Machine-Based Expert Recommendations And Insurance Choices Among Medicare Part D Enrollees
M Kate Bundorf1, Maria Polyakova2, Cheryl Stults3
1M. Kate Bundorf ( bundorf@stanford.edu ) is an associate professor of health research and policy at the Stanford University School of Medicine, in California.
Abstract:
Choosing a health insurance plan is difficult for many people, and patient-centered decision support may help consumers make these choices. We tested whether providing a patient-centered decision-support tool-with or without machine-based, personalized expert recommendations-influenced decision outcomes for Medicare Part D enrollees. We found that providing an online patient-centered decision-support tool increased older adults' satisfaction with the process of choosing a prescription drug plan and the amount of time they spent choosing a plan. Providing personalized expert recommendations as well increased rates of plan switching. Many people who could have accessed the tool chose not to, and the characteristics of people who used the tool differed from those who did not. We conclude that a patient-centered decision-support tool providing personalized expert recommendations can help people choose a plan, but different approaches may be necessary to encourage more people to periodically reevaluate their options.
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