Information in practice
Computer support for interpreting family histories of breast and ovarian cancer in primary care: comparative study with simulated cases
Jon Emery a ICRF General Practice Research Group, Division of
Public Health and Primary Health Care, Institute of Health Sciences,
University of Oxford, Oxford OX3 7LF, b Cancer
Research Campaign Primary Care Education Research Group, Division of
Public Health and Primary Health Care, University of Oxford, c Department of Primary
Health Care, University of Oxford, d Department of Clinical
Genetics, Oxford Radcliffe NHS Trust, Churchill Hospital, Oxford
OX3 7JL, e ICRF Advanced Computation Laboratory, PO Box 123, London WC2A 3PX
Correspondence to: J Emery jon.emery{at}dphpc.ox.ac.uk
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Abstract |
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 Top
 Abstract
 Introduction
Participants and methods
Results
Discussion
Appendix
References
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Objectives:
To evaluate the potential effect of
computer support on general practitioners' management of familial
breast and ovarian cancer, and to compare the effectiveness of two
different types of computer program.
Continuing advances in the molecular genetics of common diseases
mean that primary care will play an increasing role in providing genetic advice.1 The recent increase in referrals of
people at low risk of inherited cancer, particularly breast cancer, to genetics clinics suggests that general practitioners need a range of
new skills to be effective gatekeepers.2 The ability to obtain and interpret family history information accurately is fundamental to these new skills.3 Computers could support
primary care in this new task by simplifying pedigree drawing and
implementing management guidelines.
4 5
We previously reported a qualitative evaluation of Risk Assessment in
Genetics (RAGs), a computer program to support the assessment of
familial breast and ovarian cancer in primary care.6 The results of this study informed the development of the software used in
the current study so that it was more appropriate for primary care. The
aim of the current study was to compare two different types of computer
support Participants
Computer support
Simulated cases and recommended management
Study design
Outcome measures
Sample size and statistical analysis
Characteristics of participants
Outcomes
Table 1.
Design:
Crossover experiment with balanced block design.
Participants:
Of a random sample of 100 general
practitioners from Buckinghamshire who were invited, 41 agreed to
participate. From these, 36 were selected for a fully balanced study.
Interventions:
Doctors managed 18 simulated cases:
6 with computerised decision support system Risk Assessment in
Genetics (RAGs), 6 with Cyrillic (an established pedigree drawing
program designed for clinical geneticists), and 6 with pen and paper.
Main outcome measures:
Number of appropriate
management decisions made (maximum 6), mean time taken to reach a
decision, number of pedigrees accurately drawn (maximum 6). Secondary
measures were method of support preferred for particular aspects of
managing family histories of cancer; importance of specific information on cancer genetics that might be provided by an "ideal computer program."
Results:
RAGs resulted in significantly more
appropriate management decisions (median 6) than either Cyrillic
(median 3) or pen and paper (median 3); median difference between RAGs
and Cyrillic 2.5 (95% confidence interval 2.0 to 3.0; P<0.0001). RAGs also resulted in significantly more accurate pedigrees (median 5) than
both Cyrillic (median 3.5) and pen and paper (median 2); median
difference between RAGs and Cyrillic 1.5 (1.0 to 2.0; P<0.0001). The
time taken to use RAGs (median 178 seconds) was 51 seconds longer per
case (95% confidence interval 36 to 65; P<0.0001) than pen and paper
(median 124 seconds) but was less than Cyrillic (median 203 seconds;
difference 23. (5 to 43; P=0.02)). 33 doctors (92% (78% to 98%))
preferred using RAGs overall. The most important elements of an
"ideal computer program" for genetic advice in primary care were
referral advice, the capacity to create pedigrees, and provision of
evidence and explanations to support advice.
Conclusions:
RAGs could enable general practitioners
to be more effective gatekeepers to genetics services, empowering them
to reassure the majority of patients with a family history of breast
and ovarian cancer who are not at increased genetic risk.
