Successful Implementation of Workflow-Embedded Clinical Pathways During the COVID 19 Pandemic.

BACKGROUND AND OBJECTIVES: Clinical pathways have been found effective for improving adherence to evidence-based guidelines, thus providing better patient outcomes. As coronavirus disease-2019 (COVID-19) clinical guidance changed rapidly and evolved, a large hospital system in Colorado established clinical pathways within the electronic health record to guide clinical practice and provide the most up-to-date information to frontline providers. METHODS: On March 12, 2020, a system-wide multidisciplinary committee of specialists in emergency medicine, hospital medicine, surgery, intensive care, infectious disease, pharmacy, care management, virtual health, informatics, and primary care was recruited to develop clinical guidelines for COVID-19 patient care based on the limited available evidence and consensus. These guidelines were organized into novel noninterruptive digitally embedded pathways in the electronic health record (Epic Systems, Verona, Wisconsin) and made available to nurses and providers at all sites of care. Pathway utilization data were analyzed from March 14 to December 31, 2020. Retrospective pathway utilization was stratified by each care setting and compared with Colorado hospitalization rates. This project was designated as a quality improvement initiative. RESULTS: Nine unique pathways were developed, including emergency medicine, ambulatory, inpatient, and surgical care guidelines. Pathway data were analyzed from March 14 to December 31, 2020, and showed that COVID-19 clinical pathways were used 21 099 times. Eighty-one percent of pathway utilization occurred in the emergency department setting, and 92.4% applied embedded testing recommendations. A total of 3474 distinct providers employed these pathways for patient care. CONCLUSIONS: Noninterruptive digitally embedded clinical care pathways were broadly utilized during the early part of the COVID-19 pandemic in Colorado and influenced care across many care settings. This clinical guidance was most highly utilized in the emergency department setting. This shows an opportunity to leverage noninterruptive technology at the point of care to guide clinical decision-making and practice.

COVID-19 Vaccine Clinic Real-Time Throughput Analysis: Development and Implementation of an Innovative Data Collection Tool.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) pandemic has presented the healthcare system with a plethora of challenges, including implementation of an efficient vaccination strategy. Mass vaccinations have been used during previous pandemics; however, the associated data have largely been limited to theoretical simulations and post hoc analysis. METHODS: An innovative data collection tool was created to deliver real-time data analysis during a drive-through mass vaccination. Patients were assigned unique identification numbers at the clinic entrance. Using these identification numbers, and the web-based spreadsheet, patients were tracked throughout the vaccination process. Static timestamps corresponding to the entry and exit at each checkpoint were recorded in real time. RESULTS: Data were collected on a total of 3,744 vehicles over five clinic days. Total time was collected, from entry to exit, on 2,860 vehicles. Registration and vaccination times were collected on 3,111 vehicles. Of the vehicles sampled, 1,588 (42%) had data points associated with all checkpoints. CONCLUSIONS: This open-source, innovative data collection tool was successfully implemented in our mass vaccination clinic for tracking patients in real time providing actionable data on overall throughput efficiency. This cost-effective tool can be used on a variety of healthcare-related projects to provide data-driven evaluation on the efficiency of care.

ED-based COVID-19 vaccination campaign finds higher vaccination rates for individuals from racial and ethnic minority groups compared with clinic setting.

BACKGROUND: Emergency department visits associated with Coronavirus Disease 2019 (COVID-19) continue to indicate racial and ethnic inequities. We describe the sociodemographic characteristics of individuals receiving COVID-19 vaccination in the emergency department and compare with an outpatient clinic population and emergency department (ED) patients who were eligible but not vaccinated. METHODS: We conducted a retrospective analysis of electronic health record data at an urban academic ED from May to July 2021. The primary aim was to characterize the ED-vaccinated population, compared with ED patients who were eligible but unvaccinated and the physically adjacent outpatient vaccination clinic population. RESULTS: A total of 627 COVID-19 vaccinations were administered in the ED. Overall, 49% of ED patients during that time had already received at least one vaccine dose prior to ED arrival. Hispanic, non-Hispanic Black patients, and patients on non-commercial insurance had higher odds of being vaccinated in the ED as compared with outpatient clinic setting. Among eligible ED patients, men and patients who were uninsured/self-pay were more likely to accept ED vaccination. CONCLUSIONS: This ED COVID-19 vaccination campaign demonstrated a higher likelihood to vaccinate individuals from racial/ethnic minority groups, those with high social vulnerability, and non-commercial insurance, when compared with a co-located outpatient vaccination clinic.

Optimizing planning and design of COVID-19 drive-through mass vaccination clinics by simulation.

Drive-through clinics have previously been utilized in vaccination efforts and are now being more widely adopted for COVID-19 vaccination in different parts of the world by offering many advantages including utilizing existing infrastructure, large daily throughput and enforcing social distancing by default. Successful, effective, and efficient drive-through facilities require a suitable site and keen focus on layout and process design. To demonstrate the role that high fidelity computer simulation can play in planning and design of drive-through mass vaccination clinics, we used multiple integrated discrete event simulation (DES) and agent-based modelling methods. This method using AnyLogic simulation software to aid in planning, design, and implementation of one of the largest and most successful early COVID-19 mass vaccination clinics operated by UCHealth in Denver, Colorado. Simulations proved to be helpful in aiding the optimization of UCHealth drive through mass vaccination clinic design and operations by exposing potential bottlenecks, overflows, and queueing, and clarifying the necessary number of supporting staff. Simulation results informed the target number of vaccinations and necessary processing times for different drive through station set ups and clinic formats. We found that modern simulation tools with advanced visual and analytical capabilities to be very useful for effective planning, design, and operations management of mass vaccination facilities.

Optimizing planning and design of COVID-19 drive-through mass vaccination clinics by simulation

Drive-through clinics have previously been utilized in vaccination efforts and are now being more widely adopted for COVID-19 vaccination in different parts of the world by offering many advantages including utilizing existing infrastructure, large daily throughput and enforcing social distancing by default. Successful, effective, and efficient drive-through facilities require a suitable site and keen focus on layout and process design. To demonstrate the role that high fidelity computer simulation can play in planning and design of drive-through mass vaccination clinics, we used multiple integrated discrete event simulation (DES) and agent-based modelling methods. This method using AnyLogic simulation software to aid in planning, design, and implementation of one of the largest and most successful early COVID-19 mass vaccination clinics operated by UCHealth in Denver, Colorado. Simulations proved to be helpful in aiding the optimization of UCHealth drive through mass vaccination clinic design and operations by exposing potential bottlenecks, overflows, and queueing, and clarifying the necessary number of supporting staff. Simulation results informed the target number of vaccinations and necessary processing times for different drive through station set ups and clinic formats. We found that modern simulation tools with advanced visual and analytical capabilities to be very useful for effective planning, design, and operations management of mass vaccination facilities.