Methods for Large-Scale Quantitative Analysis of Scribe Impacts on Clinical Documentation

Michelle R. Hribar, Haley L. Dusek, Isaac H. Goldstein, Adam Rule, Michael F. Chiang

Research output: Contribution to journalArticlepeer-review

Abstract

Many medical providers employ scribes to manage electronic health record (EHR) documentation. Prior studies have shown the benefits of scribes, but no large-scale study has quantitively assessed scribe impact on documentation workflows. We propose methods that leverage EHR data for identifying scribe presence during an office visit, measuring provider documentation time, and determining how notes are edited and composed. In a case study, we found scribe use was associated with less provider documentation time overall (averaging 2.4 minutes or 39% less time, p < 0.001), fewer note edits by providers (8.4% less added and 4.2% less deleted text, p < 0.001), but significantly more documentation time after the visit for four out of seven providers (p < 0.001) and no change in the amount of copied and imported note text. Our methods could validate prior study results, identify variability for determining best practices, and determine that scribes do not improve all aspects of documentation.

Original languageEnglish (US)
Pages (from-to)573-582
Number of pages10
JournalAMIA ... Annual Symposium proceedings. AMIA Symposium
Volume2020
StatePublished - 2020

ASJC Scopus subject areas

  • Medicine(all)

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