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基于机器的专家建议和医疗保险计划 D 参保人员的保险选择。

Machine-Based Expert Recommendations And Insurance Choices Among Medicare Part D Enrollees.

机构信息

M. Kate Bundorf (

Maria Polyakova is an assistant professor of health research and policy at the Stanford University School of Medicine.

出版信息

Health Aff (Millwood). 2019 Mar;38(3):482-490. doi: 10.1377/hlthaff.2018.05017.

DOI:10.1377/hlthaff.2018.05017
PMID:30830808
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.

摘要

对于许多人来说,选择健康保险计划是一件困难的事情,而以患者为中心的决策支持可能有助于消费者做出这些选择。我们测试了提供以患者为中心的决策支持工具——是否结合基于机器的个性化专家建议——是否会影响医疗保险处方药计划(Medicare Part D)参保者的决策结果。我们发现,提供在线以患者为中心的决策支持工具增加了老年人对选择处方药计划过程的满意度,并增加了他们选择计划的时间。提供个性化专家建议也增加了计划转换率。许多可以使用该工具的人选择不使用,并且使用该工具的人与未使用该工具的人的特征不同。我们的结论是,提供个性化专家建议的以患者为中心的决策支持工具可以帮助人们选择计划,但可能需要采取不同的方法来鼓励更多的人定期重新评估他们的选择。

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