgeons'
  17     logs, and so on.
  18        This kind of data has been presented already
  19     today.
  20        I produced this in a bit of magical statistics at
  21     the end, a CV, a co-efficient of variation, which is
  22     simply a measure of the degree of agreement between
  23     those numbers. Technically it is the standard deviation
  24     divided by the mean. It is a measure of how well those
  25     numbers agree. Values of less than 20 per cent would

   1     generally be considered as reasonable agreement. Values
   2     less than 10 would be considered fairly good agreement.
   3        This enables us quite quickly to run our eye down
   4     and see where the agreement seems to be quite good.
   5        So in terms of number of admissions, there is
   6     quite good agreement on Fallots, very poor agreement on
   7     the TGAs, because we have already heard that the Cardiac
   8     Register's coding of group 2 and group 3 is full of
   9     problems.
  10        A fairly good agreement on TAPVDs and on AVSDs and
  11     looking down further, really quite good agreement on the
  12     number of open operations, not perfect agreement, but
  13     not too bad.
  14   Q. That falls into your better than 10?
  15   A. Yes. If we can jump to the area of most interest, the
  16     mortality rates, we can look across again and see within
  17     Fallot operations the agreement in terms of the
  18     mortality rates between all six sources is really quite
  19     good. It is not good on say the switches, group 3,
  20     because the Cardiac Register is messed up. If we took
  21     that out, the agreement is not so bad at all. It is not
  22     too bad on TAPVDs and on AVSDs and in terms of the
  23     mortality rate for open surgery, it is extremely good.
  24     I actually use the word "extraordinary" agreement
  25     between these different sources.

   1   Q. You used two superlatives there, "extremely" and
   2     "extraordinary"?
   3   A. I think it is surprising, given our initial scepticism
   4     about these sources of position.
   5   Q. One can see, looking at the figures, on five data sets
   6     there is a range of 13 or 14?
   7   A. Yes. Some areas the agreement is not so good. There
   8     are problems in coding clearly that have existed in the
   9     Fontans and surgeons' logs. There have been some
  10     problems. For the truncus, the numbers are so small
  11     even though they all come up with fairly high mortality
  12     rates, the agreement is not wonderful.
  13        I suppose I would like to call attention to the
  14     agreement on the open operations and the Fallots, the
  15     TAPVDs, the AVSDs, because it is actually where quite
  16     a lot of attention is going to focus.
  17        There are some more tables that compare the other
  18     epochs in my report, but I think that gives us some
  19     confidence in proceeding with an analysis of the
  20     national data on the basis of the Cardiac Register and
  21     HES, with the known limitations in those data sets.
  22        If I can go to page 110 which is a summary, really
  23     based on Professor Murray's presentation just now on the
  24     HES and CSR, when compared on the whole national data,
  25     not just on Bristol.

   1        To repeat what Professor Murray said, there is
   2     more activity and deaths tend to be recorded in Cardiac
   3     Register than in HES. It is not clear whether that is
   4     under-reporting of HES or under-reporting of the Cardiac
   5     Register.
   6        However, with some notable exceptions where there
   7     are coding problems, the mortality rates are reasonably
   8     similar.
   9        Similarly, from centre to centre, the reasonably
  10     consistent pattern and level of agreement between the
  11     Cardiac Register and HES and Bristol is in the middle of
  12     that. Professor Murray pointed out 73 seemed to have
  13     very odd reporting on the Cardiac Register. Bristol
  14     seems to be unremarkable in its degree of agreement.
  15        The agreement between individual procedure groups
  16     is not always so good, but really, that is hardly
  17     surprising, given that the way in which these 13
  18     procedure groups have been mapped onto is so different
  19     in the two sources.
  20        As we have seen, the Cardiac Register has been an
  21     attempt to map from the diagnostic categories onto the
  22     13 groups, and from HES it has had to work through
  23     a two-stage system of the ops codes and being mapped
  24     onto the 13 groups.
  25   Q. So is a simple way to understand that to say the

   1     distinction between an open operation and a closed one
   2     is comparatively obvious and if one is faced with that
   3     distinction across the whole range of cases done in
   4     a centre, taking any difficulty there may be in
   5     establishing mortality, nonetheless, one is looking at
   6     a rate which is much less variable than rates for
   7     individual operations about which there may be
   8     disagreement, a question of when one you code,
   9     a question of which code applies, which subcode applies,
  10     and so on?
  11   A. Yes and there will be more chance of disagreement
  12     because the numbers are small on the individual
  13     procedure groups.
  14        If I can now jump to page 51 of my report, this
  15     essentially puts in graphical form the data that
  16     Professor Murray showed in one of his slides. This is
  17     really a descriptive analysis. There is no, for
  18     instance, statistical inference going on here, but it
  19     enables us to compare what HES and the Cardiac Register
  20     is saying about open operations on children aged less
  21     than 1 year old, compared with in the three epochs.
  22        The fourth one, which is just the 9 months from
  23     April 1995 to December 1995. For the Cardiac Register,
  24     since it comes in units of a year, this epoch actually
  25     includes up to March 1996, which is strictly speaking

   1     outside the Inquiry's period, but you have to include
   2     that.
   3        This demonstrates, I think, what Professor Murray
   4     said in his presentation, that while back in epoch 1,
   5     which is 1985 to 1987, for CSR, the mortality rates
   6     between Bristol and the rest of the country really are
   7     quite simple. This is what has been reported to the
   8     Cardiac Register since then, in the rest of the country
   9     is a steady decline in mortality. What apparently has
  10     happened in Bristol -- it does seem rather
  11     superficial -- is that this decline has not occurred, it
  12     has stayed at a fairly constant level, showing an
  13     increasing divergence with the rest of the country.
  14        What is quite nice here in being able to put both
  15     the Cardiac Register data and the HES data together is
  16     that in epoch 3 and epoch 4 we can see that really there
  17     is quite good agreement between these two sources, first
  18     of all on what was happening in the rest of the country
  19     in epoch 3 and epoch 4, and here this is the HES and
  20     Cardiac Register in Bristol, fairly good agreement with
  21     what was going on in Bristol in epoch 3 and epoch 4.
  22        The rather simplistic analysis we ought to be
  23     cautious about is that between epoch 3 and epoch 4,
  24     after March 1995, there was a decline in mortality.
  25     I would like to come back to that in a moment.

