Resident Exposure to Acutely Ill Patients Over the Course of Residency

Emergency medicine literature has long debated the "black cloud" and "white cloud" phenomena, which suggest individual variability in exposure to acutely ill patients. If true, this variation may have significant implications for resident training. This study investigates whether emergency medicine (EM) residents consistently encounter differing volumes of high-acuity clinical encounters throughout their training.

This retrospective cohort study analyzed 11 years of electronic health record (HER) data from a Midwestern academic emergency department to quantify the number of acutely ill adult patients seen by EM residents across three years of training, using a consensus-based set of clinical criteria. Our primary outcome was the concordance of the ranking of each resident within their cohort by number of acutely ill patients seen during postgraduate year one (PGY 1) compared to PGY 3. Statistical analyses to assess this outcome included weighted kappa and linear regression.

A total of 93 EM residents met the criteria for inclusion and saw a total of 359,736 patients during their residency (average 3,493 per resident). Residents saw an average of 167.5 (19.8) acutely ill patients during their residency training. This volume increased sharply by year, with PGY-1 residents seeing an average of 23.8 (7.3) acutely ill patients, and PGY-3 residents seeing an average of 100.3 (19.4). Both weighted kappa (κ = -.274) and linear regression analysis (β = -0.84; 95% CI, -1.4 to -0.31; P = .002) indicated that a resident who saw more acutely ill patients than average in PGY 1 was more likely to see fewer acutely ill patients than average during PGY 3. Results were unaffected by the COVID-19 years or subsequent critical care fellowship pursuit.

"Cloud type" (as measured by EHR-documented care for acutely ill patients) does not appear to be a stable trait over time. Our findings are consistent with previous studies that found no association between residents' "cloudiness" and objective measures of workload. Using EHR data to track resident clinical exposures helps educators identify training gaps and target remediation through in situ or simulated experiences.