Computerized Genetic Risk Assessment and Decision Support in
Primary Care
Andrew S. Coulson1, David W. Glasspool1, John Fox1 and Jon Emery2
1. Imperial Cancer Research Fund, Advanced Computation Laboratory, PO Box 123, London WC2A
3PX.
2. Imperial Cancer Research Fund, General Practice Research Group, Division of Public Health and
Primary Health Care, Institute of Health Sciences, Old Road, Headington, Oxford OX3 7LF.
Correspondence to Andrew Coulson, Advanced Computation Laboratory, Imperial Cancer Research
Fund, PO Box 123, London WC2A 3PX. Email: asc@acl.icnet.uk.
This research was supported by an award from the UK Economic and Social Research Council (award
no L127251011) under the Cognitive Engineering Programme. Jon Emery is supported by the Cancer
Research Campaign.
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Abstract
Public awareness of the availability of genetic testing threatens to put severe strain upon genetics
clinics in the near future. General practitioners (GPs) could help avert this problem by making an initial
genetic risk assessment and acting as gatekeepers to specialist services. However, studies in the United
Kingdom suggest that few GPs feel they have the requisite skills for taking family history details and
making an appropriate referral decision. They are also poorly served by computer-based pedigree
programs, which do not cater to the specific needs of a general practice consultation.
To address these issues, a new computer application called RAGs (Risk Assessment in Genetics)
has been designed. The system allows a doctor to create family trees and assess genetic risk of breast
cancer. RAGs possesses two features that distinguish it from similar software: (a) a user-centred
design, which takes into account the requirements of the doctor-patient encounter; (b) risk reporting
using qualitative evidence for or against an increased risk, which the authors believe to be more useful
and accessible than numerical probabilities are. In that the system allows for any genetic risk guideline
to be implemented, it can be used with all diseases for which evaluation guidelines exist. The software
may be easily modified to cater for the amount of detail required by different specialists.
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Introduction
One of the results of the revolution in molecular genetics is the increasing availability of tests for
the presence of genetic abnormalities which predispose certain individuals to contracting particular
diseases. To date, genetic markers for over 50 diseases have been identified, and tests are available or
being developed for conditions such as cystic fibrosis, Tay-Sachs, Huntington’s, certain forms of
Alzheimer’s and muscular dystrophy, and various rare cancers such as retinoblastoma, Wilms’ tumour
and Li-Fraumeni syndrome. Predisposing genes for more common cancers have also been located, such
as those for breast cancer (the BRCA1 and BRCA2 genes) and certain forms of colon cancer (MLH1,
MSH2).
Coupled with these advances is the increased media attention upon genetic testing, which has
resulted in a heightened awareness of the subject by the general population. Such public knowledge,
although desirable, is likely to create a steady growth in the demands for genetic screening 1. In that
there are only one or two consultant geneticists per million people in the UK 2, this increase threatens to
put considerable strain upon genetics clinics in the near future. Much of the problem here will stem
from clinics’ having to deal with people who are at low genetic risk, yet who have still been referred
because one or two members of their family had the disease in question3.
The situation is further compounded by the current unreliability of genetic screening. Direct
mutation testing is available for the genes listed above, but interpretation of the test results is
complicated by the large number of mutations in some of these genes (e.g. BRCA1 / BRCA2) and by
uncertainty about their clinical meaning4. Thus in the UK for example, where as many as 30,000
women are estimated to carry a mutation in BRCA1, general population screening may not at present
constitute a responsible course of action.
There is, however, a simple practical solution to the problem of restricting advanced genetic
services only to appropriate members of the population. This involves all patients being properly
evaluated in primary care, with general practitioners (GPs) acting as the gatekeepers to specialist
services. In such cases, doctors would examine family histories in order to identify those for whom
genetic testing may be worthwhile5. It would appear that GPs accept this gatekeeper role in genetics,
believing it is appropriate for them to take detailed family pedigree information in order to make the
relevant referral decisions6 7 8.
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Initially therefore, this whole state of affairs seems promising. An increased public demand for
genetic risk evaluation will mean a greater probability of identifying those who are genuinely at risk.
At the same time, GPs acting as the first point of contact will reduce the pressure on genetics clinics by
filtering out obviously low risk cases. In addition, the use of family pedigree analysis can offset the
current uncertainty associated with large scale indiscriminate genetic testing.