Introduction
Top
Abstract
Introduction
Participants and methods
Results
Discussion
Appendix
References
RAGs and Cyrillic (an established pedigree drawing program
designed for clinical geneticists)with traditional pen and paper
methods in the recording and interpretation of family histories of cancer.
Participants and methods
Top
Abstract
Introduction
Participants and methods
Results
Discussion
Appendix
References
We wrote to a random sample of 100 Buckinghamshire general
practitioners inviting them to participate in the study. After one
mailing, 41 doctors agreed to join the study, of whom the first 36 respondents were chosen. The participants were paid £80 for the two
hours required to perform the study.
RAGs was developed in a collaboration between JE and the ICRF
Advanced Computation Laboratory. Pedigrees are generated by first
entering information about the proband and then adding data about
relatives by clicking on individual icons in the family tree. The
program uses PROforma technology7 to categorise risk of breast and ovarian cancer. The program implements detailed referral guidelines that are based on the Claus
model8 and then suggests appropriate management. The Claus
model is a mathematical model that predicts risk of breast cancer and
is based on data from a case-control study of 4730 breast cancer cases.
Cyrillic draws pedigrees and assesses risk of breast cancer, also using
the Claus model, and calculates the numerical risk of carrying a
mutation that predisposes to breast cancer and the cumulative risks of
developing breast cancer.9 Cyrillic was originally
designed for use by clinical geneticists. This study used a modified
version of Cyrillic that takes the user through a series of question
and answer boxes to construct the pedigree.
We developed 18 hypothetical cases, designed to cover a range of
risk levels, based on the types of referral received by the Oxford
genetics clinic in the previous year. An expert panel comprising a
general practitioner and a health services researcher with knowledge of
cancer genetics and a clinical cancer geneticist agreed by consensus
the appropriate management for each case. Management decisions were
based on the strategy proposed at a UK national consensus meeting: low
risk women are managed in primary care, moderate risk women at a breast
unit, and high risk women at a genetics clinic.10 The
panel decided that there were six high risk, five moderate risk, and
seven low risk cases. The cases were randomly allocated into three sets
of six.
Each doctor was asked to manage all 18 cases, six with each method
of support (RAGs, Cyrillic, and pen and paper). We used a balanced
block design. To avoid any learning effect, the order in which the
methods and case sets were presented was completely balanced among the
36 doctors. We also ensured that each method was used equally often
with each case set (see extra table on the BMJ website).
For each case, the doctor was asked to create a pedigree and decide on
management using the principle of triaging the patient as low,
moderate, or high risk. The two computer programs were set up on a
laptop computer in the doctor's consulting room. The participants were
familiarised with each program with one or two test cases before
conducting the study. When the doctors used pen and paper to manage
cases they were allowed to use any paper referral guidelines that were
available to them. Although all Buckinghamshire general practitioners
had been mailed management guidelines in 1997, only three of the
doctors in our study had access to these in their consulting room.
The principal outcome measures were the number of appropriate
management decisions made for each set of six cases, the mean time
taken to reach a decision, and the number of pedigrees accurately
drawn. A pedigree was considered correct only if it used standard
symbols and lines and contained information about the age of the
proband, type of cancer, and age of onset for each affected relative.
After managing all 18 cases, the participants completed a questionnaire
asking them to rate, on a five point Likert scale, the three methods
for particular aspects of managing family histories of cancer, and the
importance of specific functions or information on cancer genetics that
might be provided by an "ideal computer program."
From the results of a pilot study, we calculated that we required
25 doctors to detect a mean difference of 1.5 in management scores (SD
1.6) between RAGs and Cyrillic with 90% power and two sided 
=0.05.
The sample size was increased to 36 to make a completely balanced study
design. We used Friedman's two way analysis of variance to compare
effects overall for each outcome. To compare different pairs of support
for each outcome, we used Wilcoxon's matched pairs signed rank test.
We used SPSS for Windows (version 8) for the Friedman's and
Wilcoxon's tests, and the confidence interval analysis program
(CIA)11 to calculate differences in medians and associated
confidence intervals.
