Smartwatch-Measured Clinician Perceptions of Emergency Department Crowding and Their Association With Objective Metrics: Prospective Observational Study

Background Emergency department (ED) crowding compromises patient safety and increases clinical workload. Existing crowding metrics capture structural indicators but not how clinicians subjectively experience crowding in real time. Clinician perception may provide a complementary measure. Objective This study aimed to examine the concurrent and temporal associations between clinicians’ real-time ED perceived crowding (EDPC), captured via a smartwatch-based ecological momentary assessment (EMA) system, and 3 objective crowding metrics: the ED occupancy ratio (EDOR), the National Emergency Department Overcrowding Score (NEDOCS), and the ED Work Index (EDWIN). Methods We conducted a prospective observational study over a continuous 449-hour period (November 25, 2024, 7 AM to December 13, 2024, 11:59 PM) in a single tertiary ED operating under reduced bed capacity and attending-only staffing due to a national physician shortage. We enrolled 28 clinicians (5 attending physicians and 23 charge nurses; mean age 36.3, SD 5.9 years; 21 female and 7 male) by voluntary nonprobability sampling. Clinicians recorded EDPC hourly during active shifts on a continuous 0-200 scale anchored to the NEDOCS crowding categories, from “Not Busy” to “Dangerously Overcrowded.” All valid ratings within each hourly period were aggregated into a single median EDPC value. Interrater agreement was assessed with the Gwet weighted agreement coefficient (AC2) at hourly time points with at least 2 ratings. Main analyses used Pearson correlations between hourly median EDPC and median EDOR, NEDOCS, and EDWIN. Linear mixed-effects models additionally accounted for repeated ratings within clinicians and clustering at the same hourly time point. Time-lagged correlations were exploratory. Statistical significance was set at α=.05. Results Across 1124 scheduled on-duty assessment opportunities, clinicians completed 1100 individual EDPC ratings (response rate 1100/1124, 97.86%). These ratings yielded 449 hourly aggregated EDPC observations, with a median of 2 (IQR 2-3; range 1-4) clinicians contributing ratings per hour. Interrater reliability was substantial (AC2=0.742, 95% CI 0.712-0.772). Objective metrics were derived from 1846 ED visits. Hourly median EDPC correlated with median EDOR (r=0.542, 95% CI 0.473-0.604; P<.001) and NEDOCS (r=0.483, 95% CI 0.409-0.551; P<.001), but not EDWIN (r=0.060, 95% CI –0.033 to 0.152; P=.20). Conclusions We deployed smartwatch-based EMA to capture high-frequency, in situ clinician perceptions during active shifts, potentially reducing susceptibility to retrospective recall bias while minimizing the spatial constraints of traditional survey methods. Hourly median EDPC was moderately associated with EDOR and NEDOCS in this single tertiary ED during an exceptional staffing crisis. The association with EDWIN was less consistent and became significant only after adjustment for time-of-day patterns. The high response rate (1100/1124, 97.9%) supports the short-term feasibility of repeated wearable-based data collection during routine clinical shifts. These findings support further investigation of EDPC as a complementary operational measure but do not establish that it directly measures cognitive workload or predicts subsequent crowding.