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Impact of clinical decision support on controlled substance prescribing
BACKGROUND: Prescription drug overdose and misuse has reached alarming numbers. A persistent problem in clinical care is lack of easy, immediate access to all relevant information at the actionable time. Prescribers must digest an overwhelming amount of information from each patient’s record as well...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10588193/ https://www.ncbi.nlm.nih.gov/pubmed/37864226 http://dx.doi.org/10.1186/s12911-023-02314-0 |
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author | Seymour, Rachel B. Wally, Meghan K. Hsu, Joseph R. |
author_facet | Seymour, Rachel B. Wally, Meghan K. Hsu, Joseph R. |
author_sort | Seymour, Rachel B. |
collection | PubMed |
description | BACKGROUND: Prescription drug overdose and misuse has reached alarming numbers. A persistent problem in clinical care is lack of easy, immediate access to all relevant information at the actionable time. Prescribers must digest an overwhelming amount of information from each patient’s record as well as remain up-to-date with current evidence to provide optimal care. This study aimed to describe prescriber response to a prospective clinical decision support intervention designed to identify patients at risk of adverse events associated with misuse of prescription opioids/benzodiazepines and promote adherence to clinical practice guidelines. METHODS: This study was conducted at a large multi-center healthcare system, using data from the electronic health record. A prospective observational study was performed as clinical decision support (CDS) interventions were sequentially launched (January 2016–July 2019). All data were captured from the medical record prospectively via the CDS tools implemented. A consecutive series of all patient encounters including an opioid/benzodiazepine prescription were included in this study (n = 61,124,172 encounters; n = 674,785 patients). Physician response to the CDS interventions was the primary outcome, and it was assessed over time using control charts. RESULTS: An alert was triggered in 23.5% of encounters with a prescription (n = 555,626). The prescriber decision was influenced in 18.1% of these encounters (n = 100,301). As the number of risk factors increased, the rate of decision being influenced also increased (p = 0.0001). The effect of the alert differed by drug, risk factor, specialty, and facility. CONCLUSION: The delivery of evidence-based, patient-specific information had an influence on the final prescription in nearly 1 in 5 encounters. Our intervention was sustained with minimal prescriber fatigue over many years in a large and diverse health system. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-023-02314-0. |
format | Online Article Text |
id | pubmed-10588193 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-105881932023-10-21 Impact of clinical decision support on controlled substance prescribing Seymour, Rachel B. Wally, Meghan K. Hsu, Joseph R. BMC Med Inform Decis Mak Research BACKGROUND: Prescription drug overdose and misuse has reached alarming numbers. A persistent problem in clinical care is lack of easy, immediate access to all relevant information at the actionable time. Prescribers must digest an overwhelming amount of information from each patient’s record as well as remain up-to-date with current evidence to provide optimal care. This study aimed to describe prescriber response to a prospective clinical decision support intervention designed to identify patients at risk of adverse events associated with misuse of prescription opioids/benzodiazepines and promote adherence to clinical practice guidelines. METHODS: This study was conducted at a large multi-center healthcare system, using data from the electronic health record. A prospective observational study was performed as clinical decision support (CDS) interventions were sequentially launched (January 2016–July 2019). All data were captured from the medical record prospectively via the CDS tools implemented. A consecutive series of all patient encounters including an opioid/benzodiazepine prescription were included in this study (n = 61,124,172 encounters; n = 674,785 patients). Physician response to the CDS interventions was the primary outcome, and it was assessed over time using control charts. RESULTS: An alert was triggered in 23.5% of encounters with a prescription (n = 555,626). The prescriber decision was influenced in 18.1% of these encounters (n = 100,301). As the number of risk factors increased, the rate of decision being influenced also increased (p = 0.0001). The effect of the alert differed by drug, risk factor, specialty, and facility. CONCLUSION: The delivery of evidence-based, patient-specific information had an influence on the final prescription in nearly 1 in 5 encounters. Our intervention was sustained with minimal prescriber fatigue over many years in a large and diverse health system. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-023-02314-0. BioMed Central 2023-10-20 /pmc/articles/PMC10588193/ /pubmed/37864226 http://dx.doi.org/10.1186/s12911-023-02314-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Seymour, Rachel B. Wally, Meghan K. Hsu, Joseph R. Impact of clinical decision support on controlled substance prescribing |
title | Impact of clinical decision support on controlled substance prescribing |
title_full | Impact of clinical decision support on controlled substance prescribing |
title_fullStr | Impact of clinical decision support on controlled substance prescribing |
title_full_unstemmed | Impact of clinical decision support on controlled substance prescribing |
title_short | Impact of clinical decision support on controlled substance prescribing |
title_sort | impact of clinical decision support on controlled substance prescribing |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10588193/ https://www.ncbi.nlm.nih.gov/pubmed/37864226 http://dx.doi.org/10.1186/s12911-023-02314-0 |
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