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Int J Med Inform. 2010 Jul;79(7):492-500. doi: 10.1016/j.ijmedinf.2010.04.006. Epub 2010 May 15.

Physician productivity and the ambulatory EHR in a large academic multi-specialty physician group.

Author information

  • 1Weill Cornell Medical College, New York, NY, USA. adc9001@med.cornell.edu

Abstract

PURPOSE:

The impact of the ambulatory electronic health record (EHR) on physician productivity is poorly understood. Fear of productivity loss remains a major concern for practitioners and health care delivery organizations and inhibits system adoption. This study describes the changes in physician productivity after the implementation of a commercially available ambulatory EHR system in a large academic multi-specialty physician group.

METHODS:

Weill Cornell faculty members implemented on the EpicCare (Epic Systems) EHR between 2001 and 2007 were identified as potential study participants. Monthly visit volume, charges, and work relative value units (wRVUs) were compared pre and post each provider's EHR implementation go-live date. Practitioners who lacked at least 6 months of pre- and post-implementation visit volume and charge data were excluded. Practitioners who did not meet pre-determined system proficiency metrics were additionally identified and became the basis of a non-adopter comparison group.

RESULTS:

203 physicians met criteria for the analysis. The eligible providers were divided into an adopter and non-adopter cohort based on system proficiency benchmarks. Those practitioners who adopted the EHR had a statistically significant increase in average monthly patient visit volume of 9 visits per provider per month. The non-adopter cohort's visit volume was statistically unchanged. Both the EHR adopters and non-adopters had statistically significant increases (22% and 16% respectively) in average monthly charges in the post-implementation period. Average monthly wRVUs were statistically unchanged in the non-adopter cohort, but showed a positive and statistically significant increase of 12 wRVUs per provider per month for the adopter group. The EHR adoption group showed an incremental increase in productivity once practitioners achieved 6 or more months experience with the EHR, consistent with a "ramp-up" period. A multivariable regression model did not reveal any association between the post-EHR implementation change in wRVUs and several potential confounding variables, including baseline provider average monthly visit volume and wRVUs, date of system adoption, and specialty categorization.

CONCLUSION:

Provider productivity, as measured by patient visit volume, charges, and wRVUs modestly increased for a cohort of multi-specialty providers that adopted a commercially available ambulatory EHR. The productivity gain appeared to become even more pronounced after several months of system experience. This objective data may help persuade apprehensive practitioners that EHR adoption need not harm productivity. The baseline differences in productivity metrics for the adopters and non-adopters in our study suggest that there are fundamental differences in these groups. Further characterizing these differences may help predict EHR adoption success and guide future implementation strategies.

2010 Elsevier Ireland Ltd. All rights reserved.

PMID:
20478738
[PubMed - indexed for MEDLINE]
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