The Effect of Electronic Health Record Implementation on Community Emergency Department Operational Measures of Performance

Abstract

Objective To study the effect of electronic health record (EHR) implementation on the operational metrics of a diverse group of community emergency departments (ED). Methods We performed a retrospective before/after analysis of 23 EDs from a single management group that experienced EHR implementation, defined as the date of implementation of electronic clinical documentation in the ED. We obtained electronic data for 4 length-of-stay (LOS) measures (arrival-to-provider, admitted, discharged and overall LOS) and 4 measures of operational characteristics (left-prior-to–treatment-complete, significant returns, overall patient satisfaction and provider efficiency). We compared the 6-month “baseline” period immediately prior to implementation with a “steady-state” period commencing 6 months after implementation for all 8 metrics. Results For the LOS measures, there were no differences in the arrival-to-provider interval (difference of −0.02 hours, 95% CI of difference −0.12, 0.08), admitted LOS (difference of 0.10 hours, 95% CI of difference −0.17, 0.37), discharged LOS (difference of 0.07 hours, 95% CI of difference −0.07, 0.22) and overall LOS (difference of 0.11 hours, −0.04, 0.27). For operational characteristics, there were no differences in the percentage who left-prior-to-treatment-complete (difference of 0.24%, 95% CI of difference −0.47%, 0.95%), significant returns (difference of −0.04%, 95% CI of difference −0.48%,0.39%), overall percentile patient satisfaction (difference of −0.02%, 95% CI of difference −2.35%, 2.30%) and provider efficiency (difference of −0.05 patients/hour, 95% CI of difference −0.11,0.02). Conclusions There is no meaningful difference in 8 measures of operational performance for community EDs experience EHR implementation between a baseline and steady state period.

What to expect from electronic patient record system implementation: lessons learned from published evidence

“…However, laboratory testing, medication administration and radiologic imaging all showed sustained increase-post-implementation 82. In a further study, no difference was found in measures of operational performance,83 and others also report no effect on outpatient volumes84 or readmission rates 85. The most recent emergency department study reported no differences in volume, admissions, or transfers but increased length of stay until 1 year later 86…”

Timing of Opioid Administration as a Quality Indicator for Pain Crises in Sickle Cell Disease

“…29,30 Frequently, the timeliness of care is transiently increased before returning to preimplementation levels. 31 In this study, we found an independent association of post-EMR implementation with decreased total ED length of stay.…”

Exploring the Potential of Predictive Analytics and Big Data in Emergency Care

“…56 Early work has not demonstrated an operations benefit for community EDs that have invested in electronic medical records. 57 Better information technology infrastructure, using tools from predictive analytics, may be necessary to realize gains from that investment. Overall, many aspects of emergency care might benefit from new-wave predictive analytics.…”

“…Use of clinical decision tools has historically been low, 78,79 whereas early evidence has failed to demonstrate the value of electronic medical record data in ED operations. 57 Clinicians have cited performance reproducibility, cumbersome implementation, and exclusion of and inferiority to clinician gestalt as reasons for this. [80][81][82] Some barriers may be more easily addressed with new-wave predictive tools.…”