Evidence map›Paper›PMID 26104739›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2015

Cross-vendor evaluation of key user-defined clinical decision support capabilities: a scenario-based assessment of certified electronic health records with guidelines for future development.

Allison B McCoy, Adam Wright, Dean F Sittig

Abstract readEvaluation Study
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the 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.

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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Analysis of clinical decision support system malfunctions: a case series and survey.Journal of the American Medical Informatics Association : JAMIA · 2016
    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

3 authors.

Allison B McCoyDepartment of Biostatistics and Bioinformatics, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA amccoy1@tulane.edu.
Adam WrightDivision of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA Partners HealthCare, Boston, MA, USA Harvard Medical School, Boston, MA, USA.
Dean F SittigThe University of Texas School of Biomedical Informatics at Houston, Houston, TX, USA.

Funding

InSPECt: Interactive Surveillance Portal for Evaluating Clinical supportK22LM011430 · NLM · TULANE UNIVERSITY OF LOUISIANA · PI MCCOY, ALLISON B · 2013 to 2015
$372k
NLM NIH HHS 1 K22 LM011430-01A1NLM NIH HHS K22 LM011430
6 · The paper itself

Abstract

objectiveClinical decision support (CDS) is essential for delivery of high-quality, cost-effective, and safe healthcare. The authors sought to evaluate the CDS capabilities across electronic health record (EHR) systems.

methodsWe evaluated the CDS implementation capabilities of 8 Office of the National Coordinator for Health Information Technology Authorized Certification Body (ONC-ACB)-certified EHRs. Within each EHR, the authors attempted to implement 3 user-defined rules that utilized the various data and logic elements expected of typical EHRs and that represented clinically important evidenced-based care. The rules were: 1) if a patient has amiodarone on his or her active medication list and does not have a thyroid-stimulating hormone (TSH) result recorded in the last 12 months, suggest ordering a TSH; 2) if a patient has a hemoglobin A1c result >7% and does not have diabetes on his or her problem list, suggest adding diabetes to the problem list; and 3) if a patient has coronary artery disease on his or her problem list and does not have aspirin on the active medication list, suggest ordering aspirin.

resultsMost evaluated EHRs lacked some CDS capabilities; 5 EHRs were able to implement all 3 rules, and the remaining 3 EHRs were unable to implement any of the rules. One of these did not allow users to customize CDS rules at all. The most frequently found shortcomings included the inability to use laboratory test results in rules, limit rules by time, use advanced Boolean logic, perform actions from the alert interface, and adequately test rules.

conclusionSignificant improvements in the EHR certification and implementation procedures are necessary.

Indexed as

CertificationCommerceDecision Support Systems, ClinicalElectronic Health RecordsGuidelines as Topicclinicaldecision support systemselectronic health records

Identifiers

PMID26104739
PMCPMC5009930

What OpenQuestion holds

Textmetadata
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.