A Systems Approach to Optimizing Patient Flow During the COVID-19 Pandemic

Abstract

In 2020, health systems have been affected by the novel coronavirus (COVID-19) pandemic, causing an influx of COVID-19 related visits and a sharp decline in non-emergency and elective visits. To mitigate the spread of COVID-19, healthcare systems – including the University of Virginia Health System – reduced ambulatory visits and implemented various social distancing measures, resulting in a drastic change in the patient admittance process. The focus of this work is to accurately characterize the effect of COVID-19 on one of the UVA Internal Medicine, Primary Care clinics, and where possible, to refine and optimize patient flow through the appointment process while accommodating public health restrictions. To achieve these goals, the team adopted a systems approach, which involves the iterative process of problem identification, analysis, and testing recommendations.The first phase of the project focused primarily on establishment of the current state and problem identification. The appointment process contains six major elements: scheduling, sign-in/remote registration, check-in, rooming, check-out, and telemedicine. Through extensive discussions with the clients, surveys of clinic staff, in-person observation, and data collection and analysis, the capstone team was able to understand the pandemic’s impact on the clinic’s patient flow and identify key problem areas at each stage in the appointment process. The team then used these insights to develop informed recommendations for these pain points. The second phase of the project consisted of formulating trials within UVA health restrictions and guidelines to test the impact of our recommendations. Through a pilot of a new remote registration process, on-time patients increased from 68% to 75%, nurse perceived workload decreased significantly, and the arrival process became more predictable. From this work, the team was able to develop a more generic framework for how health systems might assess and address patient flow issues under normal circumstances as well as during future pandemics.