Automated Medical Resource Allocation System
Monday 3:05 PM
During the COVID-19 pandemic, the state of Arizona faced a mismatch of available ventilators to patients in need of them. To resolve this issue, the Maricopa County Department of Public Health set up an emergency database and crisis line. In short, rural hospitals with an overflow of critical COVID-19 patients could utilize this crisis line and redirect patients to urban hospitals (i.e., those in the greater Phoenix area) with available ventilators. This allowed for shorter waiting times, and a more efficient matching system of patients to ventilators. The system was additionally beneficial in reducing healthcare disparities, as it allowed individuals of all socioeconomic backgrounds and insurance statuses to access life-saving medical care.
While this system expired after the state of emergency was lifted in the state of Arizona, there is still a need for such a resource allocation system. There are a limited number of extracorporeal membrane oxygenation (ECMO) machines in the state of Arizona (approximately 27, mostly in urban areas such as Tucson and Phoenix). Patients in rural areas are often passed over for ECMO care. Thus, it would be helpful to create a system akin to the emergency COVID-19 ventilator crisis line, but for ECMO devices. We’ll need to match patients to available devices, create a hierarchy based on care status (i.e., patients in more distress should get priority), and ensure that distance is accounted for. Essentially, the maximum number of patients should be matched with the maximum number of ECMO machines in the fastest time possible.
The Maricopa County Department of Public Health has previously worked with major hospitals in the Phoenix area (e.g., Mayo Clinic) to ensure that critical COVID-19 patients were matched to available ventilators in an efficient and timely manner. Now, there is a need for such a system with the limited amount of ECMO devices in the state of Arizona, particularly for patients that hail from rural or medically underserved areas. The goal is to create a system that matches patients with available ECMO machines, accounting for factors such as distance, health status (i.e., patients who are in more critical need of ECMO), insurance status, and machine availability.