Results
Top
Abstract
Introduction
Participants and methods
Results
Discussion
Appendix
References
The characteristics of the participants were similar to those who
chose not to enter the study. Of the 36 doctors selected to
participate, 69% were men, 61% held the MRCGP, and their median time
since qualification was 21 (range 7-36) years. Of the 59 non-participants, 61% were men, 56% held the MRCGP, and their median
time since qualification was 21 (range 8-39) years.
Table 1 shows the median outcomes for the three different types of
support. RAGs resulted in significantly more appropriate management
decisions and accurate pedigrees than both Cyrillic and pen and paper.
The median difference in management scores between RAGs (median 6) and
pen and paper (median 3) was 3 (95% confidence interval 2.5 to 3.5;
P<0.0001) and between RAGs and Cyrillic (median 3) was 2.5 (2.0 to
3.0; P<0.0001). Pedigrees were more accurately drawn with RAGs than
with pen and paper (median scores 5 v 2; difference 3 (2.5 to 3.5); P<0.0001) or with Cyrillic (5.0 v 3.5; difference
1.5 (1.0 to 2.0); P<0.0001). Cyrillic produced significantly more
accurate pedigrees than pen and paper (median difference 1.5 (1.0 to
2.0); P<0.0001), but there was no difference in management scores
between these two types of support (median difference 0.5 (0 to 1.5);
P=0.08). It took significantly longer to reach a decision with RAGs
than with pen and paper (median 178 seconds v 124 seconds;
difference 51 (37 to 66); P<0.0001) but significantly less time than
with Cyrillic (178 v 203 seconds; difference 23 (5 to 43);
P=0.02). The figure shows the distributions of time taken with each
method.
traditional pen and paper and computer programs RAGs and
Cyrillic
drawing and
understanding the pedigree, ease and speed of use, and information providedand 92% (95% confidence interval 78% to 98%) of the
doctors preferred RAGs overall.
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Discussion |
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Top
Abstract
Introduction
Participants and methods
Results
Discussion
Appendix
References
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In this study of 36 general practitioners, we have shown the potential for computer support, and in particular RAGs, to improve the management of patients with a family history of breast and ovarian cancer in primary care. RAGs led to more appropriate management decisions and more accurate pedigrees at the expense of an additional median 51 seconds per case.
Limitations of study
After a single letter of invitation to participate, only 41 of 100 doctors agreed, of whom only 36 entered the study for a fully
balanced design. Our sample may therefore be unrepresentative of
British general practitioners. However, the doctors studied were no
different in their basic characteristics from those who chose not to
participate. Thirteen of the doctors in the study were unfamiliar with
a Windows interface, suggesting that our sample was not a self selected
group of highly computer literate practitioners. Furthermore, by
offering payment for participation, we were more likely to recruit a
representative sample of general practitioners.12
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Comparison with other studies and implications for practice
This study confirms the ability of computer decision support
systems to improve physicians' performance13 at the
possible expense of longer consultations.14 It also shows the difficulty general practitioners have in appropriately managing patients with a family history of cancer. This is in keeping with a
study of general practitioners in south east Scotland, who showed a
tendency to overestimate risk of cancer on the basis of family history
and who expressed a desire for computer aided risk assessment in this
field.15
standard care, numerical risk assessment, and specific
management advicerather than comparing standard care with two
computer programs that provide the same information in different
formats. Cyrillic is the only commercially available pedigree drawing
program that performs risk assessment for breast cancer. We therefore
compared existing technology with a newly developed technology.
