oa Marginal analysis in assessing factors contributing time to physician in Emergency Department using operations data

Background: Standard Emergency Department (ED) operations goals include minimization of the time interval (hereafter tMD) between patients' initial ED presentation and initial physician evaluation.

Methods: The study was conducted using one month (May 2015) of an ED administrative database (EDAD), in HGH-ED, during the study month the ED saw 39,593 cases. The first step was generation of a multivariate model identifying the parameters associated with delay in tMD. In the second step, predictive marginal probability analysis was used to calculate the relative contributions of key covariates as well as demonstrate the likely tMD impact on modifying those covariates with operational improvements. Analyses were conducted with STATA 14 MP, with significance defined at p <  .05 and confidence intervals (CIs) reported at the 95% level.

Results: In an acceptable linear regression model that accounted for just over half of the overall variance in tMD (adjusted r2 .51), important contributors to tMD included shift census (p = .008), shift time of day (p = .002), and physician coverage n (p = .004). Marginal predictive probability analysis was used to predict the overall tMD impact (improvement from 50 to 43 minutes, p <  .001) of consistent staffing with 22 physicians.

Conclusions: The analysis identified expected variables contributing to tMD with regression demonstrating significance and effect magnitude of alterations in covariates including patient census, shift time of day, and physician n. Marginal analysis provided operationally useful demonstration of the need to adjust physician coverage numbers, prompting changes at the study ED.