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A Minimal Information Model for Potential Drug-Drug Interactions
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 con...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7982727/ https://www.ncbi.nlm.nih.gov/pubmed/33762928 http://dx.doi.org/10.3389/fphar.2020.608068 |
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author | Hochheiser, Harry Jing, Xia Garcia, Elizabeth A. Ayvaz, Serkan Sahay, Ratnesh Dumontier, Michel Banda, Juan M. Beyan, Oya Brochhausen, Mathias Draper, Evan Habiel, Sam Hassanzadeh, Oktie Herrero-Zazo, Maria Hocum, Brian Horn, John LeBaron, Brian Malone, Daniel C. Nytrø, Øystein Reese, Thomas Romagnoli, Katrina Schneider, Jodi Zhang, Louisa (Yu) Boyce, Richard D. |
author_facet | Hochheiser, Harry Jing, Xia Garcia, Elizabeth A. Ayvaz, Serkan Sahay, Ratnesh Dumontier, Michel Banda, Juan M. Beyan, Oya Brochhausen, Mathias Draper, Evan Habiel, Sam Hassanzadeh, Oktie Herrero-Zazo, Maria Hocum, Brian Horn, John LeBaron, Brian Malone, Daniel C. Nytrø, Øystein Reese, Thomas Romagnoli, Katrina Schneider, Jodi Zhang, Louisa (Yu) Boyce, Richard D. |
author_sort | Hochheiser, Harry |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7982727 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79827272021-03-23 A Minimal Information Model for Potential Drug-Drug Interactions Hochheiser, Harry Jing, Xia Garcia, Elizabeth A. Ayvaz, Serkan Sahay, Ratnesh Dumontier, Michel Banda, Juan M. Beyan, Oya Brochhausen, Mathias Draper, Evan Habiel, Sam Hassanzadeh, Oktie Herrero-Zazo, Maria Hocum, Brian Horn, John LeBaron, Brian Malone, Daniel C. Nytrø, Øystein Reese, Thomas Romagnoli, Katrina Schneider, Jodi Zhang, Louisa (Yu) Boyce, Richard D. Front Pharmacol Pharmacology 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. Frontiers Media S.A. 2021-03-08 /pmc/articles/PMC7982727/ /pubmed/33762928 http://dx.doi.org/10.3389/fphar.2020.608068 Text en 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. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pharmacology Hochheiser, Harry Jing, Xia Garcia, Elizabeth A. Ayvaz, Serkan Sahay, Ratnesh Dumontier, Michel Banda, Juan M. Beyan, Oya Brochhausen, Mathias Draper, Evan Habiel, Sam Hassanzadeh, Oktie Herrero-Zazo, Maria Hocum, Brian Horn, John LeBaron, Brian Malone, Daniel C. Nytrø, Øystein Reese, Thomas Romagnoli, Katrina Schneider, Jodi Zhang, Louisa (Yu) Boyce, Richard D. A Minimal Information Model for Potential Drug-Drug Interactions |
title | A Minimal Information Model for Potential Drug-Drug Interactions |
title_full | A Minimal Information Model for Potential Drug-Drug Interactions |
title_fullStr | A Minimal Information Model for Potential Drug-Drug Interactions |
title_full_unstemmed | A Minimal Information Model for Potential Drug-Drug Interactions |
title_short | A Minimal Information Model for Potential Drug-Drug Interactions |
title_sort | minimal information model for potential drug-drug interactions |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7982727/ https://www.ncbi.nlm.nih.gov/pubmed/33762928 http://dx.doi.org/10.3389/fphar.2020.608068 |
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