Anesthesia Clinical Workload Estimated from Electronic Health Record Documentation vs Billed Relative Value Units

Abstract

Importance: Accurate measurements of clinical workload are needed to inform health care policy. Existing methods for measuring clinical workload rely on surveys or time-motion studies, which are labor-intensive to collect and subject to biases. Objective: To compare anesthesia clinical workload estimated from electronic health record (EHR) audit log data vs billed relative value units. Design, Setting, and Participants: This cross-sectional study of anesthetic encounters occurring between August 26, 2019, and February 9, 2020, used data from 8 academic hospitals, community hospitals, and surgical centers across Missouri and Illinois. Clinicians who provided anesthetic services for at least 1 surgical encounter were included. Data were analyzed from January 2022 to January 2023. Exposure: Anesthetic encounters associated with a surgical procedure were included. Encounters associated with labor analgesia and endoscopy were excluded. Main Outcomes and Measures: For each encounter, EHR-derived clinical workload was estimated as the sum of all EHR actions recorded in the audit log by anesthesia clinicians who provided care. Billing-derived clinical workload was measured as the total number of units billed for the encounter. A linear mixed-effects model was used to estimate the relative contribution of patient complexity (American Society of Anesthesiology [ASA] physical status modifier), procedure complexity (ASA base unit value for the procedure), and anesthetic duration (time units) to EHR-derived and billing-derived workload. The resulting β coefficients were interpreted as the expected effect of a 1-unit change in each independent variable on the standardized workload outcome. The analysis plan was developed after the data were obtained. Results: A total of 405 clinicians who provided anesthesia for 31688 encounters were included in the study. A total of 8288132 audit log actions corresponding to 39131 hours of EHR use were used to measure EHR-derived workload. The contributions of patient complexity, procedural complexity, and anesthesia duration to EHR-derived workload differed significantly from their contributions to billing-derived workload. The contribution of patient complexity toward EHR-derived workload (β = 0.162; 95% CI, 0.153-0.171) was more than 50% greater than its contribution toward billing-derived workload (β = 0.106; 95% CI, 0.097-0.116; P