Journal of Evaluation in Clinical Practice, 2, 3, 205-21 0

C O N F E R E N C E P R O C E E D I N G S . I I . P r e s e n t a t i o n 1

Overview and critique of judgement and decision making in health care: social and procedural dimensions

Jonathan Chase BA MSc PhD', Rosemary A. Crow MA PhD RGN SCM HVZ and Dawn Lamond RGN BSc3 'Lecturer, Department of Psychology, University of Surrey, Guildford, U K 2Research Professor in Nursing Science, European Institute of Health & Medical Sciences, University of Surrey, Guildford, UK 3Research Fellow, European Institute of Health & Medical Sciences, University of Surrey, Guildford, UK

Correspondence Dr Jonathan Chase Department of Psychology University of Surrey Guildford Surrey GU2 5XH UK

Keywords: decision making, decision theory, health care

Accepted for publication: 30 July 1996

Abstract This paper presents an outline of the scope for the application of decision theory to health care. Firstly, the main approaches to and assumptions of decision theory are discussed. Secondly, health care decision making is reviewed. It is noted that decision theory can be applied to either the health care professional or to the lay person. Applications of decision theory to clinical practice, to the management of care and to resourcing are considered. Thirdly, some areas which would repay further research are identified. These include social processes in individual and group decision making, the tem- poral distribution of outcomes and the development of techniques capable of dealing with the complex and dynamic features of decisions. On the basis of the foregoing, some conclusions are drawn.

Introduction

The aim of this paper is essentially practical and not theoretical. It is not to provide a grand new theory but to consider current practice in the area of health care- related decision making with a view to suggesting some potentially productive future directions. Current practice does, however, include both theory and application. It is also an opportunity to outline a general philosophy that informs the clinical decision- making group in the European Institute of Health & Medical Sciences at the University of Surrey.

This paper will proceed by briefly discussing deci- sion analysis in general. The application of decision analysis to health care will then be outlined. The paper will next consider some areas of decision analysis which could usefully be extended. While the focus of this will be on health care-related decision making, the argument can be generalized.

Decision analysis

Decision analysis has been considered to have three main approaches: normativc, descriptive and pre- scriptive (Bell et al. 1988).

Normative decision analysis

A normative approach tends to be very formal and mathematical and to assume rationality in the deci- sion maker. Nonnative models [such as Subjective Expected Utility Theory (SEUT), Bayes' theorem and hypothetico-deductive models] provide a series of steps stating how one ought to make a decision, given certain assumptions. Normative models may vary in their degree of precision, with SEUT being more precise than the Theory of Reasoned Action (TRA), for example (Ajzen & Fishbein 1980). While there is no necessary link, the more formal theories have tended to be applied to health care professionals and the less formal ones to lay people.

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Descriptive decision analysis

A descriptive approach to decision analysis usually starts from an understanding of human cognitive functioning and examines how people actually make judgements and decisions. The work of Tversky and Kahneman on judgemental heuristics is the best known example of this approach (e.g. Kahneman & Tversky 1973, 1982; Tversky & Kahneman 1983). Unlike with normative theories, rationality is not assumed, although it may provide a benchmark against which actual performance can be evaluated. Descriptive theories may also be used where there is no clear normative model, such as during the initial structuring of the decision. In these cases, the eva- luation of actual strategies is more difficult.

Prescriptive decision analysis

Prescriptive decision analysis is the application of both of the above to the goal of ‘improving’ decision making (either in terms of process or in terms of outcome). Ideally, a prescriptive approach draws on both normative and descriptive theories in order to provide strategies to improve decision making. Often the normative model provides a goal and the descriptive model identifies the constraints within which one develops a process to attain that goal. Work on expert systems and decision support systems are examples of the prescriptive approach. Much of this work is generally seen as applicable to the health care professional rather than the lay person. However, there is no theoretical reason why a prescriptive approach should not be applied to lay people. This would change the question from one of how people make health care-related decisions to one of how people can be helped to make ‘better’ decisions.

Uncertainty in decision analysis and decision making

Uncertainty is fundamental to both decision analysis and decision making but has dominated research in the reduced form of probability. This may again be a consequence of the focus on normative, mathematical models. Recent work in decision analysis in general has taken a broader approach to uncertainty and has also paid greater attention to utility. The analyses of

utility provided by decision theory are very pertinent to issues concerning patient (and other) values.