   1        If I could go on to 7.2.2, at the bottom of the
   2     page, which shows the picture in children aged more than
   3     1 year old, we can see again this is now with actual
   4     lower mortality rate, but a steady decline in the rest
   5     of the country, and again, while Bristol appears to be
   6     rather typical in the early part of the period of the
   7     Inquiry, than in the intermediate time, although to
   8     a slightly lesser extent than in the younger children,
   9     there has been a divergence of performance which has
  10     declined in epoch 4.
  11        I would like to point out the level of agreement
  12     between the two data sources between what was going on
  13     in the rest of the country and what was going on in
  14     Bristol.
  15        There has been caution expressed about
  16     interpreting this apparent decline into epoch 4, because
  17     as Professor Evans mentioned, there is a possibility
  18     that the pattern of operations changed and I have done
  19     a little bit of analysis that is not in my report but
  20     will now be available.
  21        If we look at page 113, if we can get all of that
  22     on the screen at once, what this does is show, in the
  23     epoch 3, using the HES data, what the profile of
  24     operations was in terms of the number and in terms of
  25     the survival rate. Cases that unfortunately died are

   1     coloured black and survivors are coloured grey. We can
   2     see immediately which were the more common operations,
   3     the fact that the high mortality rates are being
   4     observed under switches, TAPVD, AVSD and truncus
   5     operations in particular, which are also very much the
   6     rarer operations.
   7        If we look now at what was going on, just in the
   8     9 months after April 1995, clearly the scale is a lot
   9     smaller and so there is more variability attached to
  10     these numbers, but basically, the profile, in terms of
  11     the type of surgery being carried out, is broadly
  12     similar except if we look in these particular areas down
  13     here. There were no TAPVD operations recorded, only
  14     a couple of switches and one or two truncuses, so
  15     although there is a very low mortality rate, there is
  16     definitely a decline in the amount of the more severe
  17     high risk surgery being carried out.
  18        If we jump to 115, we can see whether the Cardiac
  19     Register is telling the same story or not, if we could
  20     blow that up.
  21        This is the Cardiac Register. Again, we see an
  22     agreement between the Cardiac Register and what has been
  23     reported to the Cardiac Register and HES, we see a very
  24     similar picture. The profile is rather similar, except
  25     that we can see a big decline in the number of switches,

   1     the TAPVD, the proportion of switches, the TAPVDs none,
   2     the AVSDs being carried out.
   3        So again there is a low mortality rate, but the
   4     high risk operations are not being done in that period.
   5        So my feeling is, although there is an apparent
   6     strong decline after April 1995, I would not be happy to
   7     make absolutely firm conclusions on the basis of that,
   8     unless the period after April 1995 could be extended.
   9     If we could look at data which would now be outside the
  10     Inquiry's remit, of course, but I would not be happy to
  11     compare the mortality rates in this profile unless these
  12     numbers were considerably larger, because it is clear
  13     that the type of operations over that period did change.
  14        I suppose I am expressing considerable caution
  15     about over-interpreting the decline after April 1995.
  16   Q. But you suggest that it might be one way of assessing
  17     what happened before 1995 and before, to discover what
  18     has happened in 1996/97?
  19   A. I think if that was a straightforward exercise, it would
  20     be valuable to increase the sample size in that period,
  21     because that is telling one something about the
  22     institutional factors and about the population that
  23     Bristol is serving, which presumably will not have
  24     changed over these periods.
  25        If I could go on now to what -- these are really

   1     just descriptive analyses. Now we get more tricky. If
   2     we go to page 108 which is a summary taken from my
   3     report of the strategy that we carried out, you have
   4     heard a considerable amount about this already, but I am
   5     afraid I am going to talk about it yet again.
   6        The basic idea is to try to investigate whether
   7     Bristol could be considered as divergent from the
   8     remainder of the units in the country: in which case, in
   9     which regard?
  10        Our basic strategy has been to remove Bristol from
  11     the database. Can I draw on this?
  12   Q. Yes.
  13   A. Remove Bristol from the database, and then analyse what
  14     was happening in the remainder of the centres. In
  15     particular, calculate the activity and mortality rates
  16     in the other centres, and then, within each stratum,
  17     which just means a particular set of patients with
  18     a particular operative procedure, a particular age
  19     group, particular epoch of operations, so this is the
  20     subgroup we want to look at individually, work out what
  21     was going on in the remaining centres, and essentially,
  22     characterise what would be considered a typical
  23     performance and the variability around that performance.
  24   Q. We may be used to the word "average". What is the
  25     difference between "average" and "typical" in this

   1     context?
   2   A. I have avoided the word "average" because you then would
   3     tend to think of perhaps an average patient as if there
   4     was a great homogenous pool of patients out there. By
   5     using "typical" it is much more thinking of the fact
   6     that there are 11 other centres, we do not expect them
   7     to be exactly the same, they are bound to differ in ways
   8     we cannot measure, even if we could adjust for case mix,
   9     so we are always going to expect some variability. What
  10     we want to know is whether Bristol could be considered
  11     as typical of the sort of variability that inevitably
  12     exists between centres.
  13        So what we can do, then, is to obtain an interval,
  14     a confidence interval, an uncertainty interval, for what
  15     would be the true underlying performance of a typical
  16     centre, that is almost as if a centre had been drawn at
  17     random from the other 11, and compare that with what
  18     appears to be the true performance in Bristol.
  19   Q. And again, true performance is not the actual observed
  20     performance; it is an idea that there is, underlying
  21     that, some true figure from which each year there may be
  22     a random departure?
  23   A. Exactly. It is a slightly hypothetical idea. It is
  24     almost as, if they were to do a million operations, what
  25     would be the eventual long-term mortality rate?

   1     Obviously, that is not realistic, but we can think of
   2     it, to use the rather unfortunate coin-tossing analogy,
   3     if each operation is if you were tossing a coin, one
   4     would observe the theory of heads or tails but when
   5     trying to assess the bias of the coin, it is reasonable
   6     to think of what is the true likelihood that it will
   7     come up heads. We can do that with an interval
   8     elsewhere and in Bristol and compare those graphically.
   9     We will see those in a minute.
  10        Then we will get on to the next stage, which we
  11     have already heard about today, to do with this
  12     unfortunate term, excess number of deaths. At stage 5
  13     we can say that with Bristol's activity, were Bristol to
  14     be essentially representative of the centres in the rest
  15     of the country, were it to be essentially
  16     indistinguishable, how many deaths would we expect to
  17     occur? We do not know how many deaths would have
  18     occurred had Bristol been really similar to the other
  19     centres in the country so that is an unknown quantity,
  20     but we can make essentially a prediction of what we
  21     would expect to have occurred in terms of the number of
  22     deaths.
  23        Since we know how many deaths actually occurred,
  24     we can subtract from the observed the number that were
  25     actually expected to occur were Bristol typical and call

   1     that the excess deaths. We can call it the difference
   2     in deaths, but typically in statistics, something that
   3     can be derived from the expected would be called an
   4     excess. That excess could very well be called negative
   5     if in fact less deaths were observed than would have
   6     been expected were Bristol to be a typical centre.
   7        But since we have an interval on the number of
   8     excess deaths, we can calculate the probability that the
   9     true underlying excess, in other words, having an
  10     enormous number of operations, is actually greater than
  11     zero. These figures will give us some idea so we can
  12     say we are 99 per cent sure that really there was an
  13     excess mortality, in other words, there is only less
  14     than 1 per cent chance that were Bristol typical, we
  15     would have observed such an extreme number of deaths.
  16        So we are looking for figures like 95, 99 per cent
  17     certainty or confidence that there really is excess
  18     mortality.
  19        We can also do a ranking exercise where we see
  20     within that particular subgroup of patients where
  21     Bristol was, was it at the bottom, was it second to
  22     bottom or whatever, and rather than just quoting where
  23     it lay in the rank, we can give an interval around that,
  24     to say whether we are confident that Bristol was where
  25     it was in that range of the centres.

