Evidence map›Paper›PMID 26958171›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium

Mining and Visualizing Family History Associations in the Electronic Health Record: A Case Study for Pediatric Asthma.

Elizabeth S Chen, Genevieve B Melton, Richard C Wasserman, Paul T Rosenau, Diantha B Howard, Indra Neil Sarkar

Abstract read
PubMed Full text at PMC
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Systematic Analysis of Free-Text Family History in Electronic Health Record.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2017
    Article
  3. Identifying Psychiatric Comorbidities for Obstructive Sleep Apnea in the Biomedical Literature and Electronic Health Record.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2017
    Article
  4. 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
  5. Comparative effects ofAvicenna journal of phytomedicine
    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

6 authors.

Elizabeth S ChenCenter for Biomedical Informatics, Warren Alpert Medical School of Brown University, Providence, RI; Center for Clinical and Translational Science, University of Vermont, Burlington, VT.
Genevieve B MeltonInstitute for Health Informatics, University of Minnesota, Minneapolis, MN; Department of Surgery, University of Minnesota, Minneapolis, MN.
Richard C WassermanDepartment of Pediatrics, University of Vermont, Burlington, VT; University of Vermont Children's Hospital, Burlington, VT.
Paul T RosenauDepartment of Pediatrics, University of Vermont, Burlington, VT; University of Vermont Children's Hospital, Burlington, VT.
Diantha B HowardCenter for Clinical and Translational Science, University of Vermont, Burlington, VT.
Indra Neil SarkarCenter for Biomedical Informatics, Warren Alpert Medical School of Brown University, Providence, RI; Center for Clinical and Translational Science, University of Vermont, Burlington, VT.

Funding

University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR000114 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R · 2012 to 2015
$35.0M
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
NCATS NIH HHS UL1 TR000114NLM NIH HHS R01 LM011364
6 · The paper itself

Abstract

Asthma is the most common chronic childhood disease and has seen increasing prevalence worldwide. While there is existing evidence of familial and other risk factors for pediatric asthma, there is a need for further studies to explore and understand interactions among these risk factors. The goal of this study was to develop an approach for mining, visualizing, and evaluating association rules representing pairwise interactions among potential familial risk factors based on information documented as part of a patient's family history in the electronic health record. As a case study, 10,260 structured family history entries for a cohort of 1,531 pediatric asthma patients were extracted and analyzed to generate family history associations at different levels of granularity. The preliminary results highlight the potential of this approach for validating known knowledge and suggesting opportunities for further investigation that may contribute to improving prediction of asthma risk in children.

Indexed as

Medical History TakingAdolescentAsthmaChildChild, PreschoolData MiningElectronic Health RecordsFemaleHumansMaleRisk Factors

Identifiers

PMID26958171
PMCPMC4765567

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.