Evidence map›Paper›PMID 32469412›Full record

ArticleJAMA network open2020

National Trends in the Safety Performance of Electronic Health Record Systems From 2009 to 2018.

David C Classen, A Jay Holmgren, Zoe Co, Lisa P Newmark, Diane Seger, Melissa Danforth, David W Bates

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
16.7field-weighted citation impact, top 1% 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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 82 citations in OpenAlex.

  1. Common Barriers to Reporting Medical Errors.TheScientificWorldJournal · 2021
    Pooled it
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  16. Examining medication ordering errors using AHRQ network of patient safety databases.Journal of the American Medical Informatics Association : JAMIA · 2023
    Observational
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

David C ClassenDivision of Clinical Epidemiology, University of Utah School of Medicine, Salt Lake City.
A Jay HolmgrenHarvard Business School, Boston, Massachusetts.
Zoe CoDepartment of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Lisa P NewmarkClinical and Quality Analysis, Partners Healthcare, Somerville, Massachusetts.
Diane SegerClinical and Quality Analysis, Partners Healthcare, Somerville, Massachusetts.
Melissa DanforthThe Leapfrog Group, Washington, DC.
David W BatesDepartment of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Mass General Brigham · USBrigham and Women's Hospital · USLeapfrog Group · USUniversity of Utah · US

Funding

Ensuring Safe Performance of Electronic Health RecordsR01HS023696 · AHRQ · BRIGHAM AND WOMEN'S HOSPITAL · PI BATES, DAVID W., MD,MSC · 2014 to 2014
$1.2M
AHRQ HHS R01 HS023696
6 · The paper itself

Abstract

Importance: Despite the broad adoption of electronic health record (EHR) systems across the continuum of care, safety problems persist. Objective: To measure the safety performance of operational EHRs in hospitals across the country during a 10-year period. Design, Setting, and Participants: This case series included all US adult hospitals nationwide that used the National Quality Forum Health IT Safety Measure EHR computerized physician order entry safety test administered by the Leapfrog Group between 2009 and 2018. Data were analyzed from July 1, 2018 to December 1, 2019. Exposure: The Health IT Safety Measure test, which uses simulated medication orders that have either injured or killed patients previously to evaluate how well hospital EHRs could identify medication errors with potential for patient harm. Main Outcomes and Measures: Descriptive statistics for performance on the assessment test over time were calculated at the overall test score level, type of decision support category level, and EHR vendor level. Results: Among 8657 hospital-years observed during the study, mean (SD) scores on the overall test increased from 53.9% (18.3%) in 2009 to 65.6% (15.4%) in 2018. Mean (SD) hospital score for the categories representing basic clinical decision support increased from 69.8% (20.8%) in 2009 to 85.6% (14.9%) in 2018. For the categories representing advanced clinical decision support, the mean (SD) score increased from 29.6% (22.4%) in 2009 to 46.1% (21.6%) in 2018. There was considerable variation in test performance by EHR. Conclusions and Relevance: These findings suggest that despite broad adoption and optimization of EHR systems in hospitals, wide variation in the safety performance of operational EHR systems remains across a large sample of hospitals and EHR vendors. Hospitals using some EHR vendors had significantly higher test scores. Overall, substantial safety risk persists in current hospital EHR systems.

Indexed as

Electronic Health RecordsPatient SafetyDecision Support Systems, ClinicalHospitalsHumansMedical ErrorsMedical Order Entry SystemsUnited States

Identifiers

PMID32469412
PMCPMC7260621
OpenAlexW3029192982

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.