Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-29T09:22:21.991Z Has data issue: false hasContentIssue false

MP03: Strategies to minimize impact of electronic health record implementation on emergency department flow

Published online by Cambridge University Press:  02 May 2019

E. Grafstein*
Affiliation:
St Paul's Hospital and University of British Columbia, Vancouver, BC
S. Horak
Affiliation:
St Paul's Hospital and University of British Columbia, Vancouver, BC
J. Kung
Affiliation:
St Paul's Hospital and University of British Columbia, Vancouver, BC
J. Bonilla
Affiliation:
St Paul's Hospital and University of British Columbia, Vancouver, BC
R. Stenstrom
Affiliation:
St Paul's Hospital and University of British Columbia, Vancouver, BC

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Introduction: Electronic health record (EHR) implementation can be associated with a slowdown in performance and delayed return to pre go-live productivity. The objective of this study is to describe the impact of a go-live strategy including diversion, public advertising of the go-live, and extra physician staffing to mitigate productivity loss. Methods: Lions Gate Hospital (LGH), an urban community hospital and rural referral centre with 250 beds and 65,000 annual ED visits went live with Cerner HER (Cerner Corporation, Kansas, MO) on April 28, 2018. The implementation included complete electronic ordering and electronic physician documentation. We compared patients seen per hour, time to physician (TTMD), ED length of stay (EDLOS), patients per hour left without being seen (LWBS), and admission rate (AR) for the 6 weeks prior to implementation (Pre), 2 weeks during (Imp), and 6 weeks after (Post) for LGH and a control hospital (Richmond Hospital – comparable in size/acuity) for the same periods. Medians were compared using the Mann-Whitney test for patients/hour, EDLOS and TTMD, and chi-square for AR and LWBS. Results: Patients/hour seen went from 2.1/hour in the pre phase, but dropped to 1.7/hr in the 2 week period following implementation (P < 0.05). During weeks 2-8 post implementation, 2,3 patients per hour were seen (P = 0.38 compared to Pre phase). At the control hospital, patients per hour were comparable across all time periods (Ps > 0.3). Median time to physician was 54, 56, and 54 minutes at LGH for the Pre, Imp, and Post time periods (Ps > 0.3). Median EDLOS was 184, 196, and 184 minutes in the pre, Imp, and post phases (P Imp versus pre = 0.11; Pre versus post = 0.54). LWBS rate was 1.3%, 2.9, and 2.4% (Ps for Imp and Post versus pre <0.05) at LGH, but the pattern was similar for the control hospital (2.9%, 4.1% and 4.0%’ Ps <0.05). There was no significant change in ambulance arrivals or admission rate at either hospital (Ps > 0.2). Conclusion: A deliberate implementation strategy that focuses on ED physician upstaffing and visit diversion can smooth the impact of the implementation of an EHR so that patient care is not impacted significantly. Return to normal productivity occurred by 8 weeks post go-live. We demonstrate a strategy that may support easier implementation at other sites.

Type
Moderated Poster Presentations
Copyright
Copyright © Canadian Association of Emergency Physicians 2019