School of Management is delighted to welcome Fernanda Bravo, UCLA Anderson to host a research seminar discussing: 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 o 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 US. We observe that the average health status in a state is a source of the 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.
Fernanda Bravo is an assistant professor in Decisions, Operations, and Technology Management at UCLA Anderson School of Management. Her research interests include service operations management and healthcare policy design and management. Her work centers around three dimensions: (i) Designing healthcare policy to align incentives, (ii) Fostering healthcare innovation through market design, and (iii) Supporting decision-making within health systems via data-driven models. These three areas are crucial to the long-term success of healthcare reform in the U.S. by reducing inefficiency and improving patient health—yet they involve subtle and counter-intuitive interactions. Poorly designed policies aimed at reducing hospital inefficiencies, for example, might unintentionally incentivize physicians to provide less care, ultimately hurting patients. Similarly, over-regulating drug development to ensure patient safety might unintentionally stifle technological innovation. She examines these subtle effects by combining elements from game theory, queuing theory, and optimization to quantify and characterize the most critical trade-offs. The insights derived from her research can guide both policymakers and private stakeholders as they seek to better contract for services, promote new medical innovations, and allocate scarce resources.