An introduction to health care payment reform: Research foundations, implementation, operational strengths and challenges
Policymakers across the country are currently engaged in discussions on how to improve the way that health care providers are paid for the services they deliver. These discussions involve how to shift payment systems away from traditional fee for services and toward rewarding providers that achieve excellent outcomes and deliver value to their patients. While both private and public payers are implementing significant changes, much of the focus of payment reform is on pilot programs and demonstrations in the Affordable Care Act (ACA), such as accountable care organizations (ACOs), value-based purchasing, and bundled payments.
Bundled payments, which focus on all the procedures involved in a single medical episode rather than considering these items individually, are now receiving serious attention as a way to improve quality at lower costs under the new Medicare Bundled Payment for Care Program, authorized by the ACA. In contrast, many other payers are moving forward with payment reform strategies, such as ACOs and value-based purchasing, which emphasize provider performance at the population level.
This paper takes a close look at these two broad types of payment strategies, including, their research foundations, how they have been implemented in the past, and their operational strengths and challenges. Due to the variation of health care delivery systems, not all payment strategies are appropriate for every medical condition. Appendix Figures 1 and 2 summarize the characteristics of different strategies and how they may be targeted to different types of medical episodes.
Key findings include:
- While a variety of payment reform strategies are garnering significant attention, there is little long-term evidence of their ability to reduce the growth of health care costs while improving the quality of care.
- Bundled payments have shown limited success but may be best suited to controlling cost variation for certain types of acute care episodes. It is largely unclear how successful bundled payments can be outside of highly integrated health systems, and the administrative complexity of these bundled payments has caused delays in their wide-scale implementation.
- Population-based payment models may be a potential way to reduce variation in health care utilization across populations, but further evidence of their effectiveness is necessary.
- Shared savings programs have the ability to improve quality of care but may not able to reduce costs unless they also involve shared risk.
- Global payment programs may be able to reduce costs in the short run but further evidence is needed to prove that their effects are durable.
- Pay for Performance programs have been adopted widely but with significant variation in the details of their implementation. Evidence of their effectiveness is not strong but the flexibility of P4P and its ability to be implemented incrementally maintain its popularity.
- Though results data are limited, emerging value-based payment models (such as the Blue Cross Blue Shield of Michigan OSC strategy) have promise with regard to both cost savings and quality and can build on the findings from the shared savings and pay-for-performance programs.
- Past experience shows that payers and providers must be prepared for the administrative and technical challenges of implementing payment reform models.
- The payment strategies that demonstrate the most impact on both cost and quality are those that have been implemented within tight, managed care networks with patient assignment or in highly integrated provider delivery systems. Outside of these structures, there is little evidence of payment systems that achieve a significant impact on cost or quality.
- To the extent that fee-for-service reimbursement remains the predominant form of payment, the best payment strategies are likely to be a combination of several of the above approaches with constant refinement to mitigate the noted challenges and maximize effectiveness.