Evidence map›Paper›PMID 30153926›Full record

ArticleInternational journal of medical informatics2018

Best practices for preventing malfunctions in rule-based clinical decision support alerts and reminders: Results of a Delphi study.

Adam Wright, Joan S Ash, Skye Aaron, Angela Ai, Thu-Trang T Hickman, Jane F Wiesen, William Galanter, Allison B McCoy, Richard Schreiber, Christopher A Longhurst and 1 more

Abstract read
In one paragraph

Article in International journal of medical informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

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

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Clinical decision support malfunctions related to medication routes: a case series.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  6. Article
  7. Clinician collaboration to improve clinical decision support: the Clickbusters initiative.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Structured override reasons for drug-drug interaction alerts in electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2019
    Article
  17. 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

11 authors.

Adam WrightDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, United States; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States; Information Systems, Partners HealthCare, Boston, MA, United States. Electronic address: awright@bwh.harvard.edu.
Joan S AshDepartment of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, United States.
Skye AaronDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, United States.
Angela AiSchool of Medicine and Public Health, University of Wisconsin at Madison, Madison, WI, United States.
Thu-Trang T HickmanInformation Systems, Partners HealthCare, Boston, MA, United States.
Jane F WiesenDepartment of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, United States.
William GalanterDepartment of Medicine, University of Illinois at Chicago, Chicago, IL, United States.
Allison B McCoyDepartment of Global Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States.
Richard SchreiberPhysician Informatics and Department of Internal Medicine, Geisinger Holy Spirit, Camp Hill, PA, United States.
Christopher A LonghurstDepartment of Biomedical Informatics, University of California San Diego, San Diego, CA, United States.
Dean F SittigSchool of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States.

Funding

Improving clinical decision support reliability using anomaly detection methodsR01LM011966 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI WRIGHT, ADAM T · 2014 to 2017
$2.4M
NLM NIH HHS R01 LM011966
6 · The paper itself

Abstract

objectiveDeveloping effective and reliable rule-based clinical decision support (CDS) alerts and reminders is challenging. Using a previously developed taxonomy for alert malfunctions, we identified best practices for developing, testing, implementing, and maintaining alerts and avoiding malfunctions. MATERIALS AND

methodsWe identified 72 initial practices from the literature, interviews with subject matter experts, and prior research. To refine, enrich, and prioritize the list of practices, we used the Delphi method with two rounds of consensus-building and refinement. We used a larger than normal panel of experts to include a wide representation of CDS subject matter experts from various disciplines.

results28 experts completed Round 1 and 25 completed Round 2. Round 1 narrowed the list to 47 best practices in 7 categories: knowledge management, designing and specifying, building, testing, deployment, monitoring and feedback, and people and governance. Round 2 developed consensus on the importance and feasibility of each best practice. DISCUSSION: The Delphi panel identified a range of best practices that may help to improve implementation of rule-based CDS and avert malfunctions. Due to limitations on resources and personnel, not everyone can implement all best practices. The most robust processes require investing in a data warehouse. Experts also pointed to the issue of shared responsibility between the healthcare organization and the electronic health record vendor.

conclusionThese 47 best practices represent an ideal situation. The research identifies the balance between importance and difficulty, highlights the challenges faced by organizations seeking to implement CDS, and describes several opportunities for future research to reduce alert malfunctions.

Indexed as

Delphi TechniqueElectronic Health RecordsConsensusDecision Support Systems, ClinicalHumansMedical ErrorsPractice Guidelines as TopicBest practicesClinical decision supportElectronic health recordsSafety

Identifiers

PMID30153926
PMCPMC6128667

What OpenQuestion holds

Textmetadata
LicenceTDM
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.