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

Area of Science:

• Health Informatics
• Medical Documentation
• Clinical Workflow Optimization

Background:

• Medical scribes assist providers with electronic health record (EHR) documentation.
• Previous studies suggest scribe benefits, but large-scale quantitative data on workflow impact is lacking.

Purpose of the Study:

• To develop and apply methods using EHR data to quantitatively assess scribe impact on provider documentation time and note composition.
• To evaluate scribe influence on overall documentation time, post-visit work, and note editing patterns.

Main Methods:

• Leveraging electronic health record (EHR) data to identify scribe presence.
• Quantitatively measuring provider documentation time during and after office visits.
• Analyzing note composition, including edits, additions, deletions, and copied/imported text.

Main Results:

• Scribe use was associated with a significant reduction in overall provider documentation time (39% less, p < 0.001).
• Providers using scribes had fewer note edits (8.4% less added text, 4.2% less deleted text, p < 0.001).
• Scribe use led to increased post-visit documentation time for 4 out of 7 providers (p < 0.001) and did not alter copied/imported text.

Conclusions:

• The proposed EHR data-driven methods can quantitatively validate scribe benefits and identify workflow variability.
• Scribes reduce immediate documentation burden but may shift work to post-visit periods for some providers.
• Scribes do not universally improve all facets of clinical documentation workflows.