Evidence map›Paper›PMID 26373538›Full record

ArticleBMC health services research2015

A comparison of a multistate inpatient EHR database to the HCUP Nationwide Inpatient Sample.

Jonathan P DeShazo, Mark A Hoffman

Abstract readComparative Study
In one paragraph

Article in BMC health services research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 1 pooled it
–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

51 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Digital Health Data Quality Issues: Systematic Review.Journal of medical Internet research · 2023
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  10. HIBERT: A Hybrid Clustering BERT for Interpretable Opioid Overdose Risk Prediction.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024
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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

2 authors.

Jonathan P DeShazoDepartment of Health Administration, School of Allied Health Professions, Virginia Commonwealth University, Grant House Room 201, 1008 East Clay Street, P.O. Box 980203, Richmond, VA, 23298-0203, USA. jpdeshazo@vcu.edu.
Mark A HoffmanDepartment of Biomedical and Health Informatics, School of Medicine, University of Missouri - Kansas City (UMKC), 2411 Holmes, MG-203B, Kansas City, MO, 64108-2792, USA. hoffmanma@umkc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe growing availability of electronic health records (EHRs) in the US could provide researchers with a more detailed and clinically relevant alternative to using claims-based data.

methodsIn this study we compared a very large EHR database (Health Facts©) to a well-established population estimate (Nationwide Inpatient Sample). Weighted comparisons were made using t-value and relative difference over diagnoses and procedures for the year 2010.

resultsThe two databases have a similar distribution pattern across all data elements, with 24 of 50 data elements being statistically similar between the two data sources. In general, differences that were found are consistent across diagnosis and procedures categories and were specific to the psychiatric-behavioral and obstetrics-gynecology services areas.

conclusionsLarge EHR databases have the potential to be a useful addition to health services researchers, although they require different analytic techniques compared to administrative databases; more research is needed to understand the differences.

Indexed as

Databases, FactualElectronic Health RecordsHealth Services ResearchInpatientsFemaleHumansMaleMiddle AgedUnited States

Identifiers

PMID26373538
PMCPMC4572624

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.