Why the study?
Selecting an optimal Medicare Part D plan remains challenging, and few eligible beneficiaries switch plans annually despite potential benefits.
Medicare Part D beneficiaries experience frustration with high costs and plan restrictions, highlighting a need for better plan-selection assistance and educational resources.
This is the authors' abstract. We don't add key points for this paper.
Background: A variety of services exit to assist eligible beneficiaries select Medicare Part D insurance plans; however, selecting an optimal plan remains a challenge. While patients would benefit from evaluating and switching their Medicare Part D plan on a yearly basis, few choose to do so. Objective: The objective of this study was to describe the Medicare Part D plan selection experience across all US states. Methods: This was a qualitative analysis using data from a cross-sectional Qualtrics panel survey administered in January 2022. Descriptive statistics were generated for demographic and patient-specific items for individuals who provided open-ended survey item responses. Open-coding and content analysis were used to analyze responses to the open-ended survey item. Results: Overall, 540 responses were received, with the largest number of responses from Florida (11%, 61). A total of 101 respondents (18.7%) of survey respondents provided open-ended comments. Qualitative analysis identified four response categories: Benefit design, Plan information and selection assistance, Plan Switching, and Plan-selection experience. Conclusions: Overall, participants expressed frustrations with high costs and plan restrictions. Many participants needed plan-selection assistance, with some individuals switching plans each year. Recent legislation may address difficulties related to medication costs; however, additional focus on resources and educational interventions may improve the Medicare Part D experience.
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Medicare Part D frustrations suggest need for improved selection assistance; hypothesis-generating in cross-sectional data and leaves open intervention effects.
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Murry et al. (2023) studied this question.
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