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J Am Med Inform Assoc. 2014 Oct;21(e2):e332-40. doi: 10.1136/amiajnl-2013-002279. Epub 2014 Apr 29.

Evaluation of medication alerts in electronic health records for compliance with human factors principles.

Author information

1
Partners Healthcare Systems, Inc., Wellesley, Massachusetts, USA Division of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA Harvard Medical School, Boston, Massachusetts, USA Wolters Kluwer Health, Indianapolis, Indiana, USA.
2
Partners Healthcare Systems, Inc., Wellesley, Massachusetts, USA.
3
Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Heidelberg, Germany.
4
Partners Healthcare Systems, Inc., Wellesley, Massachusetts, USA Division of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA Harvard Medical School, Boston, Massachusetts, USA.

Abstract

INTRODUCTION:

Increasing the adoption of electronic health records (EHRs) with integrated clinical decision support (CDS) is a key initiative of the current US healthcare administration. High over-ride rates of CDS alerts strongly limit these potential benefits. As a result, EHR designers aspire to improve alert design to achieve better acceptance rates. In this study, we evaluated drug-drug interaction (DDI) alerts generated in EHRs and compared them for compliance with human factors principles.

METHODS:

We utilized a previously validated questionnaire, the I-MeDeSA, to assess compliance with nine human factors principles of DDI alerts generated in 14 EHRs. Two reviewers independently assigned scores evaluating the human factors characteristics of each EHR. Rankings were assigned based on these scores and recommendations for appropriate alert design were derived.

RESULTS:

The 14 EHRs evaluated in this study received scores ranging from 8 to 18.33, with a maximum possible score of 26. Cohen's κ (κ=0.86) reflected excellent agreement among reviewers. The six vendor products tied for second and third place rankings, while the top system and bottom five systems were home-grown products. The most common weaknesses included the absence of characteristics such as alert prioritization, clear and concise alert messages indicating interacting drugs, actions for clinical management, and a statement indicating the consequences of over-riding the alert.

CONCLUSIONS:

We provided detailed analyses of the human factors principles which were assessed and described our recommendations for effective alert design. Future studies should assess whether adherence to these recommendations can improve alert acceptance.

KEYWORDS:

Clinical Decision Support; Drug Drug Interaction; EHRs; Electronic Health Records; Human Factors; Medication-Related Decision Support

PMID:
24780721
PMCID:
PMC4173170
DOI:
10.1136/amiajnl-2013-002279
[Indexed for MEDLINE]
Free PMC Article

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