Evidence map›Paper›PMID 29295287›Full record

ArticleStudies in health technology and informatics2017

Analysis of Clinical Variations in Asthma Care Documented in Electronic Health Records Between Staff and Resident Physicians.

Sunghwan Sohn, Chung-Il Wi, Young J Juhn, Hongfang Liu

Abstract read
In one paragraph

Article in Studies in health technology and informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Leveraging Electronic Health Records for Guideline-Based Asthma Documentation.The journal of allergy and clinical immunology. In practice · 2023
    Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. 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

4 authors.

Sunghwan SohnDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Chung-Il WiDepartment of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN, USA.
Young J JuhnDepartment of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN, USA.
Hongfang LiuDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.

Funding

Semi-structured Information Retrieval in Clinical Text for Cohort IdentificationR01LM011934 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI HERSH, WILLIAM R, LIU, HONGFANG · 2014 to 2025
$5.1M
Identification and characterization of children with asthma-associated comorbidities through computational and immune phenotypingR01HL126667 · NHLBI · MAYO CLINIC ROCHESTER · PI JUHN, YOUNG J, LIU, HONGFANG · 2015 to 2022
$4.3M
Secondary use of EMRs for surgical complication surveillanceR01EB019403 · NIBIB · MAYO CLINIC ROCHESTER · PI LIU, HONGFANG, STORLIE, CURTIS · 2015 to 2022
$3.8M
Natural language processing for clinical and translational researchR01GM102282 · NIGMS · MAYO CLINIC ROCHESTER · PI LIU, HONGFANG, PAKHOMOV, SERGUEI VS · 2013 to 2016
$2.5M
NHLBI NIH HHS R01 HL126667NIBIB NIH HHS R01 EB019403NIGMS NIH HHS R01 GM102282NLM NIH HHS R01 LM011934
6 · The paper itself

Abstract

Clinical documentation using free text to describe a patient's medical status is an essential component of electronic health records (EHRs), and the quality of information in documents plays a critical role in clinical practice and translational research. Physicians are the primary creators of EHRs, but their clinical practices vary substantially, resulting in variations in clinical documentation. These variations can represent a source for potential bias in clinical outcomes and downstream applications using EHRs. Asthma is one example, presenting an inconsistent ascertainment process and criteria. A recent study revealed that resident physicians' knowledge of asthma diagnosis and management is relatively limited. In this study, we examined clinical documentation variations in asthma care between staff and resident physicians using individual words, topics, and asthma-related concepts in EHR clinical narratives. Additionally, we discuss potential biases in building an informatics model and further compare asthma diagnosis and outcomes between two physician groups.

Indexed as

DocumentationElectronic Health RecordsAsthmaHumansInternship and ResidencyPhysiciansAsthmaDocumentationElectronic Health Records

Identifiers

PMID29295287
PMCPMC5859932

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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.