   1        Finally, what we have done is repeat this entire
   2     analysis for every centre in turn, done a totally
   3     symmetrical analysis, because we felt we would not be
   4     able to say anything about Bristol's degree of
   5     divergence unless we could also say something about the
   6     divergence of all the other centres, so we have repeated
   7     the entire analysis 12 times.
   8        That is why I am afraid my report is filled up
   9     with a large number of stodgy tables which I have tried
  10     to extract the main things from.
  11        If we could jump to a table which I could talk
  12     through, because I would like to go through these
  13     tables. There is one table for each procedure group.
  14     Since the conclusions really depend on the very specific
  15     procedure groups, apart from the open and closed
  16     categories, it would be useful to go through these in
  17     turn.
  18        If we could have page 68 up, this is starts off
  19     looking at tetralogy of Fallot. If we could blow that
  20     up a bit. I hope this is readable as it stands.
  21     Essentially this page is trying to summarise all the
  22     information in both the Cardiac Register and the HES
  23     database that we have available about tetralogy of
  24     Fallot, so that is why it is rather dense, in trying to
  25     put everything we can on one page. If I could write on

   1     this, to highlight some of this, to illustrate what
   2     I mean by analysis, this is data taken from 1984 to 1987
   3     from the Cardiac Register, on Fallot type operations
   4     from patients aged 1 to 15 years. First of all, we can
   5     just summarise what the mortality was in 11 other
   6     centres. That is 6 per cent, 24 deaths out of 404
   7     reported to the Cardiac Register.
   8        We can compare it in Bristol, they reported
   9     7 deaths out of 49 procedures, as 14 per cent. So it is
  10     over double the mortality rate.
  11        The little pictures after that, illustrate what we
  12     feel might be the true underlying mortality rate at
  13     Bristol, that is the solid line with the dot in the
  14     middle, which is round about 14 per cent but with quite
  15     a wide interval on each side and compare it with what we
  16     feel would be the mortality rate in a typical centre
  17     elsewhere in the country, which is round about 6 per
  18     cent but with quite a range as well. We are looking for
  19     divergence in those two intervals. If they do not
  20     overlap, then really that is pretty strong evidence we
  21     are not talking about Bristol -- it cannot be considered
  22     typical or representative of the other centres in the
  23     country. So we are looking for and we have a case here
  24     in the second epoch, 1988 to 1990, in the under 1 years,
  25     where there was a 10 per cent mortality in the rest of

   1     the country, but out of the two cases in Bristol, both
   2     unfortunately died and in that case, really, we have got
   3     quite a strong confidence that Bristol is not as
   4     a centre representative of those other centres, only
   5     based on two cases.
   6        The next column actually tries to quantify the
   7     degree of divergence between Bristol and the rest of the
   8     country by saying how many deaths there were in Bristol
   9     in excess of what would have been expected had Bristol
  10     been typical. I think we can see there that out of
  11     these 49 deaths, had the mortality rate been around
  12     6 per cent, the national rate, we would have expected,
  13     instead of seven deaths, about 3, less than 3 and
  14     a half. So that means that our excess numbers of deaths
  15     is 3.6. I hasten to add again, as has been mentioned
  16     already, that these are not 3.6 identifiable
  17     individuals; this is purely saying that we would have
  18     expected round about 3.5 deaths were Bristol typical,
  19     and in fact we have observed 7.
  20        That 3.6 in itself, you cannot claim that that
  21     could not have been due to chance alone. The interval
  22     around that goes from 7 to minus 4. Essentially, we are
  23     looking for that interval to exclude zero before we
  24     could say really we are confident that that excess
  25     mortality was not due to chance alone. So essentially

   1     getting 7 deaths out of 49 is not totally incompatible
   2     with having a 6 per cent mortality. There is excess,
   3     but we cannot be confident that it is real and it really
   4     reflects an increased risk in Bristol.
   5   THE CHAIRMAN: Dr Spiegelhalter, if I may interrupt for
   6     a moment, can you slow down sometimes just a little?
   7     Our stenographer has to ensure we have a complete
   8     record, and sometimes you have to slow down.
   9   DR SPIEGELHALTER: I will do my best, I am sorry.
  10   THE CHAIRMAN: Not at all?
  11   A. I assure you, I am not going to go through every line on
  12     every table.
  13        Essentially I have been going through this line,
  14     and then pointing directly at results.
  15        This column here, which is the probability that
  16     the excess is greater than zero, which one can think of
  17     as a probability that there really is something
  18     different, 88 per cent would not usually be considered
  19     sufficient to warrant very long evidence. Okay, there
  20     is an excess, but we are looking for 95/99 per cent
  21     really before we can be confident that there is
  22     something going on.
  23        Similarly, although in terms of its mortality
  24     Bristol ranks 10th out of 11 centres, there was only one
  25     in that particular time period, age group and for

   1     Fallot, there was only one centre in the country that
   2     had a higher mortality than Bristol. Bristol is
   3     observed to be 10th or second from bottom, but the
   4     95 per cent interval goes between 5th and 11th, so
   5     essentially all we can do is say we are confident it is
   6     in the bottom half of the centres in the country, but we
   7     cannot say it too much stronger than that.
   8        So that essentially is warning us not to take too
   9     much attention of something just because it is bottom.
  10     Someone has to be bottom, so we are looking for
  11     consistency of pattern and we are looking for really
  12     strongly divergent behaviour.
  13        When one is confronted with a page like this, all
  14     these comparative pictures are based on different groups
  15     of people. This is the first epoch, the two age groups,
  16     this is the second and this is third, 1991 to 1995 in
  17     the two age groups. We are looking for consistency of
  18     pattern. In other words, is the line from Bristol
  19     consistently lying on the left of the line from the
  20     other centres?
  21        We can see that while each stratum on its own is
  22     not too exciting, although in fact on this particular
  23     group here this really is, one can be 99 per cent sure
  24     that this is not due to chance, that there really is
  25     something different in the performance. When you are

   1     getting a similar pattern across different time periods,
   2     or age groups, it is only reasonable to accumulate them
   3     and look at what is happening in larger groups.
   4        So, for example, at the limit we can aggregate
   5     over all the time periods and all the ages, so this line
   6     here, which I will just highlight, is essentially adding
   7     up over all these six subgroups here.
   8        This says, the Cardiac Register data on Fallot
   9     operations reported double the mortality in Bristol as
  10     elsewhere in the country, and this represents an excess
  11     deaths of 11.4 out of 22 estimated to be about half, and
  12     the interval for that goes from 0 to 19, so essentially
  13     we can be 97 per cent sure that that excess is not due
  14     to chance alone but there really is excess mortality in
  15     Bristol compared with whether it is a typical centre.
  16        That is essentially by aggregating, we can say and
  17     it is one of the things I say in the report, if we do
  18     aggregate over the Cardiac Register, we find that there
  19     is reasonable evidence of excess mortality in Fallot
  20     operations.
  21   MR LANGSTAFF: Can I take you up to the line immediately
  22     above that one? You said a moment ago that looking at
  23     the excess deaths, one would be looking for a figure
  24     which would start no lower than 0 in order to see that
  25     there was a sufficient probability of an excess.

