High-priority drug-drug interactions for use in electronic health records

被引:98
|
作者
Phansalkar, Shobha [1 ,2 ,3 ]
Desai, Amrita A.
Bell, Douglas [4 ,5 ]
Yoshida, Eileen
Doole, John
Czochanski, Melissa
Middleton, Blackford [2 ,3 ]
Bates, David W. [2 ,3 ]
机构
[1] Partners Healthcare Syst Inc, CIRD, Wellesley, MA 02481 USA
[2] Brigham & Womens Hosp, Div Gen Internal Med & Primary Care, Boston, MA 02115 USA
[3] Harvard Univ, Sch Med, Boston, MA USA
[4] RAND Corp, Santa Monica, CA USA
[5] Univ Calif Los Angeles, David Geffen Sch Med, Dept Med, Los Angeles, CA 90095 USA
关键词
DECISION-SUPPORT; AMBULATORY-CARE; ORDER ENTRY; ALERTS; TRIAL;
D O I
10.1136/amiajnl-2011-000612
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Objective To develop a set of high-severity, clinically significant drug-drug interactions (DDIs) for use in electronic health records (EHRs). Methods A panel of experts was convened with the goal of identifying critical DDIs that should be used for generating medication-related decision support alerts in all EHRs. Panelists included medication knowledge base vendors, EHR vendors, in-house knowledge base developers from academic medical centers, and both federal and private agencies involved in the regulation of medication use. Candidate DDIs were assessed by the panel based on the consequence of the interaction, severity levels assigned to them across various medication knowledge bases, availability of therapeutic alternatives, monitoring/management options, predisposing factors, and the probability of the interaction based on the strength of evidence available in the literature. Results Of 31 DDIs considered to be high risk, the panel approved a final list of 15 interactions. Panelists agreed that this list represented drugs that are contraindicated for concurrent use, though it does not necessarily represent a complete list of all such interacting drug pairs. For other drug interactions, severity may depend on additional factors, such as patient conditions or timing of co-administration. Discussion The panel provided recommendations on the creation, maintenance, and implementation of a central repository of high severity interactions. Conclusions A set of highly clinically significant drug-drug interactions was identified, for which warnings should be generated in all EHRs. The panel highlighted the complexity of issues surrounding development and implementation of such a list.
引用
收藏
页码:735 / 743
页数:9
相关论文
共 50 条
  • [1] Criteria for assessing high-priority drug-drug interactions for clinical decision support in electronic health records
    Shobha Phansalkar
    Amrita Desai
    Anish Choksi
    Eileen Yoshida
    John Doole
    Melissa Czochanski
    Alisha D Tucker
    Blackford Middleton
    Douglas Bell
    David W Bates
    BMC Medical Informatics and Decision Making, 13
  • [2] Criteria for assessing high-priority drug-drug interactions for clinical decision support in electronic health records
    Phansalkar, Shobha
    Desai, Amrita
    Choksi, Anish
    Yoshida, Eileen
    Doole, John
    Czochanski, Melissa
    Tucker, Alisha D.
    Middleton, Blackford
    Bell, Douglas
    Bates, David W.
    BMC MEDICAL INFORMATICS AND DECISION MAKING, 2013, 13
  • [3] Variation in high-priority drug-drug interaction alerts across institutions and electronic health records
    McEvoy, Dustin S.
    Sittig, Dean F.
    Hickman, Thu-Trang
    Aaron, Skye
    Ai, Angela
    Amato, Mary
    Bauer, David W.
    Fraser, Gregory M.
    Harper, Jeremy
    Kennemer, Angela
    Krall, Michael A.
    Lehmann, Christoph U.
    Malhotra, Sameer
    Murphy, Daniel R.
    O'Kelley, Brandi
    Samal, Lipika
    Schreiber, Richard
    Singh, Hardeep
    Thomas, Eric J.
    Vartian, Carl V.
    Westmorland, Jennifer
    Mccoy, Allison B.
    Wright, Adam
    JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2017, 24 (02) : 331 - 338
  • [4] High-priority and low-priority drug-drug interactions in different international electronic health record systems: A comparative study
    Cornu, Pieter
    Phansalkar, Shobha
    Seger, Diane L.
    Cho, Insook
    Pontefract, Sarah
    Robertson, Alexandra
    Bates, David W.
    Slight, Sarah P.
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2018, 111 : 165 - 171
  • [5] Using Linked Data for Mining Drug-Drug Interactions in Electronic Health Records
    Pathak, Jyotishman
    Kiefer, Richard C.
    Chute, Christopher G.
    MEDINFO 2013: PROCEEDINGS OF THE 14TH WORLD CONGRESS ON MEDICAL AND HEALTH INFORMATICS, PTS 1 AND 2, 2013, 192 : 682 - 686
  • [6] Predictors of exposure to high-priority drug-drug interactions among non-elderly adults in Quebec, Canada
    Reyes, Araceli Gonzalez
    Schuster, Tibor
    ANNALS OF FAMILY MEDICINE, 2024, 22
  • [7] Semi-Supervised Learning Algorithm for Identifying High-Priority Drug-Drug Interactions Through Adverse Event Reports
    Liu, Ning
    Chen, Cheng-Bang
    Kumara, Soundar
    IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2020, 24 (01) : 57 - 68
  • [8] Detection of Drug-Drug Interactions Inducing Acute Kidney Injury by Electronic Health Records Mining
    Girardeau, Yannick
    Trivin, Claire
    Durieux, Pierre
    Le Beller, Christine
    Agnes, Lillo-Le Louet
    Neuraz, Antoine
    Degoulet, Patrice
    Avillach, Paul
    DRUG SAFETY, 2015, 38 (09) : 799 - 809
  • [9] Critical Drug-Drug Interactions for Use in Electronic Health Records Systems With Computerized Physician Order Entry: Review of Leading Approaches
    Classen, David C.
    Phansalkar, Shobha
    Bates, David W.
    JOURNAL OF PATIENT SAFETY, 2011, 7 (02) : 61 - 65
  • [10] Signal Detection for Potential Drug-Drug Interactions Using Inpatient Electronic Health Records with Laboratory Data
    Park, Rae Woong
    Park, Man Young
    Yoon, Dukyong
    Ahn, Eun Kyoung
    Schuemie, Martijn
    Hennessy, Sean
    PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2014, 23 : 419 - 420