A Custom-Developed Emergency Department Provider Electronic Documentation System Reduces Operational Efficiency

Study objective: Electronic health record implementation can improve care, but may also adversely affect emergency department (ED) efficiency. We examine how a custom, ED provider, electronic documentation system (eDoc), which replaced paper documentation, affects operational performance. Methods: We analyzed retrospective operational data for 1-year periods before and after eDoc implementation in a single ED. We computed daily operational statistics, reflecting 60,870 pre- and 59,337 postimplementation patient encounters. The prespecified primary outcome was daily mean length of stay; secondary outcomes were daily mean length of stay for admitted and discharged patients and daily mean arrival time to disposition for admitted patients. We used a prespecified multiple regression model to identify differences in outcomes while controlling for prespecified confounding variables. Results: The unadjusted change in length of stay was 8.4 minutes; unadjusted changes in secondary outcomes were length of stay for admitted patients 11.4 minutes, length of stay for discharged patients 1.8 minutes, and time to disposition 1.8 minutes. With a prespecified regression analysis to control for variations in operational characteristics, there were significant increases in length of stay (6.3 minutes [95% confidence interval 3.5 to 9.1 minutes]) and length of stay for discharged patients (5.1 minutes [95% confidence interval 1.9 to 8.3 minutes]). There was no statistically significant change in length of stay for admitted patients or time to disposition. Conclusion: In our single-center study, the isolated implementation of eDoc was associated with increases in overall and discharge length of stay. Our findings suggest that a custom-designed electronic provider documentation may negatively affect ED throughput. Strategies to mitigate these effects, such as reducing documentation requirements or adding clinical staff, scribes, or voice recognition, would be a valuable area of future research.