   1        There we have a minus 1 figure, and then, on the
   2     right-hand column, in the probability of excess, we have
   3     0.96, which I had understood from what you were saying
   4     represented a 96 per cent exclusion of chance as
   5     relating to the probability of an excess?
   6   A. Yes. One would not like to draw an absolute line of
   7     what is in quotes a "significant" excess and what is
   8     not. The point is, it is a 95 per cent interval, so you
   9     can think of it as 2.5 per cent on each side. If the
  10     bottom end of the interval is just 0, that really means
  11     there is a 97.5 per cent chance that actually the excess
  12     is positive. So slightly below 0 will correspond to
  13     something like 96/95 per cent.
  14        I do not want to make an absolute strict
  15     division. I would prefer to look for things really up
  16     high, 98/99 per cent before getting too confident.
  17   Q. If you are looking for 98/99 per cent, what about
  18     looking for 97 per cent on the bottom line?
  19   A. That would be classically considered a significant
  20     result, but the bottom end is just on 0. It is a 1 in
  21     40 chance that -- the fact there is now excess
  22     mortality.
  23        So some caution on that, and I hope I have been
  24     suitably cautious on the conclusions.
  25        One is also looking not only for consistency

   1     within the data sources but consistency across the data
   2     sources. The HES data is only available for the last
   3     epoch, so it is very useful to compare what was going on
   4     with HES in the last epoch with what was going on pooled
   5     over all the ages in the Cardiac Register for the last
   6     epoch, so that line and that line are often a very
   7     useful thing to compare. We can see in this case there
   8     is really quite strong agreement between what the
   9     Cardiac Register was reporting and what HES was
  10     reporting in the Fallot operations.
  11   Q. I think you may have said "last epoch". I think you may
  12     have meant the third?
  13   A. Yes, I am not using epoch 4 at all. All my analyses are
  14     1, 2 and 3 from now on.
  15        What I have been trying to look for as I have gone
  16     through these tables is to look for where the Cardiac
  17     Register and HES can be directly compared looking for
  18     consistency, in other words, corroboration between these
  19     two sources, and then also looking for consistency in
  20     the Cardiac Register across the periods of time, in
  21     particular, in epoch 2 and 3, when we feel there was an
  22     excess.
  23        What I would like to do, I hope without being too
  24     pedantic, would be to go through the procedure groups
  25     where there is some consistent evidence of interest. Is

   1     that all right?
   2   Q. Yes, certainly.
   3   A. If I could jump to 70, this is the group 3, the
   4     inter-atrial -- I am sorry, the arterial solution for
   5     transposition of the great arteries, so these are
   6     supposed to be the switch operations.
   7        The problem with this is that we have already
   8     heard that the Cardiac Register -- I will just look at
   9     the -- it will be useful to look at the pooled Cardiac
  10     Register data. We have already heard that the Cardiac
  11     Register does not code this group well; that the earlier
  12     Mustard and Senning operations have been coded up as
  13     corrective procedures and therefore are all mixed in.
  14        We find, looking at the Cardiac Register, in this
  15     group we do not find a distinction between Bristol and
  16     the rest of the country, except that there is perhaps
  17     some evidence in the more recent era -- this is perhaps
  18     interesting -- where most of these will be switches
  19     now. We do see some evidence of excess mortality in the
  20     under 1 years, 13 per cent in the rest of the country,
  21     28 per cent in Bristol, in the under 1 years.
  22        In the HES data, this is the data down here, we
  23     see a much stronger pattern, partly due to their ability
  24     to divide up the age groups into under 90 days, 90 days
  25     to 1 year, and 1 to 15 years. Dr Aylin has already gone

   1     through this data in detail, but I think it illustrates
   2     quite nicely -- "nicely" is not perhaps the right
   3     word -- the divergence between these two intervals.
   4     This is the national pattern elsewhere and the pattern
   5     in Bristol, with 90 per cent mortality, 9 out of 10
   6     deaths.
   7        When that is accumulated, there is apparently some
   8     excess, although very marginal in the other two age
   9     groups, and when accumulated over all ages for switch
  10     operations in the HES database, there were 11 deaths and
  11     they would -- in a typical centre I would only have
  12     expected 2, so one can estimate the excess deaths as 9,
  13     with an interval really well away from 0. I can be
  14     confident about that. The 1 should perhaps be 1.999,
  15     but it would not fit on the page.
  16        So there is an area where there is limited
  17     consistency between CSR and HES, but where we know the
  18     CSR has a lot of difficulty in the coding.
  19        If I could go on to group 4, TAPVD, page 71, this
  20     is really under 1 years of the - where these have been
  21     carried out, so that is the area of interest.
  22        We can see in CSR, if we look at these pictures,
  23     in the under 1 years, that is the top line, a consistent
  24     pattern of excess mortality over that observed in the
  25     other centres, over each era, each epoch in turn. So in

   1     the first one, 19 per cent versus 37; 13 versus 45; 14
   2     versus 33. So that suggests that is cumulating over the
   3     whole period of the cardiac register, in under 1 years,
   4     of what mortality might be. We find that the difference
   5     between 15 per cent and 38 per cent, and here we have
   6     excess mortality of 9.9 out of 17, with an interval that
   7     confidentially excludes 0.
   8        We want to see if we have consistency between HES
   9     data and the Cardiac Register, so perhaps it is good to
  10     compare what was going on in 1991/95 in HES with what
  11     was going on in 1991/95 in Bristol, reported to the
  12     Cardiac Register, and we find very strong consistency
  13     between these two sources in terms of the excess
  14     mortality.
  15        So there is a situation there where one seems to
  16     have strong consistency between the sources over the
  17     period which are being measured, consistency in the
  18     Cardiac Register across the time periods. So the TAPVD,
  19     which is in the area where coding is quite clear, comes
  20     out as an area where we can be really quite confident of
  21     excess mortality.
  22        I think that is not unrelated to the fact that we
  23     have seen, looking right back at comparing the sources,
  24     that TAPVDs were the areas with the best agreement,
  25     which also indicates consistency of coding.