A major barrier to this process, however, is that most GPs are unfamiliar with genetic risk
assessment and are consequently unprepared to provide such a service for their patients. Emery et al. 7,
for example, found that even doctors who had attended courses on cancer genetics felt themselves to be
poor at evaluating genetic risk and were uncomfortable doing so. GPs admitted that their information
gathering techniques were often incomplete and haphazard, and that they did not have the skills to draw
proper pedigrees. There was also concern about what could be termed “guideline chaos”: practitioners
were inundated with paper guidelines of varying quality, which even if retrieved at the appropriate time
would only serve to confuse the risk assessment process. As a result of such problems, GPs would
either (a) refer all patients, (b) assess risk using a simple heuristic based on an incomplete recall of
referral guidelines, or (c) simply reassure patients and do nothing. None of these actions could be said
to be desirable ‘gatekeeping’ behaviours, but practitioners were usually left with little choice. It has
also been noted that GPs may be unwilling to do genetic risk assessment because of the sheer length of
time involved in constructing a pedigree, evaluating the results and giving advice 8 9.
Computerized Assistance
Suchard et al.8 concluded that the problems of inadequate genetic expertise and time pressures on
GPs could be alleviated by “practice-enabling” strategies10, such as the use of computerized aids.
Software that can both draw pedigrees and assess genetic risk therefore has the potential to restore a
competent gatekeeping role for GPs in this field of medicine. In our view, designing such a system for
practitioners entails thinking about at least two factors that are not addressed by current genetics
software: (a) an appropriate user-interface design; (b) an effective means of communicating risk and
uncertainty.
Appropriate user-interface design.
Given the time pressures upon GPs, it is unreasonable to expect them to have to deal with a
complex piece of software in order to create family trees and make genetic risk assessments. In
addition, although demand for genetic advice may increase in the future, currently only one to two
patients per month present to a GP about their family history of a common disease 11. Therefore, since a
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genetic risk evaluation program is unlikely to be used very often, it must be simple enough to require as
little relearning as possible.
Here existing pedigree-drawing software is inappropriate12. Systems such as Cyrillic13 and
Progeny14, for example, are excellent state-of-the-art commercial pedigree-drawing packages.
However, these and similar applications are primarily designed as tools for professional geneticists, and
thus have a full complement of menu items and menu icons which require familiarization over time.
The use of such systems by GPs is impractical: practitioners simply do not have the time to learn and
continually top up their skills on complex applications that will only be accessed relatively rarely. Time
pressure on GPs during consultations also necessitates an application that is quick to use.
For these reasons, we view the appropriate software as requiring a design and presentation that is
easily comprehended, affords fast (re)learning and allows the rapid construction of pedigree charts.
Effective risk communication.
A major issue in the design of decision support software is the notorious difficulty of effective
communication about risk and uncertainty. People apparently find uncertainty information difficult to
use. We believe that this is because they do not use probability theory when making everyday
decisions, while risk is generally expressed in terms of numerical probability values (by programs such
as Cyrillic, for example). Instead, people may think more naturally in terms of arguments for or against
particular courses of action.
Degrees of risk and uncertainty may thus be more easily comprehensible (and more readily related
to appropriate action) when numerical values are augmented with or replaced by qualitative arguments
or ‘reasons to believe’ alternative possibilities15 16. Argumentation17 18 19 is a qualitative logical
procedure that allows decisions to be made by weighing up arguments for or against a particular
proposition. This powerful and formally well-developed technique for risk assessment in the absence of
precise numerical estimates of uncertainty has already proved its worth in a number of practical
applications20, including drug prescription21 and medical imaging22. The use of argumentation can
allow a decision support system to communicate in a more naturalistic way about degrees of
uncertainty.
We now describe an application designed to meet the deficiencies in current genetic risk software
outlined above.
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Overview of the RAGs Software
RAGs (Risk Assessment in Genetics) is a decision support application that is part of a larger
medical decision making system (“PROforma”) being developed at the ICRF. RAGs is designed to
assist general practitioners in assessing and communicating risk information to women who are worried
about their genetic risk of breast cancer. The software allows the user to construct a pedigree diagram
of the patient’s family, incorporating information on the known incidence of cancers. This pedigree
information is evaluated via a risk calculation protocol that assesses genetic risk level, makes
recommendations for patient management and provides an argument-based explanation for its
conclusions. The specific program features are outlined below.
