Evidence map›Paper›PMID 31183688›Full record

ArticleJournal of general internal medicine2019

Variation in Physicians' Electronic Health Record Documentation and Potential Patient Harm from That Variation.

Genna R Cohen, Charles P Friedman, Andrew M Ryan, Caroline R Richardson, Julia Adler-Milstein

Abstract read
In one paragraph

Article in Journal of general internal medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
77citing 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

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

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17 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Genna R CohenMathematica, Washington, DC, USA. gcohen@mathematica-mpr.com.
Charles P FriedmanDepartment of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, MI, USA.
Andrew M RyanDepartment of Health Management and Policy, University of Michigan School of Public Health, Ann Arbor, MI, USA.
Caroline R RichardsonDepartment of Family Medicine, University of Michigan Health System, Ann Arbor, MI, USA.
Julia Adler-MilsteinCenter for Clinical Informatics and Improvement Research, University of California San Francisco Department of Medicine, San Francisco, CA, USA.

Funding

AHRQ HHS R36 HS023719
6 · The paper itself

Abstract

backgroundPhysician-to-physician variation in electronic health record (EHR) documentation not driven by patients' clinical status could be harmful.

objectiveMeasure variation in completion of common clinical documentation domains. Identify perceived causes and effects of variation and strategies to mitigate negative effects.

designSequential, explanatory, mixed methods using log data from a commercial EHR vendor and semi-structured interviews with outpatient primary care practices.

participantsQuantitative: 170,332 encounters led by 809 physicians in 237 practices. Qualitative: 40 interviewees in 10 practices. MAIN MEASURES: Interquartile range (IQR) of the proportion of encounters in which a physician completed documentation, for each documentation category. Multilevel linear regression measured the proportion of variation at the physician level. KEY

resultsFive clinical documentation categories had substantial and statistically significant (p < 0.001) variation at the physician level after accounting for state, organization, and practice levels: (1) discussing results (IQR = 50.8%, proportion of variation explained by physician level = 78.1%); (2) assessment and diagnosis (IQR = 60.4%, physician-level variation = 76.0%); (3) problem list (IQR = 73.1%, physician-level variation = 70.1%); (4) review of systems (IQR = 62.3%, physician-level variation = 67.7%); and (5) social history (IQR = 53.3%, physician-level variation = 62.2%). Drivers of variation from interviews included user preferences and EHR designs with multiple places to record similar information. Variation was perceived to create documentation inefficiencies and risk patient harm due to missed or misinterpreted information. Mitigation strategies included targeted user training during EHR implementation and practice meetings focused on documentation standardization.

conclusionsPhysician-to-physician variation in EHR documentation impedes effective and safe use of EHRs, but there are potential strategies to mitigate negative consequences.

Indexed as

AdultAgedAged, 80 and overClinical CompetenceDocumentationElectronic Health RecordsFemaleHumansMaleMiddle AgedPatient HarmPhysiciansdocumentationEHRmixed methodsprimary care

Identifiers

PMID31183688
PMCPMC6848521

What OpenQuestion holds

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Registered trials

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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.