Facilitating Test Status Information Communication in the Time of COVID-19

• Egile Nagusiak: Stephen R. Master MD, PhD (Egilea), Brandy Neide MBA, MLS (ASCP) (Egilea), Sunaina Kollu MS (Egilea), Surabhi Mulchandani MSc, MS (Egilea), Rebecca M. Harris MD (Egilea), Amrom E. Obstfeld MD, PhD (Egilea)
• Formatua: Liburua
• Argitaratua: Elsevier, 2021-04-01T00:00:00Z.
• Gaiak: article
• Sarrera elektronikoa: Connect to this object online.
• Notes: 2374-2895; 10.1177/23742895211006822
• Keywords: Pathology; RB1-214
• Source: Academic Pathology, Vol 8 (2021)

The Coronavirus 2019 pandemic has strained nearly every aspect of pathology practice, including preanalytic, analytic, and postanalytic processes. Much of the challenges result from high demand for limited severe acute respiratory syndrome coronavirus 2 testing capacity, a resource required to facilitate patient flow throughout the hospital system and society at large. At our institution, this led to unprecedented increases in inquiries from providers to laboratory staff relating to the expected time to result for their patients. The demand was great enough to require redeployment of staff to handle the laboratory call volume. Although these data are available in our laboratory information system, the data do not interface to our electronic health record system. We developed systems using the R statistical programming language that abstract the necessary data regarding severe acute respiratory syndrome coronavirus 2 polymerase chain reaction testing from our lab system in real time, store it, and present it to clinicians for on demand querying. These data have been accessed over 2500 times by over 100 distinct users. Median length of each user session is approximately 4.9 minutes. Because our lab information system does not persistently store tracking information while our system does, we have been able to iteratively recalculate time to result values for each tracking stop as workflows have changed over time. Facility with informatics and programming concepts coupled with clinical understanding have allowed us to swiftly develop and iterate on applications which provide efficiency gains, allowing laboratory resources to focus on generating test results for our patients.