   1        If we could go on to AVSD on page 72, here, if
   2     I could highlight, if we look at the pictures, we can
   3     again see a very consistent pattern, both in all the age
   4     groups and in all the periods. We are looking all the
   5     time to see whether the apparent mortality in Bristol,
   6     allowing for the uncertainty, is separate from the
   7     mortality in other centres.
   8        That kind of consistency again suggests perhaps
   9     looking directly at data pooled over the entire Cardiac
  10     Register period, and there we see mortality in 32 per
  11     cent AVSD, 14 per cent in other centres, so we are
  12     estimating about half of these deaths were in excess of
  13     what would have been expected in a typical centre, and
  14     again at intervals well away from 0. I am very
  15     confident that this is not due to chance.
  16        If we look at some consistency in the HES data and
  17     look at what was going on in the third epoch compared
  18     with what the Cardiac Register was reporting in the
  19     third epoch, we see again, while the agreement is not
  20     wonderful, it is reasonable good agreement between these
  21     two sources of information about what was going on
  22     between 1991 and 1995.
  23        So, again, both sources point to a very confident
  24     conclusion that mortality was in excess of what would
  25     have been expected.

   1        As I said, I will not go through all the 13 like
   2     this. I am just pointing out the ones I think show the
   3     clearest patterns and the ones I would feel most
   4     confident about drawing some conclusion from.
   5        If we go to 73, the closure of ASD, here again we
   6     are seeing in the under 1s a consistent pattern across
   7     the three epochs of what has been reported to the
   8     Cardiac Register of mortality in excess of the remaining
   9     centres. So if we look at over the period 1984 to 1995
  10     under 1 years, although this is only based on 10
  11     operations, we see a 50 per cent mortality compared with
  12     6 per cent in the rest of the country, which again
  13     suggests, although in not a large number of operations
  14     at all, that the mortality is in excess.
  15        For 1 to 15 years, there is no evidence at all
  16     that there was any problem whatsoever.
  17        Again, we would want to check, compare that data
  18     in the under 1 years for what -- one would want to
  19     compare consistency across the sources so one would want
  20     to compare that evidence from the Cardiac Register with
  21     this evidence from HES. We can see there is not
  22     a wonderful agreement there, but they are pointing
  23     definitely in the same direction. The agreement is not
  24     tremendous.
  25        So the ASD findings I think must be more

   1     tentative, but there is really evidence in here and in
   2     here of excess mortality just in the under 1 years.
   3        I am going to go through VSD, which there is no
   4     evidence of any difference, but I would like to go on to
   5     75, the truncus operations. That is of considerable
   6     interest.
   7        Following the way in which I have looked at these
   8     things before, one is looking for consistency of
   9     evidence across time periods and age groups, and here,
  10     although I think I could just look over the whole of the
  11     Cardiac Register data, although the mortality rate
  12     reported to the Cardiac Register is 9 out of 19, 47 per
  13     cent, the crucial thing is that the mortality rate
  14     reported by the rest of the country is very high as
  15     well.
  16        We can see -- I think this is quite an informative
  17     thing to look at, is what was being reported in the rest
  18     of the country over the time period. We see a mortality
  19     rate of around 50 per cent, which has now apparently
  20     dropped in the more recent period from 1991 to 1995, but
  21     still very high; the point being, and this is reflected
  22     as well in the HES data, that this is an area where,
  23     although there is apparently excess mortality in
  24     Bristol, there is observed to be a higher mortality
  25     rate, one really cannot be confident that is not due to

   1     chance alone. The numbers are too small and the
   2     mortality in the rest of the country is so high that
   3     truncus is something where we would not want to be
   4     confident that there was -- we would not like to be
   5     dogmatic that there was excess mortality there.
   6        I would now like to jump to just the open
   7     operations, 81.
   8        Again, we are looking for consistency across the
   9     time periods. We can see that in the under 1 years, not
  10     so much in the first epoch, but really in the first
  11     epoch, as we saw in those early graphs, really Bristol
  12     could be considered as representative. But the
  13     divergence increases over time in the second and the
  14     third epoch, with the result that in the second two
  15     epochs we have some evidence of excess mortality in what
  16     is reported to the Cardiac Register. These intervals
  17     include 0.
  18        I am sorry, I should not be looking at all ages,
  19     it is the under 1 years that are important. If I look
  20     at this one, if I look at over the whole period, under 1
  21     year, then the mortality rate of 26 per cent reported to
  22     the CSR as compared to 16 per cent, and that represents
  23     excess mortality of 29.6 out of 90, and we can be
  24     borderline confident that that is not due to chance
  25     alone.

   1        In fact in the first epoch there is no evidence of
   2     any difference, so the effect -- this confidence is
   3     slightly damped down by that first epoch.
   4        In the HES data, as we have already heard from
   5     Dr Aylin, in the under 1 years there really is quite
   6     strong evidence of excess mortality, and over all age
   7     groups, if we just pool over all age groups, we are
   8     seeing out of 62 deaths in open operations in 1991 to
   9     1995, one would only have expected round about 30 were
  10     Bristol to be typical. So we are getting an interval
  11     well away from 0 in this situation.
  12        We should note that the ranking for this,
  13     particularly the under 90 day mortality, we can actually
  14     be pretty well confident that Bristol was the worst, had
  15     the highest mortality in the country at that time.
  16   Q. In the next category, one can be confident that it was
  17     either the worst or the second worst?
  18   A. Yes. Unless there is something I could clarify, if
  19     I could stop going through all those -- I have gone
  20     through the operations where I feel there is
  21     a consistent pattern which I summarise at the end.
  22   Q. Others can look at the charts and the tables you have
  23     produced?
  24   A. I feel apologetic about the density of these tables.
  25     I just hope I have explained slightly how to read them.

   1   THE CHAIRMAN: I would interject that no apology is called
   2     for. I find them very clear.
   3   A. Thank you very much. If I could then jump to the
   4     delicate issue of the fact that this entire analysis has
   5     been repeated for all the other centres and if I could
   6     then look at 99. If we could blow that up a little
   7     bit. What this looks at is HES data, open operations in
   8     epoch 3, broken up into the three age groups. Now we
   9     are actually seeing, centre number 1 is Bristol, so this
  10     is the data we have seen before. But, instead of all
  11     the rest being lumped together into one great elsewhere,
  12     we are now seeing the mortality rates in the individual
  13     centres.
  14        The reason for this is because we felt that we
  15     were not looking for divergent -- it would not be
  16     considered divergent performance if Bristol, or any
  17     centre, is just sitting on the outside of the
  18     distribution inevitably that exists. We are looking for
  19     something that even allowing for the interval around it
  20     is substantially way from the bulk of the other
  21     centres. For under 90 days and 90 days to 1 year, while
  22     there is rather good homogeneity between the remaining
  23     centres, we have centre number 1 sitting really
  24     substantially outside those intervals. That separation
  25     is reflected in the confidence with which we can state

