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Structured override reasons for drug-drug interaction alerts in electronic health records

OBJECTIVE: The study sought to determine availability and use of structured override reasons for drug-drug interaction (DDI) alerts in electronic health records. MATERIALS AND METHODS: We collected data on DDI alerts and override reasons from 10 clinical sites across the United States using a variet...

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Autores principales: Wright, Adam, McEvoy, Dustin S, Aaron, Skye, McCoy, Allison B, Amato, Mary G, Kim, Hyun, Ai, Angela, Cimino, James J, Desai, Bimal R, El-Kareh, Robert, Galanter, William, Longhurst, Christopher A, Malhotra, Sameer, Radecki, Ryan P, Samal, Lipika, Schreiber, Richard, Shelov, Eric, Sirajuddin, Anwar Mohammad, Sittig, Dean F
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6748816/
https://www.ncbi.nlm.nih.gov/pubmed/31329891
http://dx.doi.org/10.1093/jamia/ocz033
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author Wright, Adam
McEvoy, Dustin S
Aaron, Skye
McCoy, Allison B
Amato, Mary G
Kim, Hyun
Ai, Angela
Cimino, James J
Desai, Bimal R
El-Kareh, Robert
Galanter, William
Longhurst, Christopher A
Malhotra, Sameer
Radecki, Ryan P
Samal, Lipika
Schreiber, Richard
Shelov, Eric
Sirajuddin, Anwar Mohammad
Sittig, Dean F
author_facet Wright, Adam
McEvoy, Dustin S
Aaron, Skye
McCoy, Allison B
Amato, Mary G
Kim, Hyun
Ai, Angela
Cimino, James J
Desai, Bimal R
El-Kareh, Robert
Galanter, William
Longhurst, Christopher A
Malhotra, Sameer
Radecki, Ryan P
Samal, Lipika
Schreiber, Richard
Shelov, Eric
Sirajuddin, Anwar Mohammad
Sittig, Dean F
author_sort Wright, Adam
collection PubMed
description OBJECTIVE: The study sought to determine availability and use of structured override reasons for drug-drug interaction (DDI) alerts in electronic health records. MATERIALS AND METHODS: We collected data on DDI alerts and override reasons from 10 clinical sites across the United States using a variety of electronic health records. We used a multistage iterative card sort method to categorize the override reasons from all sites and identified best practices. RESULTS: Our methodology established 177 unique override reasons across the 10 sites. The number of coded override reasons at each site ranged from 3 to 100. Many sites offered override reasons not relevant to DDIs. Twelve categories of override reasons were identified. Three categories accounted for 78% of all overrides: “will monitor or take precautions,” “not clinically significant,” and “benefit outweighs risk.” DISCUSSION: We found wide variability in override reasons between sites and many opportunities to improve alerts. Some override reasons were irrelevant to DDIs. Many override reasons attested to a future action (eg, decreasing a dose or ordering monitoring tests), which requires an additional step after the alert is overridden, unless the alert is made actionable. Some override reasons deferred to another party, although override reasons often are not visible to other users. Many override reasons stated that the alert was inaccurate, suggesting that specificity of alerts could be improved. CONCLUSIONS: Organizations should improve the options available to providers who choose to override DDI alerts. DDI alerting systems should be actionable and alerts should be tailored to the patient and drug pairs.
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spelling pubmed-67488162019-09-23 Structured override reasons for drug-drug interaction alerts in electronic health records Wright, Adam McEvoy, Dustin S Aaron, Skye McCoy, Allison B Amato, Mary G Kim, Hyun Ai, Angela Cimino, James J Desai, Bimal R El-Kareh, Robert Galanter, William Longhurst, Christopher A Malhotra, Sameer Radecki, Ryan P Samal, Lipika Schreiber, Richard Shelov, Eric Sirajuddin, Anwar Mohammad Sittig, Dean F J Am Med Inform Assoc Research and Applications OBJECTIVE: The study sought to determine availability and use of structured override reasons for drug-drug interaction (DDI) alerts in electronic health records. MATERIALS AND METHODS: We collected data on DDI alerts and override reasons from 10 clinical sites across the United States using a variety of electronic health records. We used a multistage iterative card sort method to categorize the override reasons from all sites and identified best practices. RESULTS: Our methodology established 177 unique override reasons across the 10 sites. The number of coded override reasons at each site ranged from 3 to 100. Many sites offered override reasons not relevant to DDIs. Twelve categories of override reasons were identified. Three categories accounted for 78% of all overrides: “will monitor or take precautions,” “not clinically significant,” and “benefit outweighs risk.” DISCUSSION: We found wide variability in override reasons between sites and many opportunities to improve alerts. Some override reasons were irrelevant to DDIs. Many override reasons attested to a future action (eg, decreasing a dose or ordering monitoring tests), which requires an additional step after the alert is overridden, unless the alert is made actionable. Some override reasons deferred to another party, although override reasons often are not visible to other users. Many override reasons stated that the alert was inaccurate, suggesting that specificity of alerts could be improved. CONCLUSIONS: Organizations should improve the options available to providers who choose to override DDI alerts. DDI alerting systems should be actionable and alerts should be tailored to the patient and drug pairs. Oxford University Press 2019-04-26 /pmc/articles/PMC6748816/ /pubmed/31329891 http://dx.doi.org/10.1093/jamia/ocz033 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Research and Applications
Wright, Adam
McEvoy, Dustin S
Aaron, Skye
McCoy, Allison B
Amato, Mary G
Kim, Hyun
Ai, Angela
Cimino, James J
Desai, Bimal R
El-Kareh, Robert
Galanter, William
Longhurst, Christopher A
Malhotra, Sameer
Radecki, Ryan P
Samal, Lipika
Schreiber, Richard
Shelov, Eric
Sirajuddin, Anwar Mohammad
Sittig, Dean F
Structured override reasons for drug-drug interaction alerts in electronic health records
title Structured override reasons for drug-drug interaction alerts in electronic health records
title_full Structured override reasons for drug-drug interaction alerts in electronic health records
title_fullStr Structured override reasons for drug-drug interaction alerts in electronic health records
title_full_unstemmed Structured override reasons for drug-drug interaction alerts in electronic health records
title_short Structured override reasons for drug-drug interaction alerts in electronic health records
title_sort structured override reasons for drug-drug interaction alerts in electronic health records
topic Research and Applications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6748816/
https://www.ncbi.nlm.nih.gov/pubmed/31329891
http://dx.doi.org/10.1093/jamia/ocz033
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