Use of electronic clinical documentation: time spent and team interactions
Open accessAbstract
OBJECTIVE: To measure the time spent authoring and viewing documentation and to study patterns of usage in healthcare practice. DESIGN: Audit logs for an electronic health record were used to calculate rates, and social network analysis was applied to ascertain usage patterns. Subjects comprised all care providers at an urban academic medical center who authored or viewed electronic documentation. MEASUREMENT: Rate and time of authoring and viewing clinical documentation, and associations among users were measured. RESULTS: Users spent 20-103 min per day authoring notes and 7-56 min per day viewing notes, with physicians spending less than 90 min per day total. About 16% of attendings' notes, 8% of residents' notes, and 38% of nurses' notes went unread by other users, and, overall, 16% of notes were never read by anyone. Viewing of notes dropped quickly with the age of the note, but notes were read at a low but measurable rate, even after 2 years. Most healthcare teams (77%) included a nurse, an attending, and a resident, and those three users' groups were the first to write notes during an admission. Limitations The limitations were restriction to a single academic medical center and use of log files without direct observation. CONCLUSIONS: Care providers spend a significant amount of time viewing and authoring notes. Many notes are never read, and rates of usage vary significantly by author and viewer. While the rate of viewing a note drops quickly with its age, even after 2 years inpatient notes are still viewed.
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Studies using raw audit logs fit into three broad categories: manual mapping, identification of networks, application of automatic methods.
“Studies using raw audit logs fit into three broad categories:”
From Electronic health record activity changes around new decision support implementation: monitoring using audit logs and topic modeling (2025) · cites this paper as [80]
The Methods section (page unavailable) describes a study using detailed electronic health record usage logs and social network analysis, so this paper exemplifies a study in the network category. The Introduction lists three potential ways audit logs could advance informatics, but it does not classify studies into the three claimed categories of manual mapping, network identification, and automatic methods. (LLM, conf=0.82)
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- Authors
- Hripcsak, G., Vawdrey, D. K., Fred, M. R., & Bostwick, S. B.
- Affiliations
- NewYork–Presbyterian Hospital (US)
- Weill Cornell Medicine (US)
- Corresponding author
- Hripcsak, G.
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-03-01
- Volume
- 18
- Issue
- 2
- Pages
- 112-117
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC3116265
- OpenAlex
- W1800226305
- Cited by
- 175
- References
- 25
- Citations by year
- 2026: 10 · 2025: 6 · 2024: 10 · 2023: 8 · 2022: 7 · 2021: 12 · 2020: 8 · 2019: 20 · 2018: 14 · 2017: 10 · 2016: 14 · 2015: 16 · 2014: 14 · 2013: 11 · 2012: 13
- FWCI
- 20.51
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Agency for Healthcare Research and Quality (R03HS018250)
- U.S. National Library of Medicine (LM006910, R01LM006910)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Keywords
- electronic health records, clinical documentation, documentation time, team interaction, social network analysis, medical residents, nurses, academic medical centers, audit logs
- MeSH terms
- Documentation, Humans, Management Audit, Patient Care Team, Practice Patterns, Physicians', Sociometric Techniques, Time Factors, United States, Cluster Analysis, Information Dissemination, Electronic Health Records
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