   1     that there was excess mortality.
   2   Q. If one looks at the left-hand table, and goes back to
   3     the question which I asked you earlier about the size of
   4     the centres, there is some suggestion, is there, that
   5     the smaller centres are lagging behind the larger
   6     centres?
   7   A. That is a standard analysis to do, and I have to say we
   8     have not done it. I would say very quickly, looking at
   9     the left here, you are right. If we look at the biggest
  10     centres, centres 11 and 8 and 3, they are the centres
  11     with the lowest mortality rate. The smaller centres,
  12     centre 4 and 1 and 5, 9 and 10, are the centres with the
  13     highest mortality rate. It seems to me that under 90
  14     days picture in particular is a very strong indication
  15     of the relationship of volume with mortality rate.
  16        We have not carried out a confirmatory analysis on
  17     that. In that particular instance, that seems to be the
  18     case.
  19   Q. If we find that picture is repeated across the board, it
  20     may actually provide some of the evidence we have been
  21     told elsewhere in this Inquiry has been looked for
  22     because it does not exist in this country, that small
  23     size may be inimical to good performance, or best
  24     performance?
  25   A. I think that data such as this could stand further

   1     analysis in that regard, yes.
   2        This is looking at the HES data. If you go to
   3     page 101, it is repeating this for the Cardiac Register
   4     data.
   5        If we look up the two left-hand ones, I wonder if
   6     those could be made any bigger. That is looking at the
   7     first epoch. The point about these, the first epoch is
   8     when the Cardiac Register really did not report that
   9     Bristol was in any way different from the others. I do
  10     not want to make a strong interpretation of these,
  11     except a point perhaps already at centre 10 that in the
  12     1 to 15 year old open operations has a mortality rate of
  13     15 per cent compared with 8 per cent in the whole
  14     country.
  15        If we go on to the next column of the two graphs,
  16     the next bit along, if we go to the centre column, what
  17     has been reported to the Cardiac Register in epoch 2,
  18     between 1988 and 1990, now we are seeing Bristol with
  19     quite high mortality being reported, but not sitting out
  20     on its own at all. This is the kind of analysis that
  21     Professor Murray did showing that, although Bristol is
  22     in this instance essentially on the edge, we cannot be
  23     confident that it is really beyond the distribution of
  24     the others. I think perhaps we might point out again
  25     centre 10 in the under 1s and in the over 1s.

   1        If we go on to the last epoch, the cardiac
   2     register, the final column of that picture, again it is
   3     only in the under 1s where Bristol, now really looking
   4     in this final period, is looking really substantially
   5     different from the others. We have already been through
   6     all that. Now I would like to repeat again centre 10 is
   7     sitting out here on the 1 to 15 years.
   8        So, building on that, I would like to jump to
   9     page 97. There are pages of tables like this which are
  10     very dull. What they do say is that for each of these
  11     centres what was the apparent -- the estimated excess
  12     mortality in all these operation groups.
  13        This particular table combines all the cardiac
  14     register data from 1984 to 1995, but just in the age
  15     group 1 to 15 years.
  16        As I say in my report, when you search through
  17     these tables, you find very few -- I have given a star
  18     when we can be 99 per cent confident that the excess
  19     mortality is real, that there really is differing
  20     performance, so when that figure that was in the
  21     previous tables reached 99.
  22        This is in 1 to 15 years. What I would like to
  23     point out here is centre 10, where there really is
  24     apparently substantial excess mortality reported to the
  25     Cardiac Register in 1 to 15 years.

   1        That is in the report, I just say, centre 10,
   2     there is some consistent evidence about centre 10.
   3     I have actually done a little bit more analysis of
   4     that. If I could jump to page 123, I have done
   5     a further analysis of what was going on -- what was
   6     being reported to the Cardiac Register between 1984 and
   7     1995 by centre 10 in age 1 to 15 years.
   8        If I could jump to down here, we can see that
   9     centre 10 was reporting in open operations a mortality
  10     of 14 per cent compared with 6 per cent over the rest of
  11     the country. That represents an apparent excess
  12     mortality of around 60, and we can be very confident
  13     that is real. That is the figure I showed earlier on.
  14        What I am attempting to do here is to see some
  15     sort of explanation of what the source of that excess
  16     mortality might have been. I think the very strong
  17     finding here is that, when we look at these 13 groups,
  18     there is no real evidence of excess mortality. These 13
  19     groups also only cover 485 of those operations compared
  20     with 747 open operations. What this is saying is that
  21     in centre 10 there are a large number of open operations
  22     being reported in the Cardiac Register with high
  23     mortality rates that do not fit in with the now 13
  24     consensus groups.
  25   Q. So if it were to be the case that Harefield did a large

   1     number of transplant operations, you would not see it in
   2     1 to 13, but you might see it in the difference between
   3     485 operations conducted and 747 open operations in
   4     total conducted?
   5   A. Exactly, and this period from 1984 would cover the
   6     developmental period of paediatric transplantation,
   7     where I imagine, although I do not have the data, one
   8     would expect to have a high mortality rate.
   9   Q. I have chosen transplants because we know Harefield does
  10     them.
  11   A. When I did the analysis I had no idea what centre 10
  12     was, but when I did find out, that provided some of the
  13     explanation which I think we had taken into account.
  14        If we can just jump to page 127 -- I am nearly
  15     finished now; this is my second to last -- this is again
  16     looking in more detail at centre 10 what the HES data is
  17     saying about them, again from ages 1 to 15 years.
  18        The HES data again is reporting really
  19     a substantially increased mortality in open operations
  20     with, out of 35 deaths, they would only have expected,
  21     were they typical, about 12.5.
  22        In HES it is a slightly different picture to the
  23     cardiac register, in that these open operations really
  24     are substantially falling within the coded up groups.
  25     We see when we run up our eye along here that really

   1     there is considerable evidence of excess mortality in
   2     Fallot operations, 19 per cent mortality, and
   3     considerable evidence in Fontan operations, 9 per cent
   4     failure, 27 per cent in excess is 6. It is a very
   5     difficult pattern to that observed in Bristol. I am
   6     very anxious I do not give the impression in my report
   7     that the apparent estimated excess mortality in
   8     centre 10 reflects a similar pattern to in Bristol. It
   9     is a very, very different pattern being observed.
  10        This again suggests that there needs to be
  11     considerably more investigation of the case mix in
  12     centre 10, in case they are accepting patients who have
  13     already been operated on, perhaps have been left rather
  14     late, and so on.
  15   Q. Could I raise one matter with you in relation to
  16     centre 10? You say in the body of your report -- I am
  17     not going to take you to it -- that there is consistent
  18     evidence from both HES and the Cardiothoracic Surgical
  19     Register that Harefield has excess mortality similar to
  20     Bristol.
  21        I think that may convey the impression that that
  22     is true of all outcomes?
  23   A. Yes.
  24   Q. The consistency is limited to the 1 to 15 year group?
  25   A. Yes, exactly. That is what I wanted to apologise for,

