The impact of electronic health record systems on clinical documentation times: A systematic review

Health Policy. 2018 Aug;122(8):827-836. doi: 10.1016/j.healthpol.2018.05.014. Epub 2018 Jun 5.

Abstract

Background: Effective management of hospital staff time is crucial to quality patient care. Recent years have seen widespread implementation of electronic health record (EHR) systems but the effect of this on documentation time is unknown. This review compares time spent on documentation tasks by hospital staff (physicians, nurses and interns) before and after EHR implementation.

Methods: A systematic search identified 8153 potentially relevant citations. Studies examining proportion of total workload spent on documentation with ≥40 h of staff observation time were included. Meta-analysis was performed for physicians, nurses and interns comparing pre- and post-EHR results. Studies were weighted by person-hours observation time.

Results: Twenty-eight studies met selection criteria. Seventeen were pre-EHR, nine post-EHR and two examined both periods. With implementation of EHR, physicians' documentation time increased from 16% (95% confidence interval (CI) 11-22%) to 28% (95% CI 19-37%), nurses from 9% (95% CI 6-12%) to 23% (95% CI 15-32%) and interns from 20% (95% CI 7-32%) to 26% (95% CI 10-42%).

Conclusions: There is a lack of long-term follow-up on the effects of EHR implementation. Initial adjustment to EHR appears to increase documentation time but there is some evidence that as staff become more familiar with the system, it may ultimately improve work flow.

Keywords: Administrative burden; Documentation; Efficiency; Electronic health record; Hospital staff; Meta-analysis; Systematic review.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't
  • Review
  • Systematic Review

MeSH terms

  • Documentation / statistics & numerical data*
  • Electronic Health Records*
  • Hospitals
  • Humans
  • Patient Care
  • Patient Care Team / statistics & numerical data*
  • Quality of Health Care
  • Time Factors
  • Workload / statistics & numerical data*