Aligning incentives in health care: a multiscale decision theory approach

Financial incentives offered by insurers to health care providers have been identified as a key mechanism to lower costs while improving quality of care. How to effectively design incentive programs that can align the varying objectives of health care stakeholders, as well as predict program performance and stakeholders’ decision response is an unresolved research challenge. The objective of this paper was to establish the foundation for a novel approach based on multiscale decision theory (MSDT) that can effectively model and efficiently analyze such incentive programs, and the complex health care system in general. The MSDT model captures the interdependencies of stakeholders, their decision processes, uncertainties, and how incentives impact decisions and outcomes at the payer, hospital, physician and patient level. We illustrate the modeling approach by applying it to a specific incentive program, the Medicare Shared Savings Program (MSSP) for Accountable Care Organizations (ACOs), which was introduced by the Centers for Medicare and Medicaid Services (CMS) in the United States in 2012. We focus our analysis on computed tomography (CT) use by physicians, and CT scanner investment decisions by hospitals. We determine the conditions under which the incentive program leads to the desired outcomes of cost reduction and quality of care improvements. The results have policy and managerial implications for CMS, ACOs and their members, specifically hospitals and physicians.