Within normative theories, the person is usually defined as a rational, selfish, utility-maximizer. Within descriptive theories, rationality is seen as ‘bounded’ (Simon 1955). Indeed, it is the recognition of the constraints and peculiarities of the actual cog- nitive system that underpins the research on heur- istics. Usually the definition of selfish utility is also broadened to give a boundedly rational, loosely self- ish, utility-maximizing person.

Decision making in health care

Health care represents an enormous opportunity for the application of psychology and one that may yield substantial benefits for all concerned, i.e. consumers, resource providers, health care practitioners and psychologists.

Health-related decisions may be made by health care professionals (doctors, nurses, physiotherapists, nutritionists, managers, etc.) or by lay people. Deci- sions relating to health are important both for the individual(s) concerned and for society at large. Health care decisions involve a diversity of activities. Therefore, a range of judgemental and decision pro- cesses and of domains of knowledge, belief and atti- tude are likely to be involved in health care-related decision making. The richness of the decision making is, however, frequently not reflected in the research. This is true for both the lay and the professional person. In the former case, the most common appli- cations use the TRA (or one of its variants such as the Theory of Planned Action) or the Health Belief Model and the emphasis has been on behaviour. In the latter case, other decision theories have been uscd, such as SEUT, Bayes’ theorem or Brunswick’s ‘lens model’ and the emphasis has tended to be on diagnosis. The focus on uncertainty (probability) also detracts from a recognition of the relevance of decision analysis to questions of value (or utility). And yet such questions lie at the heart of much health care decision making, as in the debate on resourcing, for example.

However, the application of decision theory to the health-related behaviours of both groups is increas- ingly common and sophisticated, as evidenced by the formation of various societies, such as the Society for Medical Decision Making, and by the

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presence of (some) texts, such as that of Dowie & Elstein (1 988).

The following areas of health care decision making illustrate this diversity.

Diagnosis/clinical practice

This pertains to decisions made in clinical practice and might be seen as the ‘classic’ health decision. Much of the research has a strongly medical flavour and a consequent focus on clinical diagnosis (i.e. reasoning from effects to causes), within which uncertainty (defined as probability) dominates. Diagnosis is clearly an important activity, worthy of research, yet health care provision involves much more than diag- nostic decision making. The assessment of patient state and the management of care are also very important issues that are not easily addressed within a diagnostic and probabilistic framework. Additionally, the obvious importance of researching professionals’ decision making, i.e. that of the ‘experts’, has led to a focus on the domain-specific knowledge that experts are assumed to possess.

Recently, there has arisen an interest in ‘evidence- based care’. This refers to an attempt to use research findings and decision analysis to improve diagnostic and related treatment decisions. The success of evi- dence-based care requires a decision analytic per- spective as i t is essentially a strongly prescriptive approach, demanding the adoption of normative decision processes. This suggests that constant eva- luation of care is needed to feed the appropriate values (probabilities, test sensitivities, population fre- quencies, etc.) back into the decision process. Failure to do this would result in evidence-based care becoming suboptimal and self-fulfilling - a strait- jacket rather than a lifejacket.

Management of care

I t is clearly the case that much of the activity involved in health care has to do with the manage- ment of care rather than with diagnosis or prognosis. Therefore, i t seems likely that many of the decisions in health care are about the management of care. This is probably true of the majority of roles (both lay and professional) but undoubtedly varies from role to role. Nursing predominantly centres on

managing care rather than diagnosis or prognosis (Crow et al. 1995).

Of course, the social, organizational and cognitive decision processes and the task characteristics involved in managing care may overlap with those involved in diagnosis and prognosis but equally they may not. For example, the management of care may involve the prioritization of actions while diagnosis involves the integration of probabilistic information. Managing care is likely to involve continual (re)as- sessment, using knowledge of the patient’s previous state as a basis for judging change. Diagnoses are more stable.

Resourcing

In recent years, an awareness has developed that decisions about how health care (treatment, research, etc.) should be rationed are inevitable, regarding both individual clinical decisions and policy decisions. However, there is little consensus as to how to address this complex issue, i.e. how such rationing should occur. Clearly this is to some extent a political ques- tion requiring political solutions.

