Evidence map›Paper›PMID 27274014›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2017

Which veterans enroll in a VA health information exchange program?

Brian E Dixon, Susan Ofner, Susan M Perkins, Laura J Myers, Marc B Rosenman, Alan J Zillich, Dustin D French, Michael Weiner, David A Haggstrom

Registry-linked trialAbstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01446705 (Evaluation of VLER_Indiana Health Information Exchange Demonstration Project), which is not on this map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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.

NCT01446705 completednot on this map

Evaluation of VLER_Indiana Health Information Exchange Demonstration Project

TypeobservationalSponsorVA Office of Research and DevelopmentRan2012 to 2016Enrolled57,073ConditionsDiabetes Mellitus, Asthma, Cardiovascular Diseases, Heart FailureArmsActive Health Information Exchange, Non-Active Health Information exchange
3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Racial differences in patient consent policy preferences for electronic health information exchange.Journal of the American Medical Informatics Association : JAMIA · 2020
    Article
  6. Article
  7. Article
  8. 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

9 authors.

Brian E DixonCenter for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, IN bedixon@iupui.edu.
Susan OfnerDepartment of Biostatistics, School of Medicine, Indiana University.
Susan M PerkinsRichard M. Fairbanks School of Public Health, Indiana University.
Laura J MyersCenter for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, IN.
Marc B RosenmanDepartment of Pediatrics, Children's Health Services Research, Indiana University.
Alan J ZillichCenter for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, IN.
Dustin D FrenchDepartment of Ophthalmology and Center for Healthcare Studies, Feinberg School of Medicine, Northwestern University, Chicago, IL.
Michael WeinerCenter for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, IN.
David A HaggstromCenter for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, IN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo characterize patients who voluntarily enrolled in an electronic health information exchange (HIE) program designed to share data between Veterans Health Administration (VHA) and non-VHA institutions. MATERIALS AND

methodsPatients who agreed to participate in the HIE program were compared to those who did not. Patient characteristics associated with HIE enrollment were examined using a multivariable logistic regression model. Variables selected for inclusion were guided by a health care utilization model adapted to explain HIE enrollment. Data about patients' sociodemographics (age, gender), comorbidity (Charlson index score), utilization (primary and specialty care visits), and access (distance to VHA medical center, insurance, VHA benefits) were obtained from VHA and HIE electronic health records.

resultsAmong 57 072 patients, 6627 (12%) enrolled in the HIE program during its first year. The likelihood of HIE enrollment increased among patients ages 50-64, of female gender, with higher comorbidity, and with increasing utilization. Living in a rural area and being unmarried were associated with decreased likelihood of enrollment. DISCUSSION AND

conclusionEnrollment in HIE is complex, with several factors involved in a patient's decision to enroll. To broaden HIE participation, populations less likely to enroll should be targeted with tailored recruitment and educational strategies. Moreover, inclusion of special populations, such as patients with higher comorbidity or high utilizers, may help refine the definition of success with respect to HIE implementation.

Indexed as

VeteransAdultAgedFemaleHealth Information ExchangeHumansLogistic ModelsMaleMatched-Pair AnalysisMedical Records Systems, ComputerizedMiddle AgedUnited StatesUnited States Department of Veterans Affairscomputerizedhealth information exchangematched-pair analysismedical records systemsveterans health

Identifiers

PMID27274014
PMCPMC7654084

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.