   1     that rather perhaps poor wording. First of all, when
   2     I said "similar to Bristol", I meant actually the
   3     extent, the actual numbers, not the pattern. It is very
   4     different. 1 to 15 year olds seems to be in very
   5     specific areas.
   6   Q. There is in fact an inconsistency in the picture we get
   7     from HES on the one hand and the CSR on the other?
   8   A. Not in terms of the excess. Both report strong excess
   9     mortality in open operations. There are obviously a lot
  10     of operations not coded up on in the CSR that are
  11     contributing to high mortality.
  12        If I might finish, I had not realised how late it
  13     was, I am sorry.
  14        If you go to page 129, I have my final
  15     conclusions.
  16        Essentially, this is just summarising the
  17     findings, that these are imperfect data. Professor
  18     Murray has expressed strong doubts about the cardiac
  19     register's lack of agreed procedures. However, the 6
  20     sources on Bristol do agree well, especially in the
  21     areas identified by the analysis as being of primary
  22     interest. HES and CSR do show a reasonably strong
  23     degree of consistency, and in that exercise of going
  24     through the operations, particularly identified on open
  25     procedures on children less than 1, there is some

   1     consistency. For switches, TAPVDs, AVSDs and, although
   2     rare, ASDs. Truncus operations could have been due to
   3     chance alone. In over 1s, Fallot and AVSD, there is
   4     some evidence of excess mortality there. No source can
   5     be considered as the truth; however the consistency
   6     suggests the findings reinforce each other.
   7        I would agree with the others, the fact this data
   8     is imperfect, the imperfections are not sufficient to
   9     cast serious doubt on the fact there is divergence of
  10     performance in fairly identifiable areas.
  11   Q. You take that a shade further on page 131.
  12   A. Yes, I am sorry.
  13   Q. It is the "but" at the end of the page. You are echoing
  14     there what Professor Murray said?
  15   A. Exactly. I have some experience as well of using risk
  16     adjustment procedures in analysis, and while they do
  17     explain a certain percentage of the variability, I would
  18     find it remarkable if they could explain a substantial
  19     amount.
  20   Q. Although it is late, I want to take a couple of minutes
  21     to ask you, and for that matter the other experts we
  22     have heard from today, whether, in the light of the
  23     substantial measure of agreement, despite their
  24     imperfections, between the data sources, it is necessary
  25     and if so to what extent it is necessary, to further

   1     confirm the data that we have.
   2        What would you say to that?
   3   A. I am not sure. I have been pondering this. I am not
   4     convinced that actually finding out yet more precisely
   5     what happened in Bristol, even what happened elsewhere,
   6     is going to add a huge amount. I think it would be very
   7     good, as people mentioned, to validate the mortality
   8     being reported elsewhere, possibly by linkage with
   9     national mortality records.
  10   Q. Can that be easily, speedily and economically done?
  11   A. If you can identify the patients, we can tag them with
  12     the national mortality records reasonably easily and
  13     cheaply and that seems to me a valuable thing to do.
  14   Q. You have given your view. May I ask our panel here
  15     whether they take the same view, or whether they would
  16     differ?
  17   DR AYLIN: I think in the case of the CSR, because it is
  18     based on aggregate tables, you cannot track those down,
  19     but with HES, given that we have a date of birth, a sex
  20     and a postcode, it may indeed be possible to link it
  21     with the national death registration figures.
  22   MR LANGSTAFF: You are dealing with linkage. Is there any
  23     other need you would see to further confirm the data, or
  24     are you happy with what Dr Spiegelhalter has said that
  25     essentially we have extracted a surprising amount from

   1     the data and need very little further.
   2   PROFESSOR EVANS: I think I would agree with that in
   3     general. I think that there is a possibility that with
   4     the very different age distribution of children seen in
   5     the different centres that there could be that age
   6     difference having some effect. I do not think it does.
   7     In order to be rigorous, if one is going to look at
   8     other centres, it is very important to see that the age
   9     at which children got their operation was similar and if
  10     it is not, as we think it is not, there needs to be some
  11     adjustment for that. It is very difficult. It seems to
  12     me if we are going to go to other centres it could be
  13     that the key thing and the sensible thing to do would be
  14     to do it in one or two high risk groups.
  15   MR LANGSTAFF: Professor Murray?
  16   PROFESSOR MURRAY: I agree completely.
  17   MR LANGSTAFF: With Professor Evans.
  18   PROFESSOR MURRAY: With Professor Evans. I think the
  19     mortality is the biggest hole in the argument and most
  20     easily tackled. I think as Professor Evans says, there
  21     are a number of high risk procedures that we could
  22     follow up. I think that would provide added value, at
  23     relatively little extra work.
  24   MR LANGSTAFF: Professor Campbell?
  25   PROFESSOR CAMPBELL: I would agree as well. I mean, one of

   1     the big problems would be the very major source of work
   2     to go through this sort of data validation exercise in
   3     the six different sources for all 11 other centres,
   4     which I think is a possible source of bias, but I think
   5     it is a very small one. I think the amount of work
   6     required to do that would not be justified.
   7   MR LANGSTAFF: So essentially, the message you are giving is
   8     that there is some benefit in the two steps you have
   9     identified, but otherwise very little that is likely to
  10     be gained from any further in-depth examination?
  11     I thank you for that.
  12        Dr Spiegelhalter, we have not dealt with the five
  13     further bullet points you make at the top of the page as
  14     to where we go from here. This is where you were left
  15     in July when you said this is where we go, and now you
  16     are reprising.
  17   DR SPIEGELHALTER: The original strategy, as I pointed out,
  18     did envisage the possibility of really confirming the
  19     accuracy of findings and then seeking an explanation,
  20     and I suppose my feeling is that the picture is quite
  21     clear. I would like to see the mortality data
  22     validated. I would very much like to see a move towards
  23     explanation, which I think while there is some
  24     statistical input into that, we need a lot of clinical
  25     input and clinical insight and the attempts to relate

   1     outcomes to the process of care in Bristol would seem to
   2     be vital.
   3   MR LANGSTAFF: You have identified various other things,
   4     which I think probably speak for themselves. We
   5     approach tomorrow, as you know, the beginning of looking
   6     at the clinical case review which has been conducted,
   7     and getting a view from that: is that the sort of
   8     clinical input that you have in mind as perhaps giving
   9     some clue towards an explanation as to why the figures
  10     are as they appear to be?
  11   DR SPIEGELHALTER: Yes, very much so and I think the aim of
  12     this exploratory exercise was largely to identify the
  13     areas that would be worth deeper study and I think in
  14     that sense it has been quite successful in narrowing
  15     down where attention ought to be focused.
  16   PROFESSOR EVANS: May I make a comment that some people have
  17     not understood some of the key things Dr Spiegelhalter
  18     has done.
  19        Dr Spiegelhalter has done something very clever,
  20     effectively with league tables. If you imagine
  21     a football league table -- I am sorry, I am not wishing
  22     to trivialise this, but in order to try and help people
  23     understand, if after 10 games nearly all of the teams
  24     have had 10 draws, and one team has had 9 draws and
  25     a win, so they have 12 points and one team has had 9

