Abstract
Purpose :
There is pervasive lore in residency programs regarding the existence of “light” and “dark” clouds based on the resident’s perception of volume and acuity during a call shift relative to other shifts. We used a retrospective chart review to evaluate that theory at a high-volume academic referral center.
Methods :
This study utilized data from resident call shifts alongside surveys to analyze trends in volume and perceptions of that volume. Shifts were characterized as day, night, or 24-hour. Volume was measured as the total number of patients seen plus the number of triage phone calls. “Estimated patient time” was calculated by combining the number of patients seen (defined as one hour of resident work) and patient phone calls (defined as 10 minutes of resident work). Statistical analysis utilized Analysis of Variance (ANOVA) and linear regression.
Results :
In one year of call (178 shifts), a total of 1,735 patients were seen and a total number 1,438 triage calls were completed by seven residents. The average “estimated patient time” per half-day shift was 9.05 hours (SD 2.93). There was a statistically significant difference between the average shift “estimated patient time” by resident (P = 0.033). The difference in average time between the highest volume resident and lowest volume resident was 2.01 hours per shift (P = 0.019, 95% confidence interval 0.35 - 3.66). When comparing resident perceptions of their own average shift on a scale of 1 (easier) to 10 (busier), there was no significant correlation between perceptions and true call volume (P = 0.646, R-squared 0.046).
Conclusions :
Over the course of one year, there were statistically significant differences in actual call volume between residents. However, there was not a statistically significant correlation between perceptions of call volume and true call volume. Therefore, while it may be true that some residents are “dark clouds” who see more volume on call, one’s perception is not a reliable marker of that reality.
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.