Using community care coordination networks to minimize hospitalization of COVID-19 patients

Abstract

Coronavirus surges have motivated hospitals around the globe to rapidly develop and deploy two key types of telemedicine/telehealth solutions: 1) to diagnose and manage COVID-19 patients at home as their symptoms emerge, avoiding hospitalization as much as possible, and 2) to discharge 'recovered' patients to homecare as rapidly as possible from the hospital, freeing as many critical care beds as possible for incoming patients. Since early 2019, hospitals in both large cities and small cities alike have reported multiple episodes of periodic overwhelming surges, and tele-homecare strategies have been part of their overload solution. In prior work, this team of researchers have demonstrated many Petri net simulation tools to model and design optimal community homecare hub to enable safer, more effective, and more efficient homecare. This paper leverages prior work to address COVID-19 patient care, and also expands the AI/Decision Support Layer to further illustrate care coordination needs in the emerging Accountable Care era.