The loss of reason in patient decision aid research: Do checklists damage the quality of informed choice interventions?
Introduction
In 1999, two systematic reviews evaluated over 20,000 articles for interventions to support patients’ decision making about treatment or screening choices [1], [2]. Few authors referred to their interventions as decision aids but rather as education resources. Patient decision aids are complex interventions [3] that include several components to help patients make deliberative choices between two or more screening or treatment options; education resources are interventions that provide information to support a service and/or adherence with a recommended option [2], [4]. Today, there are hundreds of resources claiming to be patient decision aids with health service providers, not for profit and commercial organisations investing in a plethora of materials to support patients’ health, illness and treatment choices [5]. However, the utilisation of patient decision aids outside the research context is low [6], [7], the quality and content of interventions claiming to enable patients’ decision making varies enormously [5], [8], [9], [10], and the analysis of leaflets provided by services suggests most developers are unaware of the evidence and guidance on designing interventions to support patients’ choices [11], [12], [13].
Implementing these complex interventions within existing health services requires an active approach, targeting aspects of the systems that organise services, adoption behaviours of health professionals, and expectations of patients [3], [14], [15]. A key implementation strategy of patient decision aid advocates has been to develop, and support the use of, criteria to guide the content, evaluation and implementation of decision aid interventions [2], [4], [16], [17], [18], [19], [20]. The International Patient Decision Aids Standards (IPDAS) Collaboration is an international, cross-disciplinary group who worked together to develop these criteria [19]. A DELPHI technique was used to develop the IPDAS criteria, drawing on the expertise of patient advocates, clinicians, policy makers and researchers working across a range of areas including: patient-centred health policies, communication training for health professionals and service quality, decision sciences applied to health, and patient decision making [5]. The IPDAS collaboration recommend developers consider a range of domains when designing their decision aids, broadly issues around information content and structure (providing accurate information about options, balancing information, presenting probabilities, using plain language, use of different media), and patient assimilation of information (clarifying values, coaching deliberation) [19].
The IPDAS checklist was designed to be used in the same ways as checklists developed in other areas of evidence-based practice [5]. For example CONSORT [21] and PRISMA [22] which are used to guide investigators’ selection of the methods used in their studies, the format for their write-up, and others’ judgement of the rigour of the study. The IPDAS checklist is promoted as a resource to guide those developing patient decision aids on the intervention's content and structure, to provide a process for evaluating the intervention, and a format for disseminating findings [5]. One adaptation of the checklist (CREDIBLE) is used to elicit data from studies evaluating patient decision aid development and effectiveness for synthesis within a systematic review [10], [18]. More recently, IPDASi is being used by others to assess the degree to which developers operationalised and/or adhered to the IPDAS checklist with a view to judging the quality of the intervention and its evaluation [5], [23], [24]. Reviews suggest more patient decision aid developers are using the IPDAS criteria to inform their patient decision aid development and evaluation [10], [23].
Using the IPDAS checklist should mean that interventions designed to help patients make treatment decisions have a comparable level of quality, so reducing variations in health service delivery [20]. However, to use a checklist effectively assumes investigators know what information is pertinent to [22], and have sufficient knowledge to appraise critically [21], the intervention, its evaluation and implementation. There are several reasons why applying the IPDAS checklist critically may be challenging. First, the IPDAS checklist is informed by several theoretical and health service policy areas [19]. As a result there are many criteria to fulfil, and it is implied all need to be met and/or have equal weight in decision facilitation. Second, many of the statements require significant expertise from the decision sciences to operationalise. For example, ‘provide steps to make a decision’, ‘use visual diagrams for present probabilities of outcomes’, present information in a balanced manner enabling people to compare positive and negative features’. Third, the IPDAS checklist was decided upon by expert opinion [15] as much of the evidence-base to underpin each IPDAS domain was weak [19]. Unlike other evidence-based checklists, there is no distillation of evidence to suggest which criteria or technique results in more effective patient decision aids.
It is increasingly common to see the IPDAS checklist referred to as a model or theory [23]. This change in reference from a set of criteria to consider to a checklist to operationalise suggests developers may not have the relevant knowledge to reason critically about its application. Unlike the explanation and elaboration articles supporting CONSORT [21], little has been written to help developers understand the basic science underpinning patient decision aid interventions [19], [25], [26], [27], [28], [29]. The focus of IPDAS dissemination activities has been to increase awareness of patient decision aids’ efficacy to enhance the shared decision making or patient-centred practices of professionals and provide detailed steps on how do it [4], [5], [6], [9], [10], [19], [30], [31], [32], [33], [34], [35]. This article aims to provide a knowledge brokering of concepts [37] to help reduce the knowledge-action gap between health professionals and behavioural scientists, and enable patient decision aid developers to reason critically about their operationalisation of the IPDAS checklist. It discusses concepts from both the social sciences and health services delivery of relevance to patient decision aid interventions and evaluation with references to the evidence and theories that underpin this synthesis.
Section snippets
Translating decision sciences knowledge for patient decision aid applications
Designing patient decision aid interventions is challenging because the expertise required to develop, evaluate and implement them is drawn from several disciplines, for example (a) the basic decision science investigators explaining how individuals make decisions under risk and uncertainty, (b) the decision science investigators that apply the proof of concept studies to health and illness decisions (translational researchers), (c) the biomedical investigators identifying effective treatments,
Discussion
Using the IPDAS checklist to develop and evaluate patient decision aids will reduce variation in the quality of patient information across services. It is also likely that interventions informed by the checklist will be more useful to patients than information provided routinely by services. Developing the IPDAS criteria has been a key activity to bring together experts interested in developing theory-based interventions for use in the applied health setting, assimilating current knowledge and
Conflict of interest
The author knows of no financial or other relationship with people or organizations that have influenced her work inappropriately. For the last 3 years, the author has been employed as an academic at the University of Leeds and received awards and finances congruent with scholarship rather than collusion: fellowships to attend the Dartmouth Summer Institute for Informed Patient Choice; unrestricted grants to support doctoral student and decision aid research; expenses covering the costs of
Acknowledgements
I am grateful to Professor Anne Stiggelbout, University of Leiden, Dr. Dan Matlock, University of Colorado at Denver, and the two referees for providing useful guidance for this very much revised version of the article. I am indebted to those who have debated with me about issues in decision sciences, health psychology, patient–professional practices and research methods for the last 15 years which has informed my understanding of, and research into, this complex area.
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