The economics of telemedicine for managing chronic conditions

Thesis (Ph. D.)--University of Rochester. William E. Simon Graduate School of Business Administration, 2014.Telemedicine is the use of electronic communication to exchange medical information to improve patient health. While the medical feasibility and clinical benefits of this technology have been widely discussed, there remains a salient strategic question addressing the economics of telemedicine and the impact of such a technology on various stakeholders. My dissertation attempts to address the economic issue of telemedicine for the case of chronic health conditions. I develop an analytical model to investigate patient choices and behaviors when treatment is available via telemedicine in addition to in-person. I take Parkinson's disease to illustrate the nature of a chronic condition. Initial clinical results have already shown that care via telemedicine is feasible, and that it produces results which are on par with conventional in-person visits. I consider a market where two hospitals compete for patients spread out in the region and one of the two hospitals sets up a telemedicine facility. Based on my model, I observe that the utility to a patient in choosing telemedicine, relative to in-person visits, does not always increase with the distance of the patient from the specialist hospital. In other words, I show why not all patients may switch to telemedicine even if it is available. However, I derive general conditions under which telemedicine, as it is widely believed, not only increases access to remote patients, but also increases the catchment area for the hospital which initiates a telemedicine practice. But contrary to popular expectations, I show that telemedicine, unlike numerous other e-commerce applications, does not lead to the \winner takes all" phenomenon. Thus, competitors may continue to co-exist even without offering telemedicine services. I also analyze how community hospitals could help with the effort of increasing access and when there could be a symbiotic relationship between community hospitals and specialist hospitals. Next, I investigate the strategic behavior of medical specialists and look at the impact of travel burden on their behavior in terms of their decisions, price and service rate. The objective of a revenue-maximizing specialist is to maximize the revenue from treating self-centered utility-maximizing patients, by changing one or both the price he charges and the rate at which he sees patients. Typically, patients travel long distances to see a specialist. Using my analytical model, I find that when patients experience significant travel burden, the specialist tends to spend more time with the patients, as though he tries to compensate for the disutility of travel. The objective of the welfare-maximizing specialist will be to maximize the gross utility less expected service costs of all patients, by deciding on the number of patients to see and the rate at which he serves them. I find that while from a social welfare perspective, the specialist needs to see more patients, the revenue-maximizing specialist opts to see fewer patients and gains more revenue by charging a higher price. Interestingly, total time spent per visit (including waiting time) by the patients under both regimes remain the same. With the introduction of telemedicine, the specialist now sees patients both in person and via telemedicine. If the specialist spends the same amount of time on average for both kinds of visits, then I observe that the revenue-maximizing service rate moves closer to the socially optimal service rate. If the service quality effect is linear, then even after the introduction of telemedicine, the total time spent per visit (including waiting time) remain the same on average for patients. This is because of a concurrent increase in the utilization level of the specialists. The increased access to specialist care also increases the overall social welfare. I then analyze the case where the specialist can choose two different service rates, for telemedicine and in-person visits, with some less restrictive assumptions. I lay out the methodology to solve the optimization problem in this scenario. Based on some numerical analysis, I find that while the service rates are higher after telemedicine is introduced, the service rate for in-person visits may be higher or lower than the service rate of telemedicine visits. I also observe that the optimal prices are lower after telemedicine is introduced, in spite of the effective transportation cost going down for the patients choosing telemedicine. I then consider Diabetic Retinopathy as another illustration of a chronic condition. I analyze how telemedicine has the potential to decrease costs by preventing complications. I conclude by observing how incentive programs must be designed to account for the distribution of the degree of chronic condition severity in the patient population and other avenues through which telemedicine could improve the efficiency of the healthcare system