初级保健第一倡议:对护理提供和结果的影响

Elodie Adida, Fernanda Bravo
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引用次数: 0

摘要

问题定义:医疗保险和医疗补助服务中心于2021年1月启动了初级保健优先(PCF)计划。该倡议以以前的创新支付模式为基础,旨在鼓励重新设计初级保健服务,包括新的提供模式,如远程保健。为实现这一目标,该倡议将按人头支付和按服务收费(FFS)相结合,并包括与服务质量和健康结果相关的基于绩效的调整。我们分析了由这种新的支付系统驱动的模型,以及它对不同利益相关者的影响,并得出如何设计它以达到最佳结果的见解。方法/结果:我们提出了一个分析模型,该模型捕捉了患者在健康复杂性、提供者选择的护理提供模式(转介给专家、亲自就诊或远程护理)和服务质量(健康结果和等待时间)方面的异质性。我们分析了在FFS和PCF下提供者对护理提供模式的决策,并研究了PCF是否可以设计为产生社会最优结果。我们分析了在PCF下患者、支付方和提供者的情况,并表明在许多情况下,PCF可以设计为产生社会最优结果。我们对美国14个州的模型进行了数值校准。我们观察到,一个州的平均健康状态是异质性的来源,这对PCF的性能至关重要。我们发现,由当前PCF实施驱动的模型导致转诊护理的采用过多,而远程护理的采用过少。此外,平均健康状况较差的州可能比基线(低)人均水平下的社会最佳护理使用更多的面对面护理。此外,依赖于高水平的人头导致很少采用亲自护理。管理意义:通过揭示PCF如何影响患者、付款人和提供者,我们的结果具有卫生政策意义。根据目前基于业绩的调整,应优先考虑低水平的人均收入。PCF有可能被设计成实现社会最优结果。但是,每次就诊的费用可能需要根据当地人口的健康状况进行调整。补充材料:在线附录可在https://doi.org/10.1287/msom.2023.1207上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Primary Care First Initiative: Impact on Care Delivery and Outcomes
Problem definition: The Centers for Medicare & Medicaid Services launched the Primary Care First (PCF) initiative in January 2021. The initiative builds upon prior innovative payment models and aims at incentivizing a redesign of primary care delivery, including new modes of delivery, such as remote care. To achieve this goal, the initiative blends capitation and fee-for-service (FFS) payments and includes performance-based adjustments linked to service quality and health outcomes. We analyze a model motivated by this new payment system, and its impact on the different stakeholders, and derive insights on how to design it to reach the best possible outcome. Methodology/results: We propose an analytical model that captures patient heterogeneity in terms of health complexity, provider choice of care-delivery mode (referral to a specialist, in-person visit, or remote care), and quality of service (health outcomes and wait time). We analyze the provider decision on the mode of care delivery under both FFS and PCF and study whether PCF can be designed to yield a socially optimal outcome. We characterize analytically when patients, payer, and providers are better off under PCF and show that, in many cases, PCF can be designed to yield a socially optimal outcome. We numerically calibrate our model for 14 states in the United States. We observe that the average health status in a state is a source of heterogeneity that crucially drives the performance of PCF. We find that the model motivated by the current PCF implementation results in too much adoption of referral care and too little adoption of remote care. In addition, states with poor average health status may use more in-person care than socially optimal under a baseline (low) level of capitation. Moreover, relying on high levels of capitation leads to low adoption of in-person care. Managerial implications: Our results have health policy implications by shedding light on how PCF might impact patients, payer, and providers. Under the current performance-based adjustments, low levels of capitation should be preferred. PCF has the potential to be designed to achieve socially optimal outcomes. However, the fee per visit may need to be tailored to the local population’s health status. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1207 .
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