   1     draws and a loss, so they only have 9 points, the
   2     difference between the top and the bottom of the league
   3     is clearly due to chance and somebody would see that
   4     very clearly.
   5        But if after 10 games there was one team that had
   6     had 10 wins, and one team that had had 10 losses, it
   7     would be very clear that there was a really big
   8     difference between those.
   9        What Dr Spiegelhalter has done is by doing
  10     something very clever, he has allowed for the fact that
  11     whatever we do, there will always be someone top and
  12     bottom and the really important question is, if Bristol
  13     were bottom, are they bottom by a small amount and could
  14     they have just as easily been in the middle or near the
  15     top, or not? That is the key statistical thing that has
  16     been done very cleverly, and which is able to sort that
  17     out. It means that a lot of the medical world out there
  18     also believes that Bristol was just bottom by chance and
  19     that it was just bottom of the league and they know that
  20     league tables are capable of misinterpretation.
  21        What Dr Spiegelhalter and what Nicky Best and Paul
  22     Aylin have done is to make sure that kind of
  23     interpretation of it merely being bottom of the league
  24     is not done. I am sorry to take your time --
  25   MR LANGSTAFF: Not at all. I am very grateful.

   1   PROFESSOR EVANS: I do not know whether they would agree
   2     with that.
   3   MRS MACLEAN: I just wanted to go back to the point of the
   4     size of centres. Would it be of value to investigate
   5     that further? I think it might be helpful to us.
   6   DR SPIEGELHALTER: I think just using the data available,
   7     that could be investigated further. I think in a sense,
   8     that is going beyond what we were asked to do, because
   9     it is not specifically Bristol, it is the whole idea of
  10     performance, but I do feel that having gone through
  11     enormous data together, it could be mined for
  12     considerably more.
  13   MR LANGSTAFF: Sir, can I thank all our participants today.
  14     Can I say, I am conscious of the hour and that there may
  15     be a number of those who have watched and listened today
  16     who may have questions to ask. If I can remind them of
  17     the procedure which is open in this Inquiry, for the
  18     Inquiry itself to ask further questions of witnesses, in
  19     writing, orally if need be, in order to clarify or
  20     expand, and if it seems to the legal team that you, the
  21     Panel, would benefit by an expansion, an exploration, or
  22     even a contradiction of what has been put before you
  23     today, that we would be happy to ask the appropriate
  24     questions of the appropriate or indeed all experts, and
  25     I am sure that they would be happy to answer in a way

   1     which would help the Inquiry.
   2   THE CHAIRMAN: Thank you, Mr Langstaff. If we are coming to
   3     the end of the day, I just wanted to say a couple of
   4     things.
   5        We have seen today another piece of the jigsaw.
   6        I will make one comment if I may: data such as
   7     that which we have seen today explains nothing. It
   8     suggests, however, that we should seek an explanation,
   9     or explanations. Thus, it would be quite wrong yet to
  10     draw any firm conclusions about any individual or in
  11     general. We still have some work to do and some way to
  12     go and tomorrow we take the next step, taking I think
  13     quite properly the advice that we see in
  14     Dr Spiegelhalter's paper, that some clinical insights
  15     would now be valuable. That is indeed what we will see
  16     tomorrow: another piece of the jigsaw. But before
  17     I close today's proceedings, I must praise and thank the
  18     expert panel, both our statisticians and the clinicians
  19     who have sat quietly today but I know have been so
  20     important in the background.
  21        I notice in your papers that you have also
  22     generously thanked members of the Inquiry's Secretariat,
  23     and we echo our gratitude to all of them, especially
  24     Ruth Chadwick and Liz Baldock, and the whole of the
  25     Inquiry's Secretariat. They are the backroom girls,

   1     rarely noticed and we praise them and thank them.
   2        The Inquiry, indeed, I would venture to suggest,
   3     the public generally, owes you, our experts, a great
   4     debt of gratitude. You have performed an outstanding
   5     service and you have done so brilliantly, if I may say
   6     so. May no-one underestimate the challenge you face,
   7     not least because of the time-scale we impose.
   8     I express our thanks.
   9        One further point, more generally. I have from
  10     time to time asked for patience as the Inquiry has
  11     proceeded. What we have seen today demonstrates the
  12     need for that patience. If we are to do our job
  13     properly, do our duty to the public, we must, amongst
  14     other things, do it thoroughly. Only in that way, will
  15     we be fair to everyone.
  16        You have seen today what "thoroughness" means.
  17        A remark, you have also seen what we meant when we
  18     committed ourselves to carrying out our role openly and
  19     in public. What we have sought to do today is to
  20     explain what to many is a mystery: we have sought not to
  21     sustain the mystery and keep it to ourselves. Good
  22     afternoon to you.
  23   MR LANGSTAFF: Before we part company and in the light of
  24     making it completely transparent what material is before
  25     the Panel in terms of statistics, I should say, perhaps

   1     I should have said earlier, that today there has been
   2     published a witness statement of Professor Robert Curnow
   3     of the Department of Statistics of the University of
   4     Reading which is available as WIT 361 as to the
   5     contribution that statistical evidence can make to the
   6     Inquiry. Because of his position in the Statistical
   7     Society of Great Britain, he is particularly well placed
   8     to give that advice.
   9        WIT 375, Mr Nigel Bell of the National Health
  10     Service information authority, dealing with the process
  11     and nature of the coding exercise; and as I mentioned
  12     earlier, but did not identify by reference, INQ 18,
  13     a paper from the Inquiry Secretariat from Ruth Chadwick
  14     and her assistants to whom you have referred, who have
  15     explained, so that it is clear and transparent, the
  16     process by which the various groupings and rankings were
  17     reached.
  18   THE CHAIRMAN: Thank you for reminding us of that. Good
  19     afternoon again.
  20   (5.06 pm)
  21       (Adjourned until 9.30 am on 4th November 1999)
  22
  23
  24
  25

   1                I N D E X
   2
   3
   4     INTRODUCTION TO TODAY'S EVIDENCE ................... 1
   5
   6     PROFESSOR MICHAEL JOSEPH CAMPBELL (sworn)
   7        Examined by MR LANGSTAFF ..................... 27
   8
   9     PROFESSOR STEPHEN EVANS (sworn)
  10        Examined by MR LANGSTAFF ..................... 42
  11
  12     DR PAUL AYLIN (sworn)
  13        Examined by MR LANGSTAFF ..................... 72
  14
  15     PROFESSOR GORDON MURRAY (sworn) .................... 116
  16        Examined by MR LANGSTAFF ..................... 116
  17        Examined by THE PANEL ........................ 145
  18
  19     DR DAVID SPIEGELHALTER (affirmed)
  20        Examined by MR LANGSTAFF ..................... 147
  21
  22
  23
  24
  25

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Published by the Bristol Royal Infirmary Inquiry, July 2001
© Crown Copyright 2001