The Limits of Humans in Data Gathering: Documentation Error Rates in the Electronic Health Record in the Operating Room

We studied the accuracy of nursing electronic health record (EHR) documentation during surgical procedures focusing on time-stamping of events. In high-end manufacturing these tasks would be considered simple routine with error rates of 0.1% to 0.5%. Documentation accuracy of six key events over 10 consecutive weeks was measured. Error rates, delays in documentation, and environmental variables including operating room (OR) size, number of nurses per OR, and service line were recorded. Statistical methods included regression models, correlation analysis and analysis of variance (ANOVA). From 202 cases, 98.10% of 1240 events were captured, revealing an overall error rate of 17.01%. Delays in documentation were observed in 51.40% of events. Larger ORs, multiple nurses documenting, and delays over 20 min were linked to higher error rates. Error rates increased from 1.30% without delays to 38.43% with delays exceeding 20 min. Documentation error rates for time-stamping tasks were at a minimum 2.6 times higher than predicted and increased significantly with delays in documentation indicating that environmental complexity and stress diminish human tasks performance as well as recall of events. Our data indicate that error rates in the healthcare space are higher than in the manufacturing space for tasks of identical or similar complexity. Given the certainty and immutability of human error in task performance, our findings highlight the need for technologies to improve accuracy of EHR documentation in this critical and high complexity space.

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Publication Details

Journal
Journal of Medical Systems
Published
2026-02-09
DOI
https://doi.org/10.1007/s10916-026-02346-9
Primary Topic
Electronic Health Records Systems
Type
article
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article

The Limits of Humans in Data Gathering: Documentation Error Rates in the Electronic Health Record in the Operating Room

Andrew Bradley, Peter Nichol, Abner M.P. Barbosa, Logan Younk et al.
Journal of Medical Systems
Electronic Health Records Systems
article

The Limits of Humans in Data Gathering: Documentation Error Rates in the Electronic Health Record in the Operating Room

Andrew Bradley, Peter Nichol, Abner M.P. Barbosa, Logan Younk, Naila Camila da [UNESP] Rocha
article en

Abstract

We studied the accuracy of nursing electronic health record (EHR) documentation during surgical procedures focusing on time-stamping of events. In high-end manufacturing these tasks would be considered simple routine with error rates of 0.1% to 0.5%. Documentation accuracy of six key events over 10 consecutive weeks was measured. Error rates, delays in documentation, and environmental variables including operating room (OR) size, number of nurses per OR, and service line were recorded. Statistical methods included regression models, correlation analysis and analysis of variance (ANOVA). From 202 cases, 98.10% of 1240 events were captured, revealing an overall error rate of 17.01%. Delays in documentation were observed in 51.40% of events. Larger ORs, multiple nurses documenting, and delays over 20 min were linked to higher error rates. Error rates increased from 1.30% without delays to 38.43% with delays exceeding 20 min. Documentation error rates for time-stamping tasks were at a minimum 2.6 times higher than predicted and increased significantly with delays in documentation indicating that environmental complexity and stress diminish human tasks performance as well as recall of events. Our data indicate that error rates in the healthcare space are higher than in the manufacturing space for tasks of identical or similar complexity. Given the certainty and immutability of human error in task performance, our findings highlight the need for technologies to improve accuracy of EHR documentation in this critical and high complexity space.

Journal of Medical SystemsVol. 50(1)
University of Wisconsin–Madison (US), U.S. Dairy Forage Research Center (US)
Openalex Percentile: Top 64%
Electronic Health Records Systems
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