Decision analysis may be useful in two ways regarding resource allocation in health care. Firstly, it can be used to improve decision making and therefore increase the efficient use of resources, thus alleviating demands on resources. Secondly, decision analysis may be used to develop ways of determining resource allocations. In this regard, measures such as the QALY (Quality Adjusted Life years) and the HYE (Healthy years) have been proposed (Johannesson 1994; Gafni & Birch 1995). These approaches tend to use normative models and therefore may not be accurate representations of people’s actual pre- ferences (Kaplan et al. 1993). One could use a descriptive theory such as Kahneman & Tversky’s Prospect Theory as an alternative to these normative theories. QALYs and HYEs also tend to result in a static and unitary value that ignores the possibility of conflict and argument over values.

Structuring decisions

Defining and structuring decisions

The way in which people define and structure deci- sions fundamentally constrains the choices available

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to them. Definitional and structurational processes are thought to predominate in the early stages or phases of decision making. Normative models can help direct and assess these processes, but only after a model has been adopted. Defining the decision requires judgements to be made about what should and should not be considered. Factors such as who is involved in the decision, what time frame the decision relates to and what dimensions of value are to be considered all need to be resolved.

The importance of defining and structuring a decision can be inferred from the research on framing effects in decision analysis and context effects in sur- vey research. Both of these bodies of work show that different presentations of what are formally the same issue may elicit radically different responses (for example, see Vaughan & Seifert 1992 for discussion of environmental and public health risks). However, by and large, the research involves manipulating the structure given to the subject and not directly exam- ining the processes by which the respondent structures that material. Essentially, what is needed is an improved understanding of the processes involved in how people structure ecologically valid ‘decisions’.

Temporality in decision making

Temporal aspects of decisions are particularly important and rarely addressed. For example, select- ing a time horizon for the decision (i.e. a point in time for which one will identify and assess outcomes) is very important. The patterning of positive and nega- tive features associated with different outcomes may vary across time, leading to reversals of preference depending upon which time horizon was used. Com- parisons between surgery and radiotherapy for some cancers show this type of distribution, i.e. that surgery has an initially higher mortality rate but gradually improves relative to radiotherapy. Research is needed to identify the effects of different ways of presenting such information to people.

The stability of preferences across time is a basic assumption of normative decision theories. Yet, peo- ple show considerable lability with regard to pre- ferences. This may be considered a form of incontinence in decision making (Elster 1979) and can result in decisions being made on the basis of inac- curate preferences. Researchers could usefully con-

sider how people can be aided in imagining future states in order better to predict their feelings, values and preferences concerning those states.

The evaluation of future outcomes (usually referred to as ‘discounting’) is also relevant to resourcing decisions. However, discount rates are rarely actually assessed. Instead, some discount rate (varying between zero and one) is imposed arbitrarily.

Taxonomies of decisions

Von Winterfeldt (1980) discusses the use of taxo- nomies of decisions to aid decision makers in the initial structuration stage of the decision making process. He discriminates between taxonomies based upon more concrete, substantive features (reflecting domain specificity) and those based upon more abstract, theoretical ones. Such an approach may also be useful for conceptualizing research, both pro- grammatic and applied. This process may identify potentially fruitful fields for future research and application through the assessment of similarities and differences across various dimensions.

One implication of this would be that individuals may have their own lay taxonomies of decisions or prototypical decision structures. People may possess the appropriate skills but not apply them in an instance due to the particular framing of that instance. For example, research on sexual behaviour in the context of HIV/AIDS often involves the application of the TRA or a variant of this. Yet sexual behaviour may be (indeed frequently is) seen as relating to passion and spontaneity and not rational calculation (Ingham el af. 1992) -the domain of Dionysus and not Apollo. There may be a wilful refusal to apply logic to love. An implication of this is that, in order to change sexual behaviour which exposes people to the risk of con- tracting HIV, one may have to do more than provide infomiation. One may have to evoke a decision frame.

Individualistic slant to decision analysis

Decision theory is individualistic. Even when the focus is on social decision making, the model of the person is essentially that of a distinct unit. The rele- vance of much of the research that has been carried out is therefore undermined by the lack of a social perspective.

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Social factors may affect decision making even in apparently individual contexts, given that the indivi- dual is inherently social. Cognition is bound to a (social) context. Social processes are likely to be especially important in the definition and structuring of the decision for both lay and professional people (perhaps especially for professionals because training is a socialization process for producing consensus in individuals). For example, identification processes may determine the framing of the decision and thus affect the salience of information and the generation of values. Seeing oneself as ‘pro-life’ or ‘pro-choice’ (as Roman Catholic or as feminist, perhaps) may affect the advice a GP gives regarding unwanted pregnancy (Westfall et al. 1991).

