Chronic Disease Management under Different Payment Systems and the Promise of mHealth

Problem definition: In a chronic care clinical practice setting, we investigate fee-for-service (FFS) and capitation payment systems, and explore their performance. We also identify conditions under which it is preferable to switch to an mHealth-based practice from an office visit-based practice. Academic/practical relevance: While the debate over the ideal payment system continues to brew, the U.S. has been slowly transitioning from fee-for-service reimbursement model to a capitation-based payment model. The movement is mainly targeted at the ever-rising healthcare costs, and it is an attempt to target the growing inefficiencies in the healthcare delivery. Simultaneously, rapid innovations in technology have created opportunities for a different mode of healthcare delivery. mHealth technology is promising to provide efficient, effective, and patient-centered healthcare to manage chronic conditions. However, the economics associated with the adoption of mHealth and the care delivery process is not well understood. Methods: We use an analytical model to track progression of a chronic disease and formulate an optimization problem in which the clinic decides the time between scheduled visits and patient panel size. We take into account many patient-doctor interaction factors including the risk-index of patients, cost of being sick, and effectiveness of treatment. We measure the performance based on three different criteria: net revenue, panel size, and total patient utility.Results: We show that a capitation clinic would prefer to see patients less frequently when compared to FFS clinic but manage a bigger panel size than the FFS clinic. While patients may find mHealth mode to be very beneficial, FFS clinics may only adopt mHealth for moderately risky patients but for neither low-risk nor high-risk patients. Capitation clinics are likely to adopt mHealth even if the technology is moderately effective.Managerial Implications: Chronic conditions need continuous care management and use of mHealth has been very promising. However, adoption of mHealth by healthcare providers has been very slow. Our research explores payment schemes, physician incentives, and optimal conditions for mHealth to achieve its full potential