Evidence map›Paper›PMID 25024757›Full record

ArticleApplied clinical informatics2014

An analysis of free-text alcohol use documentation in the electronic health record: early findings and implications.

Es Chen, M Garcia-Webb

Abstract read
In one paragraph

Article in Applied clinical informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–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

14 citing papers in PubMed.

  1. Validation and Epidemiologic Definition of the Novel Steatotic Liver Disease Nomenclature in a National United States Cohort With Cirrhosis.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2025
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  10. Content and Quality of Free-Text Occupation Documentation in the Electronic Health Record.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016
    Article
  11. Article
  12. Identifying Family History and Substance Use Associations for Adult Epilepsy from the Electronic Health Record.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016
    Article
  13. Automated Extraction of Substance Use Information from Clinical Texts.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2015
    Article
  14. 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

2 authors.

Es ChenBiomedical Informatics Unit - Center for Clinical and Translational Science, University of Vermont , Burlington, VT ; Division of General Internal Medicine - Department of Medicine, University of Vermont , Burlington, VT ; Department of Computer Science, University of Vermont , Burlington, VT.
M Garcia-WebbUniversity of Massachusetts Medical School , Worcester, MA.

Funding

Leveraging the EHR to Collect and Analyze Social, Behavioral & Familial FactorsR01LM011364 · NLM · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI CHEN, ELIZABETH S., MELTON-MEAUX, GENEVIEVE B · 2012 to 2015
$1.4M
NLM NIH HHS R01 LM011364NLM NIH HHS R01LM011364.
6 · The paper itself

Abstract

backgroundAlcohol use is a significant part of a patient's history, but details about consumption are not always documented. Electronic Health Record (EHR) systems have the potential to improve assessment of alcohol use and misuse; however, a challenge is that critical information may be documented primarily in free-text rather than in a structured and standardized format, thereby limiting its use.

objectiveTo characterize the use and contents of free-text documentation for alcohol use in the social history module of an EHR.

methodsThis study involved a retrospective analysis of 500 alcohol use entries that include structured fields as well as a free-text comment field. Two coding schemes were developed and used to analyze these entries for: (1) quantifying the reasons for using free-text comments and (2) categorizing information in the free-text into separate elements. In addition, for entries indicating possible alcohol misuse, a preliminary review of other structured parts of the EHR was conducted to determine if this was also documented elsewhere.

resultsThe top three reasons for using free-text were limited ability to describe alcohol use frequency (75%), amount (22%), and status (18%) with available structured fields. Within the free-text, descriptions of frequency were most common (79%) using words or phrases conveying occasional (61%), daily (13%), or weekly (12%) use. Of the 36 cases suggesting alcohol misuse, 44% had mention of alcohol problems in the problem list or past medical history.

conclusionsBASED ON THE EARLY FINDINGS, IMPLICATIONS FOR IMPROVING THE STRUCTURED COLLECTION AND USE OF ALCOHOL USE INFORMATION IN THE EHR ARE PROVIDED IN FOUR AREAS: (1) system enhancements, (2) user training, (3) decision support, and (4) standards. Next steps include examining how alcohol use is documented in other parts of the EHR (e.g., clinical notes) and how documentation practices vary based on patient, provider, and clinic characteristics.

Indexed as

Alcohol DrinkingElectronic Health RecordsDocumentationHumansPatient CareReference StandardsAlcohol drinkingalcoholismelectronic health recordsmedical history taking

Identifiers

PMID25024757
PMCPMC4081744

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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.