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Reduction in Hospital System Opioid Prescribing for Acute Pain Through Default Prescription Preference Settings: Pre–Post Study

BACKGROUND: The United States is in an opioid epidemic. Passive decision support in the electronic health record (EHR) through opioid prescription presets may aid in curbing opioid dependence. OBJECTIVE: The objective of this study is to determine whether modification of opioid prescribing presets i...

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Autores principales: Slovis, Benjamin Heritier, Riggio, Jeffrey M, Girondo, Melanie, Martino, Cara, Babula, Bracken, Roke, Lindsey M, Kairys, John C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082388/
https://www.ncbi.nlm.nih.gov/pubmed/33851922
http://dx.doi.org/10.2196/24360
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author Slovis, Benjamin Heritier
Riggio, Jeffrey M
Girondo, Melanie
Martino, Cara
Babula, Bracken
Roke, Lindsey M
Kairys, John C
author_facet Slovis, Benjamin Heritier
Riggio, Jeffrey M
Girondo, Melanie
Martino, Cara
Babula, Bracken
Roke, Lindsey M
Kairys, John C
author_sort Slovis, Benjamin Heritier
collection PubMed
description BACKGROUND: The United States is in an opioid epidemic. Passive decision support in the electronic health record (EHR) through opioid prescription presets may aid in curbing opioid dependence. OBJECTIVE: The objective of this study is to determine whether modification of opioid prescribing presets in the EHR could change prescribing patterns for an entire hospital system. METHODS: We performed a quasi-experimental retrospective pre–post analysis of a 24-month period before and after modifications to our EHR’s opioid prescription presets to match Centers for Disease Control and Prevention guidelines. We included all opioid prescriptions prescribed at our institution for nonchronic pain. Our modifications to the EHR include (1) making duration of treatment for an opioid prescription mandatory, (2) adding a quick button for 3 days’ duration while removing others, and (3) setting the default quantity of all oral opioid formulations to 10 tablets. We examined the quantity in tablets, duration in days, and proportion of prescriptions greater than 90 morphine milligram equivalents/day for our hospital system, and compared these values before and after our intervention for effect. RESULTS: There were 78,246 prescriptions included in our study written on 30,975 unique patients. There was a significant reduction for all opioid prescriptions pre versus post in (1) the overall median quantity of tablets dispensed (54 [IQR 40-120] vs 42 [IQR 18-90]; P<.001), (2) median duration of treatment (10.5 days [IQR 5.0-30] vs 7.5 days [IQR 3.0-30]; P<.001), and (3) proportion of prescriptions greater than 90 morphine milligram equivalents/day (27.46% [10,704/38,976; 95% CI 27.02%-27.91%] vs 22.86% [8979/39,270; 95% CI 22.45%-23.28%]; P<.001). CONCLUSIONS: Modifications of opioid prescribing presets in the EHR can improve prescribing practice patterns. Reducing duration and quantity of opioid prescriptions could reduce the risk of dependence and overdose.
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spelling pubmed-80823882021-05-06 Reduction in Hospital System Opioid Prescribing for Acute Pain Through Default Prescription Preference Settings: Pre–Post Study Slovis, Benjamin Heritier Riggio, Jeffrey M Girondo, Melanie Martino, Cara Babula, Bracken Roke, Lindsey M Kairys, John C J Med Internet Res Original Paper BACKGROUND: The United States is in an opioid epidemic. Passive decision support in the electronic health record (EHR) through opioid prescription presets may aid in curbing opioid dependence. OBJECTIVE: The objective of this study is to determine whether modification of opioid prescribing presets in the EHR could change prescribing patterns for an entire hospital system. METHODS: We performed a quasi-experimental retrospective pre–post analysis of a 24-month period before and after modifications to our EHR’s opioid prescription presets to match Centers for Disease Control and Prevention guidelines. We included all opioid prescriptions prescribed at our institution for nonchronic pain. Our modifications to the EHR include (1) making duration of treatment for an opioid prescription mandatory, (2) adding a quick button for 3 days’ duration while removing others, and (3) setting the default quantity of all oral opioid formulations to 10 tablets. We examined the quantity in tablets, duration in days, and proportion of prescriptions greater than 90 morphine milligram equivalents/day for our hospital system, and compared these values before and after our intervention for effect. RESULTS: There were 78,246 prescriptions included in our study written on 30,975 unique patients. There was a significant reduction for all opioid prescriptions pre versus post in (1) the overall median quantity of tablets dispensed (54 [IQR 40-120] vs 42 [IQR 18-90]; P<.001), (2) median duration of treatment (10.5 days [IQR 5.0-30] vs 7.5 days [IQR 3.0-30]; P<.001), and (3) proportion of prescriptions greater than 90 morphine milligram equivalents/day (27.46% [10,704/38,976; 95% CI 27.02%-27.91%] vs 22.86% [8979/39,270; 95% CI 22.45%-23.28%]; P<.001). CONCLUSIONS: Modifications of opioid prescribing presets in the EHR can improve prescribing practice patterns. Reducing duration and quantity of opioid prescriptions could reduce the risk of dependence and overdose. JMIR Publications 2021-04-14 /pmc/articles/PMC8082388/ /pubmed/33851922 http://dx.doi.org/10.2196/24360 Text en ©Benjamin Heritier Slovis, Jeffrey M Riggio, Melanie Girondo, Cara Martino, Bracken Babula, Lindsey M Roke, John C Kairys. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 14.04.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Slovis, Benjamin Heritier
Riggio, Jeffrey M
Girondo, Melanie
Martino, Cara
Babula, Bracken
Roke, Lindsey M
Kairys, John C
Reduction in Hospital System Opioid Prescribing for Acute Pain Through Default Prescription Preference Settings: Pre–Post Study
title Reduction in Hospital System Opioid Prescribing for Acute Pain Through Default Prescription Preference Settings: Pre–Post Study
title_full Reduction in Hospital System Opioid Prescribing for Acute Pain Through Default Prescription Preference Settings: Pre–Post Study
title_fullStr Reduction in Hospital System Opioid Prescribing for Acute Pain Through Default Prescription Preference Settings: Pre–Post Study
title_full_unstemmed Reduction in Hospital System Opioid Prescribing for Acute Pain Through Default Prescription Preference Settings: Pre–Post Study
title_short Reduction in Hospital System Opioid Prescribing for Acute Pain Through Default Prescription Preference Settings: Pre–Post Study
title_sort reduction in hospital system opioid prescribing for acute pain through default prescription preference settings: pre–post study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082388/
https://www.ncbi.nlm.nih.gov/pubmed/33851922
http://dx.doi.org/10.2196/24360
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