Influence of electronic medical record implementation on provider retirement at a major academic medical centre

J Eval Clin Pract. 2016 Apr;22(2):222-6. doi: 10.1111/jep.12458. Epub 2015 Sep 22.

Abstract

Rationale, aims and objectives: The push for electronic medical record (EMR) implementation is grounded on increasing efficiency and cost savings. Our objective was to investigate the effect of EMR implementation on provider attrition.

Methods: We completed a retrospective study investigating whether medical provider attrition, clinical MD or equivalent, coincided with EMR implementation. We analysed monthly provider attrition rates and mean age at attrition 24 months preceding the EMR 'go-live' date at our institution and 12 months after.

Results: 208 provider departures occurred between July 2011 and June 2014. The attrition categories were classified as 'departure' (n = 137, 65.9%), 'emeritus' (n = 30; 14.4%), 'no specified reason' (n = 26; 12.5%) and 'not reappointed' (n = 15; 7.2). The most common degree held by departing providers was 'MD' (n = 170; 81.7%). Most departures occurred in June 2013 (n = 24). The mean provider age at departure was 46.4 years ± 2.9 years for June 2012, 48.1 years ± 2.5 years for June 2013 and 45.0 years ± 4.1 years for June 2014. Our data indicate a trend for both an increase in number of departing providers, as well as an increased mean age in the month immediately prior to EMR implementation.

Conclusion: To date, no other investigation of the effect of EMR implementation of provider retirements have been published. We demonstrate a peak in provider attrition in the month prior to EMR implementation that may not be explained by normal attrition patterns with an academic calendar.

Level of evidence: Level 5 - qualitative or descriptive study.

Keywords: attrition; electronic medical record; human resources; retirement.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Academic Medical Centers / organization & administration*
  • Adult
  • Age Factors
  • Electronic Health Records / statistics & numerical data*
  • Humans
  • Middle Aged
  • Physicians / statistics & numerical data*
  • Retirement / statistics & numerical data*
  • Retrospective Studies
  • United States