Decision tool to improve the quality of care in rheumatoid arthritis

Clarifying values: an updated review

BACKGROUND

Consensus 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.

METHODS

Building 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.

RESULTS

Values 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.

CONCLUSIONS

Values 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.

Shared decision making and patient decision aids: knowledge, attitudes, and practices among Hawai'i physicians

As the health care field moves toward patient-centered care (PCC), increasing emphasis has been placed on the benefits of patient decision aids for promoting shared decision making (SDM). This study provides a baseline measure of knowledge, attitudes, and practices (KAP) among Hawai'i's physicians with respect to patient decision aids (DAs). Physicians throughout the State of Hawai'i were invited to complete a survey assessing their knowledge, attitudes, and practices with respect to the clinical use of DAs. One hundred and seventy four valid surveys were analyzed. Reported awareness and use of DAs were low, but recognition of the benefits of SDM and openness to the use of DAs were very high. The leading perceived barriers to the implementation of DAs were lack of awareness, lack of resources, and limited physician time to learn about DA technology. However, a significant majority of the respondents reported that DAs could empower patients by improving knowledge (88%), increasing satisfaction with the consultation process (81%), and increasing compliance (74%). Among physicians currently employing DAs, use of brochures or options matrix sheets was the most common aid tool. However, leading recommended DA formats were paper-based brochures for clinic use (75%) and interactive online website programs for outside clinic use (73.5%). Given growing emphasis on the PCC model and the recognized desire of many patients to participate in the medical decision making process, positive responses toward SDM and the use of DAs by Hawai'i physicians are promising.

Developmental reversals in risky decision making: intelligence agents show larger decision biases than college students

Intelligence agents make risky decisions routinely, with serious consequences for national security. Although common sense and most theories imply that experienced intelligence professionals should be less prone to irrational inconsistencies than college students, we show the opposite. Moreover, the growth of experience-based intuition predicts this developmental reversal. We presented intelligence agents, college students, and postcollege adults with 30 risky-choice problems in gain and loss frames and then compared the three groups' decisions. The agents not only exhibited larger framing biases than the students, but also were more confident in their decisions. The postcollege adults (who were selected to be similar to the students) occupied an interesting middle ground, being generally as biased as the students (sometimes more biased) but less biased than the agents. An experimental manipulation testing an explanation for these effects, derived from fuzzy-trace theory, made the students look as biased as the agents. These results show that, although framing biases are irrational (because equivalent outcomes are treated differently), they are the ironical output of cognitively advanced mechanisms of meaning making.

Communicating Numerical Risk: Human Factors That Aid Understanding in Health Care

In this chapter, we review evidence from the human factors literature that verbal and visual formats can help increase the understanding of numerical risk information in health care. These visual representations of risk are grounded in empirically supported theory. As background, we first review research showing that people often have difficulty understanding numerical risks and benefits in health information. In particular, we discuss how understanding the meanings of numbers results in healthier decisions. Then, we discuss the processes that determine how communication of numerical risks can enhance (or degrade) health judgments and decisions. Specifically, we examine two different approaches to risk communication: a traditional approach and fuzzy-trace theory. Applying research on the complications of understanding and communicating risks, we then highlight how different visual representations are best suited to communicating different risk messages (i.e., their gist). In particular, we review verbal and visual messages that highlight gist representations that can better communicate health information and improve informed decision making. This discussion is informed by human factors theories and methods, which involve the study of how to maximize the interaction between humans and the tools they use. Finally, we present implications and recommendations for future research on human factors in health care.

Incorporating patients' preferences into medical decision making

Current models of care emphasize the importance of including patients' values in the decision-making process. This is particularly important for decisions for which there are few data supporting a clear strategy or treatment choice. Constructing preferences for complex decisions requires that patients be able to consider multiple trade-offs between specific risks and benefits. Several marketing research techniques have been recently applied to heath care settings to facilitate this process. Most can be programmed to generate patients' preferences or priorities, which can then be used to improve patient-physician communication. In this article, we will describe some of the currently available approaches that have been successfully used in the health care setting. We provide case examples to illustrate the potential value of adopting each of these approaches in clinical practice.