Impact of electronic health record implementation on patient flow metrics in a pediatric emergency department

Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio 45229, USA.
Journal of the American Medical Informatics Association (Impact Factor: 3.93). 11/2011; 19(3):443-7. DOI: 10.1136/amiajnl-2011-000462
Source: PubMed

ABSTRACT Implementing electronic health records (EHR) in healthcare settings incurs challenges, none more important than maintaining efficiency and safety during rollout. This report quantifies the impact of offloading low-acuity visits to an alternative care site from the emergency department (ED) during EHR implementation. In addition, the report evaluated the effect of EHR implementation on overall patient length of stay (LOS), time to medical provider, and provider productivity during implementation of the EHR. Overall LOS and time to doctor increased during EHR implementation. On average, admitted patients' LOS was 6-20% longer. For discharged patients, LOS was 12-22% longer. Attempts to reduce patient volumes by diverting patients to another clinic were not effective in minimizing delays in care during this EHR implementation. Delays in ED throughput during EHR implementation are real and significant despite additional providers in the ED, and in this setting resolved by 3 months post-implementation.

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    ABSTRACT: Introduction Use of electronic health record (EHR) systems can place a considerable data entry burden upon the emergency department (ED) physician. Voice recognition data entry has been proposed as one mechanism to mitigate some of this burden; however, no reports are available specifically comparing emergency physician (EP) time use or number of interruptions between typed and voice recognition data entry-based EHRs. We designed this study to compare physician time use and interruptions between an EHR system using typed data entry versus an EHR with voice recognition. Methods We collected prospective observational data at 2 academic teaching hospital EDs, one using an EHR with typed data entry and the other with voice recognition capabilities. Independent raters observed EP activities during regular shifts. Tasks each physician performed were noted and logged in 30 second intervals. We compared time allocated to charting, direct patient care, and change in tasks leading to interruptions between sites. Results We logged 4,140 minutes of observation for this study. We detected no statistically significant differences in the time spent by EPs charting (29.4% typed; 27.5% voice) or the time allocated to direct patient care (30.7%; 30.8%). Significantly more interruptions per hour were seen with typed data entry versus voice recognition data entry (5.33 vs. 3.47; p=0.0165). Conclusion The use of a voice recognition data entry system versus typed data entry did not appear to alter the amount of time physicians spend charting or performing direct patient care in an ED setting. However, we did observe a lower number of workflow interruptions with the voice recognition data entry EHR. Additional research is needed to further evaluate the data entry burden in the ED and examine alternative mechanisms for chart entry as EHR systems continue to evolve.
    The western journal of emergency medicine 07/2014; 15(4):541-7. DOI:10.5811/westjem.2014.3.19658
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    ABSTRACT: We study the effect of an emergency department (ED) electronic health record implementation on the operational metrics of a diverse group of community EDs. We performed a retrospective before/after analysis of 23 EDs from a single management group that experienced ED electronic health record implementation (with the majority of electronic health records optimized specifically for ED use). We obtained electronic data for 4 length of stay measures (arrival to provider, admitted, discharged, and overall length of stay) and 4 measures of operational characteristics (left before treatment complete, significant returns, overall patient satisfaction, and provider efficiency). We compared the 6-month "baseline" period immediately before implementation with a "steady-state" period commencing 6 months after implementation for all 8 metrics. For the length of stay measures, there were no differences in the arrival-to-provider interval (difference of -0.02 hours; 95% confidence interval [CI] of difference -0.12 to 0.08), admitted length of stay (difference of 0.10 hours; 95% CI of difference -0.17 to 0.37), discharged length of stay (difference of 0.07 hours; 95% CI of difference -0.07 to 0.22), and overall length of stay (difference of 0.11 hours; 95% CI of difference -0.04 to 0.27). For operational characteristics, there were no differences in the percentage who left before treatment was complete (difference of 0.24%; 95% CI of difference -0.47% to 0.95%), significant returns (difference of -0.04%; 95% CI of difference -0.48% to 0.39%), overall percentile patient satisfaction (difference of -0.02%; 95% CI of difference -2.35% to 2.30%), and provider efficiency (difference of -0.05 patients/hour; 95% CI of difference -0.11 to 0.02). There is no meaningful difference in 8 measures of operational performance for community EDs experiencing optimized ED electronic health record implementation between a baseline and steady-state period.
    Annals of emergency medicine 01/2014; DOI:10.1016/j.annemergmed.2013.12.019 · 4.33 Impact Factor
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    ABSTRACT: Introduction: Electronic patient records are important for quality health services and efficient patient data management. In emergency care, saving valuable time during patient care is of great significance. One out of two fatalities due to trauma occur half an hour after the injury. The aim of this study was to investigate the potential effect of an electronic trauma documentation system on the length of stay in an emergency department. Methods: A 2-year observational study was conducted in the emergency department of a university hospital located in central Greece. The purpose was to compare 3 length-of-stay parameters with and without the use of an electronic documentation system. Ninety-nine trauma patients were monitored with the use of the electronic system, whereas 101 patients were monitored with a paper-based method (control group). Results: Statistical analysis using independent-samples t tests indicated that the time between admission and completion of the planned care was significantly lower in the electronic documentation patient group (100 ± 92 minutes) than in the control group (149 ± 29 minutes) (P < .01). A similar effect was found on the total ED length of stay (127 ± 93 minutes in electronic documentation group vs 206 ± 41 minutes in control group, P < .01) and the time between completion of care and discharge from the emergency department (26 ± 10 minutes in electronic documentation group vs 57 ± 23 minutes in control group, P < .01). Discussion: We investigated 3 length-of-stay parameters and found that all were lower with the use of the electronic documentation system. This finding is important regarding the quality of trauma patient care because saving time during the first hours after the injury may determine the outcome of the trauma patient.
    Journal of Emergency Nursing 01/2014; 40(5). DOI:10.1016/j.jen.2013.10.008 · 1.13 Impact Factor

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