ArticleJournal of the American Medical Informatics Association : JAMIA2013
Relationship between medication event rates and the Leapfrog computerized physician order entry evaluation tool.
Article in Journal of the American Medical Informatics Association : JAMIA, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- A systematic review of the types and causes of prescribing errors generated from using computerized provider order entry systems in primary and secondary care.Journal of the American Medical Informatics Association : JAMIA · 2017Pooled it
- Association of Hospital Public Quality Reporting With Electronic Health Record Medication Safety Performance.JAMA network open · 2021Trial
- Article
- Article
- How Safe are Outpatient Electronic Health Records? An Evaluation of Medication-Related Decision Support using the Ambulatory Electronic Health Record Evaluation Tool.Applied clinical informatics · 2023Article
- Development and pilot evaluation of an electronic health record usability and safety self-assessment tool.JAMIA open · 2022Article
- An e-Delphi study to obtain expert consensus on the level of risk associated with preventable e-prescribing events.British journal of clinical pharmacology · 2022Article
- Implementing Large-Scale Data-Driven Quality Improvement in Assisted Living.Journal of the American Medical Directors Association · 2022Article
- Assessing hospital electronic health record vendor performance across publicly reported quality measures.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Assessment of Electronic Health Record Use Between US and Non-US Health Systems.JAMA internal medicine · 2021Article
- The Development and Piloting of the Ambulatory Electronic Health Record Evaluation Tool: Lessons Learned.Applied clinical informatics · 2021Article
- The tradeoffs between safety and alert fatigue: Data from a national evaluation of hospital medication-related clinical decision support.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- National Trends in the Safety Performance of Electronic Health Record Systems From 2009 to 2018.JAMA network open · 2020Article
- Structured override reasons for drug-drug interaction alerts in electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Data-driven approach to Early Warning Score-based alert management.BMJ open quality · 2018Article
- National trends in safety performance of electronic health record systems in children's hospitals.Journal of the American Medical Informatics Association : JAMIA · 2017Article
- NCPDP recommendations for dose accumulation monitoring in the inpatient setting: Acetaminophen case model, version 1.0.American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists · 2016Article
- Personalization and Patient Involvement in Decision Support Systems: Current Trends.Yearbook of medical informatics · 2015Review
- Patient safety incidents associated with EMR use: Results of a national survey of Swiss physicians.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe Leapfrog CPOE evaluation tool has been promoted as a means of monitoring computerized physician order entry (CPOE). We sought to determine the relationship between Leapfrog scores and the rates of preventable adverse drug events (ADE) and potential ADE. MATERIALS AND
methodsA cross-sectional study of 1000 adult admissions in five community hospitals from October 1, 2008 to September 30, 2010 was performed. Observed rates of preventable ADE and potential ADE were compared with scores reported by the Leapfrog CPOE evaluation tool. The primary outcome was the rate of preventable ADE and the secondary outcome was the composite rate of preventable ADE and potential ADE.
resultsLeapfrog performance scores were highly related to the primary outcome. A 43% relative reduction in the rate of preventable ADE was predicted for every 5% increase in Leapfrog scores (rate ratio 0.57; 95% CI 0.37 to 0.88). In absolute terms, four fewer preventable ADE per 100 admissions were predicted for every 5% increase in overall Leapfrog scores (rate difference -4.2; 95% CI -7.4 to -1.1). A statistically significant relationship between Leapfrog scores and the secondary outcome, however, was not detected. DISCUSSION: Our findings support the use of the Leapfrog tool as a means of evaluating and monitoring CPOE performance after implementation, as addressed by current certification standards.
conclusionsScores from the Leapfrog CPOE evaluation tool closely relate to actual rates of preventable ADE. Leapfrog testing may alert providers to potential vulnerabilities and highlight areas for further improvement.
Indexed as
Identifiers
What OpenQuestion holds
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.