Implications of Switching Costs for Medicare Premium Support

医疗保险保费支持转换成本的影响

• 批准号: 8620426
• 负责人: ADAM J ATHERLY
• 金额: $ 11.6万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-30 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8620426
• 关键词: Belief; Caring; Characteristics; Competitive Bidding; Data; Data Set; Drug Prescriptions; Effectiveness; Evaluation; Face; Fees; Funding; Goals; Government; Health; Health Planning; Incentives; Individual; Logic; Logit Models; Marketing; Medicare; Modeling; Pharmaceutical Preparations; Policy Analysis; Provider; Rewards; Savings; Services; Structure; Surveys; Time; Translating; Trust; Trustees; base; beneficiary; cost; design; falls; payment; programs; satisfaction

DESCRIPTION (provided by applicant): The overarching goal of this project is to evaluate the extent of switching costs in Medicare health plans to understand whether they are large enough to undermine the ability of competitive markets to function in a premium support context. To do this, we will analyze whether Medicare beneficiaries are sufficiently responsive to changes in health plan premiums and benefits for "premium support" style Medicare reforms to be a viable strategy to control Medicare spending. The Medicare program faces substantial financial challenges over the next several decades. The Medicare Trustees project that the Part A trust fund will become insolvent by 2025 and that the entire program is on an unsustainable spending trajectory. Although there are many different proposals for how to deal with the impending spending crisis, most falls into one of two groups: care redesign and premium support. Care redesign seeks to preserve the basic structure of the existing Fee-For-Service (FFS) model while introducing incentives to provide care more efficiently. The second idea - premium support - has health plans submit "bids" to the government for a basic benefit package. The government uses these bids to set its contribution to premiums. Plans that provide better value are rewarded with high market share, while those that do not are penalized by losing market share. This is the essential logic behind the structure of Medicare Part D prescription drug coverage, a program that has achieved high beneficiary satisfaction and program costs substantially below projections. However, whether this Part D result would translate to a premium support model that included broader coverage is unclear. Although there have been substantial efforts to evaluate the impact of care redesign in Medicare - CMS is currently funding numerous evaluations of care redesigns, such as bundled payment initiatives and Accountable Care Organizations - there has been relatively little effort to evaluate the viability of premium suppor models, despite its prominence as a possible reform option. The project draws data from the Medicare Current Beneficiary Survey, a representative longitudinal dataset. Analytically, we will estimate the magnitude of switching costs using a mixed logit model, observing plan choices over time. We will explicitly model the impact of plan "loyalty" on plan choices, and will allow "loyalty" to be a random coefficient. The random coefficient will allow us to identify not only the mean value of loyalty, but also to identify factors which predict loyalty.

描述（由申请人提供）：本项目的首要目标是评估医疗保险健康计划中的转换成本的程度，以了解它们是否大到足以破坏竞争市场在保费支持环境中发挥作用的能力。要做到这一点，我们将分析医疗保险受益人是否充分响应健康计划保费和福利的变化，以“保费支持”式的医疗保险改革是一个可行的战略，以控制医疗保险支出。医疗保险计划在未来几十年面临着巨大的财政挑战。医疗保险受托人预计，A部分信托基金将在2025年之前破产，整个计划处于不可持续的支出轨道上。尽管对于如何应对即将到来的支出危机有许多不同的建议，但大多数福尔斯都属于两类之一：重新设计护理和保费支持。护理重新设计旨在保留现有收费服务模式的基本结构，同时引入激励措施，以更有效地提供护理。第二个想法-保费支持-有健康计划提交“投标”给政府的基本福利计划。政府利用这些投标来确定其对保费的贡献。提供更好价值的计划将获得更高的市场份额，而那些没有提供更好价值的计划将失去市场份额。这是医疗保险D部分处方药覆盖范围结构背后的基本逻辑，该计划实现了很高的受益人满意度，计划成本大大低于预期。然而，这一D部分的结果是否会转化为包括更广泛覆盖范围的高级支持模式尚不清楚。尽管在评估医疗保险重新设计的影响方面做出了巨大努力- CMS目前正在资助许多对医疗重新设计的评估，如捆绑支付倡议和责任医疗组织-但在评估保费支持模式的可行性方面所做的努力相对较少，尽管其作为一种可能的改革选择的重要性。该项目从医疗保险当前受益人调查中提取数据，这是一个具有代表性的纵向数据集。在分析上，我们将使用混合logit模型估计转换成本的大小，随着时间的推移观察计划选择。我们将明确模拟计划“忠诚度”对计划选择的影响，并允许“忠诚度”是一个随机系数。随机系数将使我们不仅能够识别 平均值的忠诚度，而且还确定预测忠诚度的因素。