Hype or Hope? Selection and Performance of Accountable Care Organizations

The performance of pay-for-performance (P4P) models in healthcare has been mixed. While prior studies have explored various population-based payment models, there is a lack of empirical evidence related to selection of high risk, high-reward payment models in the context of value-based healthcare. Further, the performance implications of selection into new types of payment models is not well understood. We study the rollout of Accountable Care Organizations (ACO) under the Medicare Shared Savings Program (MSSP) and identify factors that explain their selection into two-sided risk models, which offer greater rewards as well as penalties. Specifically, we study whether such ACO selection decisions are associated with performance improvements based on their shared cost savings as well as quality of health outcomes. Our longitudinal analysis is based on publicly available Medicare ACO data for the six-year period between 2013 and 2018, and explores the antecedents and consequences of ACO selection into two-sided risk models. We find that ACOs with greater organizational scope, based on their scale, service variety and patient segments, are also more likely to switch to a two-sided risk model. Further, we observe that ACOs that switched into two-sided models exhibit greater savings and marginally higher quality, compared to ACOs that remained in a one-sided risk model. However, our analysis indicates that the initial gains after switching are not sustained over time, as these ACOs exhibit significant reduction in the rate of improvement of shared savings and quality, in the three-year period after switching. Our results indicate that ACOs with superior prior capabilities reap the advantages associated with MSSP incentives, and imply that incentive programs that promote short-term goals help participants who enjoyed greater a priori advantages in terms of their extant resources and capabilities. However, long-term sustainable performance improvements remain an elusive goal, and our research suggests that the incentives in the current ACO program need to be modified to reward improvements in their operational capabilities

Data-driven incentive design in the medicare shared savings program

The Medicare Shared Savings Program (MSSP) was created under the Patient Protection and Affordable Care Act to control escalating Medicare spending by incentivizing providers to deliver healthcare more efficiently. Medicare providers that enroll in the MSSP earn bonus payments for reducing spending to below a risk-adjusted financial benchmark that depends on the provider's historical spending. To generate savings, a provider must invest to improve efficiency, which is a cost that is absorbed entirely by the provider under the current contract. This has proven to be challenging for the MSSP, with amajority of participating providers unable to generate savingsowing to the associated costs. In this paper, we propose a predictive analytics approach to redesigning the MSSP contract with the goal of better aligning incentives and improving financial outcomes from the MSSP. We formulate the MSSP as a principal-agent model and propose an alternate contract that includes a performance-based subsidy to partially reimburse the provider's investment. We prove the existence of a subsidy-based contract that dominates the current MSSP contract by producing a strictly higher expected payoff for both Medicare and the provider. We then propose an estimator based on inverse optimization for estimating the parameters of ourmodel. Weuse a data set containing the financial performance of providers enrolled in the MSSP,which together accounts for 7 million beneficiaries and more than $70 billion inMedicare spending.We estimate that introducing performance-based subsidies to the MSSP can boost Medicare savings by up to 40% without compromising provider participation in the MSSP. We also find that the subsidy-based contract performs well in comparison with a fully flexible nonparametric contract

The Impact of Medicare Insurance Plans upon Healthcare Services Utilization Considering Patients\u27 Characteristics and Their Access to Medical Care

The annual average cost of healthcare for services utilization by a Medicare beneficiary is projected to grow from about $10,000 to over$16,000 by 2023. As an ongoing initiative to address this trend, the federal government contracts with private insurance companies and other entities, called Medicare Advantage Organizations (MAOs), to develop and administer alternative health insurance plans designed to contain service utilization and costs. One feature of some Medicare Advantage plans is the presence of risk-bearing contracts with primary care physician organizations that voluntarily accept financial responsibility for the overall cost of care for patients attributed to them. In this arrangement, the MAO delegates medical care, care management oversight, and discretionary spending authority to the physician organization. For services rendered, the physician organization accepts as payment the surplus or deficit derived from annual budgetary results (as negotiated in their contract with the MAO) rather than the traditional per-encounter or service-specific payments associated with fee-for-service payment schemes. This study uses an extensive and novel data set from the Centers for Medicare and Medicaid Services, as well as third-party sources, to examine how Missouri beneficiary’s attributes (age, gender, race, and health status), presumed financial resources and education, access to doctors and hospitals, and Medicare plan choices help to predict services utilization. We use summary statistics, tests of differences in means, CHAID decision trees, and Poisson regression to analyze beneficiaries’ utilization of five service categories (inpatient care, skilled nursing care, outpatient services, home health services, and other provider services, including physicians). The study reveals three critical findings. First, specific beneficiary attributes such as age and race, and beneficiary access to doctors and hospitals, are predictors of one’s chosen Medicare plan. Notably, some Medicare beneficiary groups are more likely to enroll in a Medicare Advantage plan rather than others. Second, beneficiary characteristics, doctor and hospital access, and plan choice collectively have a strong association with service utilization. Those enrolled in Medicare Advantage plans use fewer services than their Traditional Medicare counterparts. Lastly, beneficiaries enrolled in a Medicare Advantage plan that engages risk-bearing primary care physician groups use fewer services than beneficiaries in other plans