Optimization and Standardization of a Surveillance Tool to Identify Patients at Risk for Candida Auris Across a Health System

Background Our healthcare system is comprised of 11 hospitals in the Chicagoland area. Prior to the COVID-19 pandemic, our academic medical center (AMC) conducted a pilot surveillance program for Candida auris (C. auris), but discontinued during the pandemic due to resource constraints. During the pandemic, C. auris re-emerged locally, prompting our system to resume screening and active surveillance. Methods This team used data from local, state, and federal agencies and our AMC’s epidemiological pilot to determine high-risk patient populations. Laboratory and reporting protocols were reviewed to ensure timely testing and results for prompt isolation to mitigate transmission risk. To standardize and implement active surveillance across the healthcare system, several changes were made to the electronic medical record (EMR) and Laboratory testing. Results A review of our epidemiological data resulted in changes to the admission screening questions to identify at-risk patients and prompt specimen collection. Laboratory partnered system-wide to standardize C. auris testing to a polymerase chain reaction (PCR) method and shorten turnaround time of results. A data dashboard was created in the electronic data warehouse (EDW) to track compliance with admission screening. Our system implemented C. auris screening in March 2022. Since then, 52,385 patients have been screened at admission. 9.69% of these patients (5,074 patients) met testing criteria, and 40 patients (0.64%) tested positive for C. auris. Conclusions Utilizing the EMR to assist in early identification of C. auris is essential in expediting the mitigation and containment of exposure. This team improved the process by simplifying the screening questions to pinpoint high-risk factors and transitioning from a culture-based test to a standardized PCR sensitive methodology to quickly identify and isolate positive patients. Continuous review of positive patient demographics and epidemiology allows us to evaluate and further refine screening processes and selected high-risk patient populations. Our healthcare system is comprised of 11 hospitals in the Chicagoland area. Prior to the COVID-19 pandemic, our academic medical center (AMC) conducted a pilot surveillance program for Candida auris (C. auris), but discontinued during the pandemic due to resource constraints. During the pandemic, C. auris re-emerged locally, prompting our system to resume screening and active surveillance. This team used data from local, state, and federal agencies and our AMC’s epidemiological pilot to determine high-risk patient populations. Laboratory and reporting protocols were reviewed to ensure timely testing and results for prompt isolation to mitigate transmission risk. To standardize and implement active surveillance across the healthcare system, several changes were made to the electronic medical record (EMR) and Laboratory testing. A review of our epidemiological data resulted in changes to the admission screening questions to identify at-risk patients and prompt specimen collection. Laboratory partnered system-wide to standardize C. auris testing to a polymerase chain reaction (PCR) method and shorten turnaround time of results. A data dashboard was created in the electronic data warehouse (EDW) to track compliance with admission screening. Our system implemented C. auris screening in March 2022. Since then, 52,385 patients have been screened at admission. 9.69% of these patients (5,074 patients) met testing criteria, and 40 patients (0.64%) tested positive for C. auris. Utilizing the EMR to assist in early identification of C. auris is essential in expediting the mitigation and containment of exposure. This team improved the process by simplifying the screening questions to pinpoint high-risk factors and transitioning from a culture-based test to a standardized PCR sensitive methodology to quickly identify and isolate positive patients. Continuous review of positive patient demographics and epidemiology allows us to evaluate and further refine screening processes and selected high-risk patient populations.