Evaluating the Presence of Cognitive Biases in Health Care Decision Making: A Survey of U.S. Formulary Decision Makers

BACKGROUND: Behavioral economics is a field of economics that draws on insights from psychology to understand and identify patterns of decision making. Cognitive biases are psychological tendencies to process information in predictable patterns that result in deviations from rational decision making. Previous research has not evaluated the influence of cognitive biases on decision making in a managed care setting. OBJECTIVE: To assess the presence of cognitive biases in formulary decision making. METHODS: An online survey was conducted with a panel of U.S. pharmacy and medical directors who worked at managed care organizations and served on pharmacy and therapeutics committees. Survey questions assessed 4 cognitive biases: relative versus absolute framing effect, risk aversion, zero-risk bias, and delay discounting. Simulated data were presented in various scenarios related to adverse event profiles, drug safety and efficacy, and drug pricing for new hypothetical oncology products. Survey questions prompted participants to select a preferred drug based on the information provided. Survey answers were analyzed to identify decision patterns that could be explained by the cognitive biases. Likelihood of bias was analyzed via chi-square tests for framing effect, risk aversion, and zero-risk bias. The delay discounting section used a published algorithm to characterize discounting patterns. RESULTS: A total of 35 pharmacy directors and 19 medical directors completed the survey. In the framing effect section, 80% of participants selected the suboptimal choice in the relative risk frame, compared with 38.9% in the absolute risk frame (P < 0.0001). When assessing risk aversion, 42.6% and 61.1% of participants displayed risk aversion in the cost- and efficacy-based scenarios, respectively, but these were not statistically significant (P = 0.27 and P = 0.10, respectively). In the zero-risk bias section, results from each scenario diverged. In the first zero-risk bias scenario, 90.7% of participants selected the drug with zero risk (P < 0.001), but in the second scenario, only 32.1% chose the zero-risk option (P < 0.01). In the section assessing delay discounting, 54% of survey participants favored a larger delayed rebate over a smaller immediate discount. A shallow delay discounting curve was produced, which indicated participants discounted delayed rewards to a minimal degree. CONCLUSIONS: Pharmacy and medical directors, like other decision makers, appear to be susceptible to some cognitive biases. Directors demonstrated a tendency to underestimate risks when they were presented in relative risk terms but made more accurate appraisals when information was presented in absolute risk terms. Delay discounting also may be applicable to directors when choosing immediate discounts over delayed rebates. However, directors neither displayed a statistically significant bias for risk aversion when assessing scenarios related to drug pricing or clinical efficacy nor were there significant conclusions for zero-risk biases. Further research with larger samples using real-world health care decisions is necessary to validate these findings.