Social factors are more obviously present in deci- sions about resource and risk distribution issues (Keeney 1994). I t may be argued that these concerns are essentially economic and political and that they can be left to the operation of the ‘free market’. However, the proponents of the ‘free market’ ignore its origins in social psychological processes (Hodgson 1988). Therefore, the development of techniques for arriving at consensus regarding risk or resource dis- tribution is necessary. Such work involves generating processes which can be used and are accepted as ‘fair’ and producing techniques for eliciting people’s values or utilities. Both cases need to reflect the active gen- eration of value in a social context rather than its passive, given, individual character, as assumed in most economic analyses (especially those deriving from the Austrian School after Hayek).

Process in decision making

The process of decision making, in health care as well as in other settings, has become more widely studied. This focus on process emphasizes change over stabi- lity, generation over retrieval, and interaction with a (social) environment over hermetic individualism. There are two main ways in which this can be done.

Firstly, process may be examined through the use of an appropriate research methodology. Many studies infer process indirectly from outcome measures, while in others process data are gathered directly. ‘Think- aloud’ studies are one way of producing verbal pro- tocols that can, within constraints, provide informa- tion about the cognitive processes that are occurring

during decision making. Ericsson & Simon (1980, 1984) have made considerable theoretical and meth- odological contributions to this area. In appropriate cases, this approach can be used in combination with outcome measures to provide more complete data. This approach might also offer greater opportunities to explore the interaction between general processes and more domain-specific knowledge content.

Secondly and less commonly, process can be examined in the analysis of the data produced through the application of the research methodology. In much research, while a particular theory may be used to determine data collection, its relevance to the analysis is (usually) slight (Weinstein 1993). Theories such as the Health Belief Model, TRA or SEUT may be used to generate a set of variables to be measured. How- ever, a theory such as the TRA or SEUT also provides some specific combinatorial rules for its various component parts (Weinstein 1993). Simply carrying out a multiple regression to identify the factors that are most predictive of the dependent variable is an inadequate test of the model. The data gathered need to be aggregated according to the combinatorial rules of the model and the output of this process should then be investigated in relation to the dependent variables in order to test the model.

Alongside and implicit in the need to examine the process of health care decision making more directly is the need to appreciate the complexity and dynamism of much decision making. One model - whether it be the TRA, SEUT, Bayes’ theorem or any other - will not fully describe, explain or predict decision making. Different theories and models are not necessarily in competition (although they may be) but may be combined in the broad decision process. So, for instance, in order to carry out a Subjective Expected Utility process, one must generate values for prob- abilities and utilities which might be done through Bayesian statistics and/or the operation of various heuristics. This type of integrative research has greater potential and validity than that of the list makers.

Conclusion

Technological, social and political developments have combined to produce enormous potential for the application of decision analysis to health care. This paper has identified some of the ways in which

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decision theory can be used. It has also been argued that research is needed to develop a more social and valid framework for decision theories. Such a frame- work is a prerequisite for the effective application of decision theories. A variety of questions of consider- able theoretical and practical relevance have been noted, in particular the need to develop sound theo- retical and methodological treatments of the temporal and procedural dimensions of decision making.

More research is required in order to assess and evaluate the impact of changes in health care practice. This is needed to support the move towards evidence- based care and should include both changes in pro- fessional practice and programmes to affect lay behaviours. The complex, diverse and dynamic nature of decision making has to be recognized and accounted for. Specific nostrums should not be trea- ted as panaceas. Research on health care decision making needs to maintain strong links with research in other areas and on other types of decision making as well as with general theories of decision making.

Psychologists have a central role in this application. However, in order to fulfil this role, it is necessary to bring some order and integration to the field. Psy- chologists have an unfortunate tendency to employ a profusion of terms for essentially the same phenom- enon. For example, are locus of control, self-efficacy and attributions of success and failure really different phenomena or just slightly different conceptualiza- tions of the same one? A weeding out of some unne- cessary terms would enable researchers to discern commonalities across research areas more clearly. I t might also yield a pay-off in terms of increased inte- gration, i.e. an increased understanding of how dif- ferent processes interact.

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