, D. (2009). Decision aids for people facing health treatment or screening decisions (Review). Cochrane Database of Systematic Reviews, (3), [CD001431].

This review is published as a Cochrane Review in the Cochrane Database of Systematic Reviews 2017, Issue 4. Cochrane Reviews are regularly updated as new evidence emerges and in response to comments and criticisms, and the Cochrane Database of Systematic Reviews should be consulted for the most recent version of the Review.

Hip fractures result in significant mortality, morbidity, and costs. The estimated lifetime cost for all hip fractures in the United States in 1997 likely exceeded $20 billion. These results emphasize the importance of current and future interventions to decrease the incidence of hip fracture.

ObjectivesTo describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids).DesignScale development study, involving construct, item and scale development, validation and reliability testing.SettingThere has been increasing use of decision support technologies – adjuncts to the discussions clinicians have with patients about difficult decisions. A global interest in developing these interventions exists among both for-profit and not-for-profit organisations. It is therefore essential to have internationally accepted standards to assess the quality of their development, process, content, potential bias and method of field testing and evaluation.MethodsScale development study, involving construct, item and scale development, validation and reliability testing.ParticipantsTwenty-five researcher-members of the International Patient Decision Aid Standards Collaboration worked together to develop the instrument (IPDASi). In the fourth Stage (reliability study), eight raters assessed thirty randomly selected decision support technologies.ResultsIPDASi measures quality in 10 dimensions, using 47 items, and provides an overall quality score (scaled from 0 to 100) for each intervention. Overall IPDASi scores ranged from 33 to 82 across the decision support technologies sampled (n = 30), enabling discrimination. The inter-rater intraclass correlation for the overall quality score was 0.80. Correlations of dimension scores with the overall score were all positive (0.31 to 0.68). Cronbach's alpha values for the 8 raters ranged from 0.72 to 0.93. Cronbach's alphas based on the dimension means ranged from 0.50 to 0.81, indicating that the dimensions, although well correlated, measure different aspects of decision support technology quality. A short version (19 items) was also developed that had very similar mean scores to IPDASi and high correlation between short score and overall score 0.87 (CI 0.79 to 0.92).ConclusionsThis work demonstrates that IPDASi has the ability to assess the quality of decision support technologies. The existing IPDASi provides an assessment of the quality of a DST's components and will be used as a tool to provide formative advice to DSTs developers and summative assessments for those who want to compare their tools against an existing benchmark.

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Background. There is growing interest in shared medical decision making among patients, physicians, and policy makers. This requires patients to interpret increasing amounts of medical information, much of which is uncertain. Little is known about the optimal approaches to or outcomes of communicating uncertainty about the risks and benefits of treatments. Methods. The authors reviewed the literature on various issues related to uncertainty in decision making: conceptualizing uncertainty, identifying its potential sources, assessing uncertainty, potential methods of communicating uncertainty, potential outcomes of communicating uncertainty, and current practices and recommendations by expert groups on communicating uncertainty. Results. There are multiple sources of uncertainty in most medical decisions. There are conceptual differences in how researchers define uncertainty and its sources, as well as in its measurement. The few studies that have assessed alternate means of communicating uncertainty dealt mostly with presenting uncertainty about probabilities. Both patients' and physicians' interpretation of and responses to uncertainty may depend on their personal characteristics and values and may be affected by the manner in which uncertainty is communicated. Conclusions. Research has not yet identified best practices for communicating uncertainty to patients about harms and benefits of treatment. More conceptual, qualitative, and quantitative studies are needed to explore fundamental questions about how people process, interpret, and respond to various types of uncertainty inherent in clinical decisions.

BackgroundConsensus guidelines have recommended that decision aids include a process for helping patients clarify their values. We sought to examine the theoretical and empirical evidence related to the use of values clarification methods in patient decision aids.MethodsBuilding on the International Patient Decision Aid Standards (IPDAS) Collaboration’s 2005 review of values clarification methods in decision aids, we convened a multi-disciplinary expert group to examine key definitions, decision-making process theories, and empirical evidence about the effects of values clarification methods in decision aids. To summarize the current state of theory and evidence about the role of values clarification methods in decision aids, we undertook a process of evidence review and summary.ResultsValues clarification methods (VCMs) are best defined as methods to help patients think about the desirability of options or attributes of options within a specific decision context, in order to identify which option he/she prefers. Several decision making process theories were identified that can inform the design of values clarification methods, but no single “best” practice for how such methods should be constructed was determined. Our evidence review found that existing VCMs were used for a variety of different decisions, rarely referenced underlying theory for their design, but generally were well described in regard to their development process. Listing the pros and cons of a decision was the most common method used. The 13 trials that compared decision support with or without VCMs reached mixed results: some found that VCMs improved some decision-making processes, while others found no effect.ConclusionsValues clarification methods may improve decision-making processes and potentially more distal outcomes. However, the small number of evaluations of VCMs and, where evaluations exist, the heterogeneity in outcome measures makes it difficult to determine their overall effectiveness or the specific characteristics that increase effectiveness.

PtDAs improve decision quality and the decision process's measures of feeling informed and clear about values; however, the size of the effect varies across studies. Several IPDAS decision process measures have not been used. Future trials need to use a minimum data set of IPDAS evaluation measures. The degree of detail PtDAs require for positive effects on IPDAS criteria should be explored.