The expected utility framework underlies much research in medical decision making. Because the framework requires decisions to be decomposed into probabilities of states and the values of those states, researchers have investigated the two components separately from each other and from patients' actual decisions. The authors propose that it would be productive to focus more research on the relationships among risk perceptions, outcome valuations, and choices in the same decision makers. They outline exploratory analyses based on two existing national surveys, the Medical Expenditure Panel Survey and the Joint Canada/United States Survey of Health.
"While there are many perceived advantages to this prescriptive approach, there are also criticisms. First, ‘optimal’ options derived from decision analysis are reliant on assumptions, theories and inaccuracies in inputs which mean they may not actually prescribe the best course of action for each patient . Second, the current approaches to decision analysis are typically ‘overt’ to be best course of action, and consequently have been argued to be an extension of paternalism, compromising patient autonomy . "
[Show abstract][Hide abstract] ABSTRACT: Background
Patient decision aids (PtDA) are developed to facilitate informed, value-based decisions about health. Research suggests that even when informed with necessary evidence and information, cognitive errors can prevent patients from choosing the option that is most congruent with their own values. We sought to utilize principles of behavioural economics to develop a computer application that presents information from conventional decision aids in a way that reduces these errors, subsequently promoting higher quality decisions.
The Dynamic Computer Interactive Decision Application (DCIDA) was developed to target four common errors that can impede quality decision making with PtDAs: unstable values, order effects, overweighting of rare events, and information overload. Healthy volunteers were recruited to an interview to use three PtDAs converted to the DCIDA on a computer equipped with an eye tracker. Participants were first used a conventional PtDA, and then subsequently used the DCIDA version. User testing was assessed based on whether respondents found the software both usable: evaluated using a) eye-tracking, b) the system usability scale, and c) user verbal responses from a ‘think aloud’ protocol; and useful: evaluated using a) eye-tracking, b) whether preferences for options were changed, and c) and the decisional conflict scale.
Of the 20 participants recruited to the study, 11 were male (55%), the mean age was 35, 18 had at least a high school education (90%), and 8 (40%) had a college or university degree. Eye-tracking results, alongside a mean system usability scale score of 73 (range 68–85), indicated a reasonable degree of usability for the DCIDA. The think aloud study suggested areas for further improvement. The DCIDA also appeared to be useful to participants wherein subjects focused more on the features of the decision that were most important to them (21% increase in time spent focusing on the most important feature). Seven subjects (25%) changed their preferred option when using DCIDA.
Preliminary results suggest that DCIDA has potential to improve the quality of patient decision-making. Next steps include larger studies to test individual components of DCIDA and feasibility testing with patients making real decisions.
BMC Medical Informatics and Decision Making 08/2014; 14(1):62. DOI:10.1186/1472-6947-14-62 · 1.83 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The quality and safety of health care are under increasing scrutiny. Recent studies suggest that medical errors, practice variability, and guideline noncompliance are common, and that cognitive error contributes significantly to delayed or incorrect diagnoses. These observations have increased interest in understanding decision-making psychology.Many nonrational (i.e., not purely based in statistics) cognitive factors influence medical decisions and may lead to error. The most well-studied include heuristics, preferences for certainty, overconfidence, affective (emotional) influences, memory distortions, bias, and social forces such as fairness or blame.Although the extent to which such cognitive processes play a role in anesthesia practice is unknown, anesthesia care frequently requires rapid, complex decisions that are most susceptible to decision errors. This review will examine current theories of human decision behavior, identify effects of nonrational cognitive processes on decision-making, describe characteristic anesthesia decisions in this context, and suggest strategies to improve decision-making.
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