Patients living with a chronic disease often require regular appointments and treatments . Due to the constraints on the availability of office appointments and the capacity of physicians, access to chronic care can be limited; consequently, patients may fail to receive the recommended care suggested by clinical guidelines . Virtual appointments can provide a cost-effective alternative to traditional office appointments for managing chronic conditions . Advances in information technology infrastructure, communication, and connected medical devices are enabling providers to evaluate, diagnose, and treat patients remotely . In this study, we build a capacity allocation model to study the use of virtual appointments in a chronic care setting . We consider a cohort of patients receiving chronic care and model the flow of the patients between office and virtual appointments using an open migration network . We formulate the planning of capacity needed for office and virtual appointments with a newsvendor model to maximize long-run average earnings . We consider differences in treatment and diagnosis effectiveness for office and virtual appointments . We derive optimal capacity allocation policies and implement numerical experiments . With the model developed, capacity decisions for office and virtual appointments can be made more systematically with the consideration of patient disease progressions.