The Promise of mHealth for Chronic Disease Management Under Different Payment Systems

Problem definition : Rapid innovations in technology have created opportunities for different modes of healthcare delivery including digital services provided via mobile applications (mHealth). mHealth technology has the potential to provide efficient, effective, and patient-centered healthcare to manage chronic conditions. However, the economics associated with the adoption and integration of mHealth into the care delivery process is not well understood. In a chronic care clinical practice setting, we investigate fee-for-service (FFS) and capitation payment systems, and explore their performance in a traditional office-visit mode and in a mHealth-adopted mode. We identify conditions under which it is preferable to switch to an mHealth-based practice from an office visit-based practice. Methodology/results : We use an analytical model to track the 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 consider many patient-doctor interaction factors including the risk-index of patients, the cost of being sick, and the effectiveness of treatment. We measure the performance based on four different criteria: physician net revenue, physician panel size, total patient utility, and payor net revenue. Although patients may find mHealth mode to be very beneficial, physicians under an FFS system may only adopt mHealth for moderately risky patients but for neither low-risk nor high-risk patients. Capitation clinics are likely to adopt mHealth (higher net revenue) even if the technology is moderately effective. Importantly, mHealth is preferred by patients (higher total utility) and policy makers (greater coverage) when the clinic serves moderate-risk or high-risk patients. 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 systems, physician incentives, and optimal conditions for mHealth to achieve its full potential.