Data entry.
Relevant information for all family members is entered via a standard data entry form (Figure 1).
Shaded fields on the form indicate information which is required before a risk assessment can be made.
The user is prevented from adding a person to the tree until all such information is entered.
Family tree icons.
Once a person’s information has been entered, a representative icon appears in a graphics window.
Icons are colour coded according to cancer type, with colours mixed appropriately if a person has more
than one form of cancer. Two types of pedigree representation are available. The “Standard”
representation consists of ‘small people’ icons which take patient sensitivity into account, e.g. by not
having lines drawn across icons for deceased relatives. The alternative, “Expert” representation uses
standard genetic pedigree symbols.
Building the tree.
Family members are added by clicking on any of the person icons currently on the screen. A form is
presented that gives the user options to change that person’s details, add family members or remove
that person from the pedigree. When a family member is to be added, the relevant data entry form
appears. In this way one can quickly create an entire pedigree.
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Figure 1: Standard data entry form in RAGs.
Risk assessment and communication.
RAGs evaluates genetic risk for a given patient by using the PROforma argumentation-based
software system20 23 24 25. This is a generic technology for implementing clinical decision support and
‘intelligent’ clinical guidelines. For the present version of RAGs, a guideline was devised for
evaluating the genetic risk of breast cancer in women. The protocol is expressed as a set of 23 rules,
each of which relates to a person’s increased or decreased genetic risk. For example:

Each first degree relative (i.e. parent, child or sibling) with breast cancer increases the
presenting patient’s genetic risk.
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
Genetic risk is decreased if the presenting patient is over 40 and has not yet developed
cancer.
The rules allow an overall risk score to be computed. Based on this score a patient is put into a low,
moderate or high genetic risk category, and the appropriate referral advice is given, specifically:

Low risk: patient can be reassured and managed in primary care

Moderate risk: refer to breast clinic

High risk: refer to clinical geneticist
Both the assignment of risk categories and the referral advice are, like the guideline, components of the
program that can be altered as required.
A sensitivity analysis of the system was performed by comparing the risk assignments in RAGs
with equivalent assignments based on values given by Cyrillic13, which calculates the genetic risk of
breast cancer as a numerical probability using the Claus dataset26. In all 50 test cases, RAGs agreed
with Cyrillic in its assignment of patients into ‘low’, ‘moderate’ and ‘high’ genetic risk categories.
Figure 2 shows the family tree for a hypothetical patient, Karen, after a risk assessment has been
performed. RAGs computes a risk score for every possible path of inheritance and then chooses the
highest-risk path on which to base its decision. This path is highlighted in the program.
Some of the results of the risk assessment are also displayed in the figure. Three kinds of
information are available:
1.
General Explanation, which gives a standard overview of what the software does and
how it performs its risk assessment.
2.
Referral Advice, which provides a short, simple referral recommendation based upon the
risk calculation.
3.
Reasons for Advice, the text for which is shown in the figure. This button presents the
user with an explanation of how the system came to its decision. It does so by providing
the arguments for and against believing a cancer-predisposing gene to be present in the
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Figure 2: Explanation generated by RAGs for its risk assessment and referral advice.
patient’s family. These arguments can be directly cross-referenced with the pedigree
diagram.
The user may continue to alter the tree after a risk assessment has been calculated, and then request
a new risk assessment if desired.
Discussion
There are a number of pedigree drawing and genetic risk assessment programs available
commercially, but RAGs has certain features that distinguish it from similar software.
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Interface Design
As noted in the Introduction, not all GPs are adept at the use of computers, yet most pedigree
software tends to have a large array of options, usually represented by menu items or menu icons. In
contrast, the RAGs system has been designed to keep choices and procedures to a minimum, with those
available always indicated on screen. The application can be mastered within a few minutes even by
those with minimal computer experience, and requires little investment in time either for initial
learning or for re-familiarization. Such features are essential for infrequently used software.