This study shows the importance of developing medical software to meet
the specific needs of its intended users, and this may require
considerable variation in the format and type of information provided.16 It supports the combination of qualitative and
quantitative methods, with the early involvement of potential users, to
develop medical software that is appropriate for a specific clinical
context.17
There are several reasons why RAGs might be more appropriate for
general practitioners than Cyrillic. RAGs has a simpler interface with
fewer potential actions or choices for the user. This seemed to be
particularly important for the less computer literate doctors. The
method of generating a pedigree was more flexible and allowed mistakes
to be corrected more easily. In particular, the graphical presentation
of the family tree, with labels explaining the nature of the
relationship with the proband, assisted doctors who were less familiar
with pedigrees. Cyrillic assumes that users understand the nature of
family relationships such as cousins and great aunts, but this
knowledge was not universal in our sample of doctors. RAGs prompts
users to enter a minimum dataset required for risk assessment, thus
avoiding potential incorrect estimations of risk because of inadequate
data. Most importantly, however, RAGs provides management advice,
whereas Cyrillic gives only a numerical risk assessment. With the
exception of extreme values, the numerical risks alone were
insufficient to aid general practitioners in their decision making. The
doctors in this study rarely ignored the advice provided by RAGs, and
the main reason for incorrect management with RAGs was an error in
entering data.
Molecular genetics is likely to have an increasing influence on the
practice of clinical medicine.18 Primary care is poorly prepared for this new era, and general practitioners will need to
acquire new skills and knowledge to play an important role in the
delivery of genetics services.
19 20
Guidelines have been
suggested as a method of bridging this knowledge gap, but, as we found
in this study, paper guidelines are rarely accessible in general
practice when required.21
In the United Kingdom few general practitioners currently use their
computer as a source of information during
consultations.22 This reflects the limitations of existing
hardware and software, which present a substantial barrier to
integration of decision support into clinical practice.4
Field trials are needed to assess the real impact of computer support
for cancer genetics in primary care and patients' responses to using
such software in the consultation.23 This study shows that
RAGs could enable general practitioners to be more effective
gatekeepers to genetics services and empower them to reassure the
majority of their patients with a family history of breast and ovarian
cancer who are not at increased genetic risk.
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What is already known on this topic
General practitioners will play an increasing role in providing genetic advice but currently lack the skills to be effective gatekeepers to genetics services Computers have been proposed as a way of supporting primary care in this new task What this study addsRAGs, a program designed specifically for primary care, resulted in more appropriate management decisions and more accurate pedigrees than both Cyrillic, an established pedigree drawing program designed for clinical geneticists, and traditional methods but took an extra 51 seconds per case For general practitioners, RAGs was superior to Cyrillic because it provided more relevant information and had a simpler interface Computer support could empower general practitioners to reassure patients with a family history of breast or ovarian cancer who are not at increased genetic risk and avoid unnecessary referrals |
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Acknowledgments |
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We thank the general practitioners who took part in this study, and Peter Rose, Anneke Lucassen, and Eila Watson for forming the expert panel.
Contributors: JE, RW, PY, MM, and JA developed the study protocol. JE conducted the intervention. JE, RW, and PY analysed the data. The decision process in RAGs was designed and implemented by JE and DG. AC wrote the RAGs family tree software. JF supported AC and DG in developing the RAGs software and using PROforma. CC developed and adapted Cyrillic. All authors contributed to writing the paper. JE acts as guarantor for the study.
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Footnotes |
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Funding: The Cancer Research Campaign funded this study. JE and JA are funded by the Cancer Research Campaign. RW, MM, PY, and JF are funded by the Imperial Cancer Research Fund. AC and DG are funded by the Economic and Social Research Council and the Imperial Cancer Research Fund.
Competing interests: CC has been paid as a consultant and has been reimbursed for attending conferences by Cherwell Scientific Publishing, which produces Cyrillic. After completion of this study, JE has been paid as a consultant by Cherwell Scientific Publishing.
An extra table detailing the
study's balanced block design appear on the BMJ website
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Appendix: Access to software |
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Top
Abstract
Introduction
Participants and methods
Results
Discussion
Appendix
References
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Cyrillic is available commercially from Cherwell Scientific Publishing (www.cherwell.com). Experience from from the evaluation of RAGs and Cyrillic is being applied to the development of an online genetic risk assessment service that will be available shortly at www.familygenetix.com. Requests for copies of the version of RAGs used in this study should be made to Professor John Fox (jfox{at}acl.icnet.uk).
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References |
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Top
Abstract
Introduction
Participants and methods
Results
Discussion
Appendix
References
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(Accepted 11 May 2000)
© BMJ 2000
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