Evidence map›Paper›PMID 35594070›Full record

ArticleJMIR medical informatics2022

Integrated Health Record Viewers and Reduction in Duplicate Medical Imaging: Retrospective Observational Analysis.

Yingzhe Yuan, Megan Price, David F Schmidt, Merry Ward, Jonathan Nebeker, Steven Pizer

Open access · goldAbstract read
In one paragraph

Article in JMIR medical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.6field-weighted citation impact, top 11% of its field
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

3 citing papers in PubMed, 6 citations in OpenAlex.

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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 at 3 institutions in 1 country.

Yingzhe YuanDepartment of Health Law, Policy & Management, School of Public Health, Boston University, Boston, MA, United States.ORCID https://orcid.org/0000-0002-6075-6833
Megan PricePartnered Evidence-Based Policy Resource Center, Boston Veterans Affairs Healthcare System, Boston, MA, United States.ORCID https://orcid.org/0000-0002-5412-8152
David F SchmidtVeterans Health Administration Office of Health Informatics, Department of Veterans Affairs, Washington DC, DC, United States.ORCID https://orcid.org/0000-0001-6799-8782
Merry WardVeterans Health Administration Office of Health Informatics, Department of Veterans Affairs, Washington DC, DC, United States.ORCID https://orcid.org/0000-0002-0330-5083
Jonathan NebekerVeterans Health Administration Office of Health Informatics, Department of Veterans Affairs, Washington DC, DC, United States.ORCID https://orcid.org/0000-0001-5355-5008
Steven PizerDepartment of Health Law, Policy & Management, School of Public Health, Boston University, Boston, MA, United States.ORCID https://orcid.org/0000-0003-4908-5976
United States Department of Veterans Affairs · USBoston University · USVA Boston Healthcare System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth information exchange and multiplatform health record viewers support more informed medical decisions, improve quality of care, and reduce the risk of adverse outcomes due to fragmentation and discontinuity in care during transition of care. An example of a multiplatform health record viewer is the VA/DoD Joint Longitudinal Viewer (JLV), which supports the Department of Veterans Affairs (VA) and Department of Defense (DoD) health care providers with read-only access to patient medical records integrated from multiple sources. JLV is intended to support more informed medical decisions such as reducing duplicate medical imaging when previous image study results may meet current clinical needs.

objectiveWe estimated the impact of provider usage of JLV on duplicate imaging for service members transitioning from the DoD to the VA health care system.

methodsWe conducted a retrospective cross-sectional study in fiscal year 2018 to examine the relationship between providers' use of JLV and the likelihood of ordering duplicate images. Our sample included recently separated service members who had a VA primary care visit in fiscal year 2018 within 90 days of a DoD imaging study. Patients who received at least one imaging study at VA within 90 days of a DoD imaging study of the same imaging mode and on the same body part are considered to have received potentially duplicate imaging studies. We use a logistic regression model with "JLV provider" (providers with 1 or more JLV audits in the prior 6 months) as the independent variable to estimate the relationship between JLV use and ordering of duplicate images. Control variables included provider image ordering rates in the prior 6 months, provider type, patient demographics (age, race, gender), and clinical characteristics (Elixhauser comorbidity score).

resultsProviders known to utilize JLV in the prior 6 months order fewer duplicate images relative to providers not utilizing JLV for similar visits over time (odds ratio 0.44, 95% CI 0.24-0.78; P=.005). This effect is robust across multiple specifications of linear and logistic regression models. The provider's practice pattern of ordering image studies and the patient's health status are powerful confounders.

conclusionsThis study provides evidence that adoption of a longitudinal viewer of health records from multiple electronic health record systems is associated with a reduced likelihood of ordering duplicate images. Investments in health information exchange systems may be effective ways to improve the quality of care and reduce adverse outcomes for patients experiencing fragmentation and discontinuity of care.

Indexed as

duplicate medical imagingelectronic health recordshealth carehealth care systemhealth informaticshealth information exchangehealth recordshealth record viewer

Identifiers

PMID35594070
PMCPMC9166659
OpenAlexW4280506342

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.