There are two more positive effects of this simplicity. First of all, it will help the doctor maintain an
air of competence. Insofar as the software itself is not contributing an added level of confusion and
stress to the consultation, the GP can relax and focus his/her attention on the patient. This in turn gives
the patient an increased confidence in the way the doctor is addressing her concerns. Secondly, the
simple and informal nature of the system encourages practitioners to share the screen with their
patients. This activity appears to promote a sense of joint effort and shared understanding 7, and our
own experiences in trials with volunteer GPs suggest that it is also likely to enhance the quality of the
data entered.
Effective program development. The RAGs system is being refined through feedback by GPs, who
have been using it in mock consultations with actors taking the part of patients. This method of
program enhancement by testing it in a real work setting has been termed an “action design” approach
to software development27.
The technique has already raised issues relating to data input and presentation that would have been
missed had we just requested a simple ‘wish list’ of features 7. For example, a prototype version had the
risk information present itself on screen as soon as the user clicked on the “Create Report” button. This
feature proved to be undesirable in the mock consultations, as it did not afford GPs the opportunity to
absorb the information before discussing it with the patient, resulting in the loss of a relaxed and
empathic doctor-patient interaction. The current software version simply gives a message that the
report is ready, and waits for one of the three information buttons (Figure 2) to be clicked. Thus, once
the practitioner or qualified assistant has entered the family tree details, the results can be accessed in a
more controlled fashion. For example, some GPs might prefer to read the report in the absence of the
patient and discuss the results in a second consultation. The doctor therefore has the chance to adopt
the appropriate attitude in light of the results, and talk about them in an informed manner. To our
knowledge, other programs in general do not take into account factors such as patient sensitivity in
their design.
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Risk Assessment and Reporting
The RAGs software centres around a qualitative reason-based decision procedure. This allows the
outcome of an assessment to be communicated in what we believe to be a more useful form than
simple numerical risk estimates.
The most immediate benefit of such a process is that the clinician and the patient can understand
how the program is arriving at its conclusions, and even have the opportunity to take issue with the
presented arguments. Unlike other genetic risk assessment programs, therefore, RAGs allows its users
to make an informed choice as to what to do with the advice it gives.
Paradoxically such advantages may be particularly clear in the case of those who are not at
increased risk due to genetic factors. Breast cancer is sufficiently common that many women have a
number of affected relatives, yet genetic predisposition is relatively rare. Most women approaching
their GPs with concerns about genetic predisposition are thus unlikely to be at increased risk. In such
situations it can be difficult to reassure the patient, and here the argumentation-based explanations
provided by the RAGs system may be considerably more effective than a simple predicted risk level.
The fact that one can see what arguments the program is using may have further, more general
benefits. For example, different national or international authorities may employ different guidelines
for genetic risk, making it even more imperative that the user knows exactly what rules are being used
in an assessment. In that the PROforma risk assessment part of the software is a separate system, it can
easily be adapted to implement whatever guideline the user wishes. As a result, any required changes to
a guideline are simple and quick.
Future Developments
Emery et al.7 found that GPs’ responses to the RAGs system as a whole were positive.
Nevertheless, a number of improvements and refinements were suggested. In particular, unpublished
results from this study revealed that practitioners wanted RAGs to function at two levels, depending on
the type of care to be provided and the amount of information the patient wanted:
1.
‘Gatekeeper’ mode - where patients are triaged into risk categories and are given the
appropriate advice. This is what RAGs currently does, with its main purpose being to allow
the GP to identify those patients that can be reassured and those who require referral to
specialist services.
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2.
‘Primary care geneticist’ mode - for GPs who wish to become more involved in genetic
counselling. This would entail the program being capable of providing much more detailed
information than it does at present.
For both these levels, the practitioners still felt it was important to have access to the evidence
supporting the risk assessment and management suggestions.
With regard to the ‘primary care geneticist’ mode of functioning, we are investigating how to adapt
the RAGs program to cater for the needs not only of GPs, but for genetics associates and other specific
groups of users. Changes here may include giving information on screening and prevention, explaining
the role of genetic testing, and providing numerical risk estimates to supplement the argument-based
conclusions. Also as discussed, the implementation of alternative guidelines is very straightforward,
and we are currently looking into producing a version of the program that gives referral advice relating
to colorectal cancer. It is also hoped that all these modifications would be refined in the same way as
with the original system, i.e. as a result of detailed evaluation of the software in an actual clinical
environment.
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