TY - JOUR
T1 - A Minimal Information Model for Potential Drug-Drug Interactions
AU - Hochheiser, Harry
AU - Jing, Xia
AU - Garcia, Elizabeth A.
AU - Ayvaz, Serkan
AU - Sahay, Ratnesh
AU - Dumontier, Michel
AU - Banda, Juan M.
AU - Beyan, Oya
AU - Brochhausen, Mathias
AU - Draper, Evan
AU - Habiel, Sam
AU - Hassanzadeh, Oktie
AU - Herrero-Zazo, Maria
AU - Hocum, Brian
AU - Horn, John
AU - LeBaron, Brian
AU - Malone, Daniel C.
AU - Nytro, Oystein
AU - Reese, Thomas
AU - Romagnoli, Katrina
AU - Schneider, Jodi
AU - Zhang, Louisa (Yu)
AU - Boyce, Richard D.
N1 - Funding Information:
This work was supported by National Library of Medicine Grant No. R01 LM011838 and R15LM012941. Additional support was provided by grants U18 HS027099, R01HS025984 and R21HS023826 from the Agency for Healthcare Research and Quality (AHRQ). Any opinions, findings, and conclusion or recommendations expressed on the site are those of the site maintainers and do not necessarily reflect the views of AHRQ.
Publisher Copyright:
© Copyright © 2021 Hochheiser, Jing, Garcia, Ayvaz, Sahay, Dumontier, Banda, Beyan, Brochhausen, Draper, Habiel, Hassanzadeh, Herrero-Zazo, Hocum, Horn, LeBaron, Malone, Nytrø, Reese, Romagnoli, Schneider, Zhang and Boyce.
PY - 2021/3/8
Y1 - 2021/3/8
N2 - Despite the significant health impacts of adverse events associated with drug-drug interactions, no standard models exist for managing and sharing evidence describing potential interactions between medications. Minimal information models have been used in other communities to establish community consensus around simple models capable of communicating useful information. This paper reports on a new minimal information model for describing potential drug-drug interactions. A task force of the Semantic Web in Health Care and Life Sciences Community Group of the World-Wide Web consortium engaged informaticians and drug-drug interaction experts in in-depth examination of recent literature and specific potential interactions. A consensus set of information items was identified, along with example descriptions of selected potential drug-drug interactions (PDDIs). User profiles and use cases were developed to demonstrate the applicability of the model. Ten core information items were identified: drugs involved, clinical consequences, seriousness, operational classification statement, recommended action, mechanism of interaction, contextual information/modifying factors, evidence about a suspected drug-drug interaction, frequency of exposure, and frequency of harm to exposed persons. Eight best practice recommendations suggest how PDDI knowledge artifact creators can best use the 10 information items when synthesizing drug interaction evidence into artifacts intended to aid clinicians. This model has been included in a proposed implementation guide developed by the HL7 Clinical Decision Support Workgroup and in PDDIs published in the CDS Connect repository. The complete description of the model can be found at https://w3id.org/hclscg/pddi.
AB - Despite the significant health impacts of adverse events associated with drug-drug interactions, no standard models exist for managing and sharing evidence describing potential interactions between medications. Minimal information models have been used in other communities to establish community consensus around simple models capable of communicating useful information. This paper reports on a new minimal information model for describing potential drug-drug interactions. A task force of the Semantic Web in Health Care and Life Sciences Community Group of the World-Wide Web consortium engaged informaticians and drug-drug interaction experts in in-depth examination of recent literature and specific potential interactions. A consensus set of information items was identified, along with example descriptions of selected potential drug-drug interactions (PDDIs). User profiles and use cases were developed to demonstrate the applicability of the model. Ten core information items were identified: drugs involved, clinical consequences, seriousness, operational classification statement, recommended action, mechanism of interaction, contextual information/modifying factors, evidence about a suspected drug-drug interaction, frequency of exposure, and frequency of harm to exposed persons. Eight best practice recommendations suggest how PDDI knowledge artifact creators can best use the 10 information items when synthesizing drug interaction evidence into artifacts intended to aid clinicians. This model has been included in a proposed implementation guide developed by the HL7 Clinical Decision Support Workgroup and in PDDIs published in the CDS Connect repository. The complete description of the model can be found at https://w3id.org/hclscg/pddi.
KW - drug-drug interaction
KW - adverse drug events
KW - minimal information model
KW - clinical informatics
KW - knowledge representation
U2 - 10.3389/fphar.2020.608068
DO - 10.3389/fphar.2020.608068
M3 - Article
C2 - 33762928
SN - 1663-9812
VL - 11
JO - Frontiers in Pharmacology
JF - Frontiers in Pharmacology
M1 - 608068
ER -