Identifying and Mitigating the Effects of the Covid-19 Pandemic on Primary Care Clinics Using Lean Tools and Simulation

Abstract

Lean Systems have provided the healthcare industry with a set of tools to identify, reduce and eliminate waste (delays, re-work, waiting, unnecessary movement, etc.) from their processes. These tools have been useful during the Covid-19 pandemic era, when all non-acute healthcare services were pressured to quickly switch completely to telehealth operations to reduce disease transmission. However, in the literature, there has been little discussion on using Lean Systems to measure the effect of the pandemic on operational processes and how to mitigate that impact in the outpatient setting. This dissertation addresses this gap by applying lean methodologies such as Value Stream Mapping (VSM), Voice of the Process (VoP), Control Charts, and Time Motion Studies (TMS) in combination with agent-based simulation to evaluate the operational, organizational, and human impacts of the Covid-19 pandemic in an outpatient primary care clinic. The research is organized into three complementary contributions that combine lean Engineering methodologies with agent-based simulation to develop evidence-based recommendations for future public health emergencies. This dissertation addresses this gap by applying lean methodologies such as Value Stream Mapping (VSM), Voice of the Process (VoP), Control Charts, and Time Motion Studies (TMS) in combination with agent-based simulation to evaluate the operational, organizational, and human impacts of the Covid-19 pandemic in an outpatient primary care clinic. The research is organized into three complementary contributions that combine lean Engineering methodologies with agent-based simulation to develop evidence-based recommendations for future public health emergencies. The first contribution identified and quantified the effects of the Covid-19 pandemic on operational process waste using Lean methodologies. By comparing pre-pandemic workflows with pandemic workflows, the study identified wastes that increased, remained unchanged, decreased, or emerged as a direct result of Covid-19-related operational changes. The findings demonstrate how lean tools can be used not only to identify process inefficiencies but also to support rapid workflow redesign during major healthcare disruptions. The second contribution assessed actual and perceived occupational risk associated with Covid-19 and evaluated its relationship to provider and clinical staff stress and burnout. Voice of the Process interviews and organizational-wide surveys were used to examine how rapidly changing clinical protocols affected healthcare workers throughout multiple stages of the pandemic. The results identified organizational and clinical practices that reduced occupational risk while improving employee well-being and maintaining patient care. The third contribution developed and validated an agent-based simulation of an outpatient primary care clinic to evaluate alternative clinical and organizational protocols under pandemic conditions. The simulation incorporated real clinic workflows, staffing patterns, patient movement, infection transmission, and mitigation strategies, including masking, social distancing, and symptom screening. Multiple experimental scenarios were used to evaluate the effects of these protocols on workflow efficiency, patient wait times, provider utilization, and infection transmission. The simulation provides healthcare organizations with a decision-support framework for balancing operational efficiency, employee safety, and quality patient care during future infectious disease outbreaks. Overall, this dissertation demonstrates that integrating Lean Engineering methodologies with agent-based simulation provides a comprehensive approach for identifying operational waste, evaluating occupational risk, and optimizing healthcare workflows. The results contribute new knowledge to the limited body of research on outpatient primary care during the Covid-19 pandemic and provide practical guidance for healthcare organizations seeking to improve resilience and preparedness for future public health emergencies.