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As telehealth utilization for ambulatory and home-based care skyrockets, there has been a paradigm shift to a decentralized and hybrid care delivery modality integrating both in-person and telehealth services provided at different layers of the care delivery network, i.e., central hospitals, satellite clinics, and patient homes. The operations of such care delivery systems need to take into consideration patients’ mobility and care needs, and rely on multiple types of nurses who can support and facilitate telehealth (with hospital physicians) in clinics and patient homes. We formulate an optimization problem, aiming at operationalizing the proposed care delivery network. Decisions regarding the type of care delivered, the location of care delivered, and the scheduling of all kinds of nurses are determined jointly to minimize operating costs while simultaneously satisfying patients’ care needs. We propose a bi-level approximation that exploits the structure of the hybrid telehealth system, and develop column generation-based heuristic algorithms to identify the joint decision rules for clinic selection, patient assignment, and visiting nurse routing problems. Numerical experiment results demonstrate our algorithm’s capability to achieve high-quality solutions in reasonable computation time, and is capable of solving instances with large patient sizes and time windows. Our work supports the efficient and effective operation of the proposed hybrid telehealth systems to improve patient access to care. 

Despite providing convenience and reducing the travel burden of patients, Video-Conferencing (VC) clinical visits have not enjoyed wide uptake by patients and care providers. It is desired that the medical problems addressed by VC visits can match a face-to-face encounter in scope and quality. Subsequently, VC visits with nurse assistance are emerging; however, the scalable and financially sustainable of such services are unclear. Therefore, we explore the implementability of VC visits with nursing services using a game-theoretic model, and investigate the impact of different pricing schemes (discriminative pricing based on patient characteristics vs. non-discriminative) on patients’ care choices between VC and in-person visits. Our results shed light on the “artificial congestion” created by a profit-driven medical institution that hurts patient welfare, and subsequently identify the conditions where the interest of the social planner and the medical institution are aligned. Our results highlight that, compared to a uniform price of VC visits which seems fair, discriminative pricing can be more beneficial for patients and the medical institution alike. This heightens the importance of insurance coverage of telehealth-related services to promote the adoption of telehealth by patients and care providers, and ultimately, improving care access and patient outcomes.