Evidence map›Paper›PMID 25829460›Full record

ReviewJournal of the American Medical Informatics Association : JAMIA2015

Recommendations to improve the usability of drug-drug interaction clinical decision support alerts.

Thomas H Payne, Lisa E Hines, Raymond C Chan, Seth Hartman, Joan Kapusnik-Uner, Alissa L Russ, Bruce W Chaffee, Christian Hartman, Victoria Tamis, Brian Galbreth and 14 more

Abstract readConsensus StatementReview
In one paragraph

Review 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 92 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
92citing papers in PubMed, 3 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

92 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Association between e-alert implementation for detection of acute kidney injury and outcomes: a systematic review.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2017
    Pooled it
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  11. Evaluation of an electronic health record Drug Interaction Customization Editor (DICE).American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists · 2024
    Article
  12. Article
  13. Leveraging explainable artificial intelligence to optimize clinical decision support.Journal of the American Medical Informatics Association : JAMIA · 2024
    Article
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32 more citing papers are in PubMed but not listed here.

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

24 authors.

Thomas H PayneDepartment of Medicine, University of Washington, Seattle, WA, USA.
Lisa E HinesDepartment of Pharmacy Practice & Science, The University of Arizona College of Pharmacy, Tucson, AZ, USA.
Raymond C ChanInformation Technology, Sentara Healthcare, Virginia Beach, VA, USA.
Seth HartmanDepartment of Pharmacy Services, Oregon Health & Science University, Portland, OR, USA.
Joan Kapusnik-UnerClinical Editorial, FDB (First Databank, Inc.), San Francisco, CA, USA.
Alissa L RussCenter for Health Information and Communication, Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service, Richard L. Roudebush VA Medical Center; Regenstrief Institute, Inc. Indianapolis, IN USA; and Purdue University College of Pharmacy, West Lafayette, IN USA.
Bruce W ChaffeeDepartment of Pharmacy, The University of Michigan Health System, Ann Arbor, MI, USA.
Christian HartmanClinical Solutions, Pharmacy OneSource, Boston, MA, USA.
Victoria TamisPeaceHealth St. John Medical Center, Longview WA, USA.
Brian GalbrethAt the time of this study was with Pharmacy Services, PeaceHealth Southwest Medical Center, Vancouver, WA, USA.
Peter A GlassmanInternal Medicine, Department of Veterans Affairs (VA), Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
Shobha PhansalkarMedical Informatics, Wolters Kluwer Health - Clinical Solutions, Newton, MA, USA/San Diego, CA, USA.
Heleen van der SijsDepartment of Hospital Pharmacy, Erasmus Medical Center, Rotterdam, Netherlands.
Sheila M GephartCollege of Nursing, The University of Arizona, Tucson, AZ, USA.
Gordon MannPharmacy, Epic, Verona, WI, USA.
Howard R StrasbergMedical Informatics, Wolters Kluwer Health - Clinical Solutions, Newton, MA, USA/San Diego, CA, USA.
Amy J GrizzleCenter for Health Outcomes & PharmacoEconomic Research, The University of Arizona College of Pharmacy, Tucson, AZ, USA.
Mary BrownDepartment of Pharmacy Practice & Science, The University of Arizona College of Pharmacy, Tucson, AZ, USA.
Gilad J KupermanInteroperability Informatics, New York-Presbyterian Hospital, New York, NY, USA.
Chris SteinerEditorial Systems, Gold Standard Drug Databases/Elsevier, Tampa, FL, USA.
Amanda SullinsInformation Technology and Services, Cerner Corporation, Kansas City, MO, USA.
Hugh RyanInformation Technology and Services, Cerner Corporation, Kansas City, MO, USA.
Michael A WittieOffice of Clinical Quality and Safety, Office of the National Coordinator for Health Information Technology, Department of Health and Human Services, Washington, DC, USA.
Daniel C MaloneDepartment of Pharmacy Practice & Science, The University of Arizona College of Pharmacy, Tucson, AZ, USA malone@pharmacy.arizona.edu.

Funding

Clinical decision support optimizing NEC prevention implementation in NICUK08HS022908 · AHRQ · UNIVERSITY OF ARIZONA · PI GEPHART, SHEILA MARIA · 2014 to 2018
$696k
Drug-Drug Interaction Clinical Decision Support Conference SeriesR13HS021826 · AHRQ · UNIVERSITY OF ARIZONA · PI MALONE, DANIEL C · 2012 to 2014
$288k
AHRQ HHS 1K08HS022908-01A1AHRQ HHS 1R13HS021826-01AHRQ HHS K08 HS022908AHRQ HHS R13 HS021826
6 · The paper itself

Abstract

objectiveTo establish preferred strategies for presenting drug-drug interaction (DDI) clinical decision support alerts. MATERIALS AND

methodsA DDI Clinical Decision Support Conference Series included a workgroup consisting of 24 clinical, usability, and informatics experts representing academia, health information technology (IT) vendors, healthcare organizations, and the Office of the National Coordinator for Health IT. Workgroup members met via web-based meetings 12 times from January 2013 to February 2014, and two in-person meetings to reach consensus on recommendations to improve decision support for DDIs. We addressed three key questions: (1) what, how, where, and when do we display DDI decision support? (2) should presentation of DDI decision support vary by clinicians? and (3) how should effectiveness of DDI decision support be measured?

resultsOur recommendations include the consistent use of terminology, visual cues, minimal text, formatting, content, and reporting standards to facilitate usability. All clinicians involved in the medication use process should be able to view DDI alerts and actions by other clinicians. Override rates are common but may not be a good measure of effectiveness. DISCUSSION: Seven core elements should be included with DDI decision support. DDI information should be presented to all clinicians. Finally, in their current form, override rates have limited capability to evaluate alert effectiveness.

conclusionDDI clinical decision support alerts need major improvements. We provide recommendations for healthcare organizations and IT vendors to improve the clinician interface of DDI alerts, with the aim of reducing alert fatigue and improving patient safety.

Indexed as

Drug InteractionsDrug Therapy, Computer-AssistedConsensusHumansMedical Order Entry Systemsalertsclinical decision supportCPOE (up to 5)drug interactionsusability

Identifiers

PMID25829460
PMCPMC11737836

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.