Evidence map›Paper›PMID 35673147›Full record

ArticleStudies in health technology and informatics2022

Medical Scribes Have a Variable Impact on Documentation Workflows.

Adam Rule, Michael F Chiang, Michelle R Hribar

Abstract read
In one paragraph

Article in Studies in health technology and informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Adam RuleBiomedical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA.
Michael F ChiangNational Eye Institute, National Institutes of Health, Bethesda, MD, USA.
Michelle R HribarBiomedical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA.

Funding

TRAINING PROGRAM IN HEALTH INFORMATICST15LM007088 · NLM · OREGON HEALTH & SCIENCE UNIVERSITY · PI WILLIAM R HERSH, Vishnu Mohan · 1992 to 2026
$23.4M
Proteomics CoreP30EY010572 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI John Peter Campbell · 1995 to 2026
$19.4M
Operationalizing Machine Learning and Discrete Event Simulation Models to Improve Clinic EfficiencyR01LM013426 · NLM · OREGON HEALTH & SCIENCE UNIVERSITY · PI HRIBAR, MICHELLE · 2020 to 2023
$1.3M
Modeling and Optimization of Clinical Processes Using EHR DataR00LM012238 · NLM · OREGON HEALTH & SCIENCE UNIVERSITY · PI HRIBAR, MICHELLE · 2017 to 2019
$672k
NEI NIH HHS P30 EY010572NLM NIH HHS R00 LM012238NLM NIH HHS R01 LM013426NLM NIH HHS T15 LM007088
6 · The paper itself

Abstract

Physicians can reduce their documentation time by working with a scribe. However, what scribes document and how their actions affect existing documentation workflows is unclear. This study leverages electronic health record (EHR) audit logs to observe how scribes affected the documentation workflows of seven physicians and their staff across 13,000 outpatient ophthalmology visits. In addition to editing progress notes, scribes routinely edited exam findings and diagnoses. Scribes with clinical training also edited items such as vital signs that a scribe without clinical training did not. Every physician edited patient records later in the day when working with a scribe and those who deferred their editing the most had some of the largest reductions in EHR time. These results suggest that what scribes document, how physicians work with scribes, and scribe impact on documentation time are all highly variable, highlighting the need for evidence-based best practices.

Indexed as

DocumentationPhysiciansElectronic Health RecordsHumansWorkflowDocumentationElectronic Health Records

Identifiers

PMID35673147
PMCPMC10477084

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.