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Using electronic health record’s data to assess daily dose of opioids prescribed for outpatients with chronic non-cancer pain

This research intended to examine electronic health record (EHR) based methods for automated estimation of morphine equivalent daily dose (MEDD) of prescribed opioids in primary care research and practice. The study leveraged the health system’s audit of adults treated with long-term opioids for chr...

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Autores principales: Tuan, Wen-Jan, Sehgal, Nalini, Zgierska, Aleksandra E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8614133/
https://www.ncbi.nlm.nih.gov/pubmed/34819321
http://dx.doi.org/10.1136/fmch-2021-001277
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author Tuan, Wen-Jan
Sehgal, Nalini
Zgierska, Aleksandra E
author_facet Tuan, Wen-Jan
Sehgal, Nalini
Zgierska, Aleksandra E
author_sort Tuan, Wen-Jan
collection PubMed
description This research intended to examine electronic health record (EHR) based methods for automated estimation of morphine equivalent daily dose (MEDD) of prescribed opioids in primary care research and practice. The study leveraged the health system’s audit of adults treated with long-term opioids for chronic non-cancer pain to compare two EHR-based automated MEDD calculation methods: RxSignature (active prescriptions’ signature information) and RxQuantity (quantity dispensed for prescriptions issued within the past 90 days). Prescribed opioid EHR data were extracted from the target population at a large US academic health system in a 2-year assessment period. Forty-five ‘target patients’ were selected by the health system for a manual audit by an expert physician who then ‘manually’ calculated the actual MEDD over the past 90 days (RxAudit) for those with discrepancies in the MEDD calculated with RxSignature and RxQuantity. Paired samples t-test compared the MEDD generated by the RxSignature and RxQuantity methods by opioid type in the target population. The audit (n=45) revealed the RxSignature and RxQuantity methods yielded comparable MEDD results for 20 patients and discrepant results for 25 patients. The former group had opioid prescriptions issued at regular intervals for stable, scheduled doses of opioids; the latter group had opioid prescriptions issued irregularly or for changed daily dosing regimen, for as-needed use, or had changes in the dosing regimen or inactive prescriptions mislabeled as active. RxAudit of the EHR of those with discrepant MEDD results (n=25) produced consistent results with those yielded by the RxQuantity, but not the RxSignature, method. Significant differences in MEDD were found for most opioid types when the MEDD was calculated for the target population using the RxSignature and RxQuantity methods. In conclusion, different EHR-based methods for MEDD calculation can lead to vastly different estimates, with implications for research and clinical care outcomes. Standardising data extraction and MEDD calculation algorithms could overcome these challenges, enabling a more accurate and reproducible approach to the dose calculation for prescribed opioids, improving the quality of research and patient safety.
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spelling pubmed-86141332021-12-10 Using electronic health record’s data to assess daily dose of opioids prescribed for outpatients with chronic non-cancer pain Tuan, Wen-Jan Sehgal, Nalini Zgierska, Aleksandra E Fam Med Community Health Methodology and Research Methods This research intended to examine electronic health record (EHR) based methods for automated estimation of morphine equivalent daily dose (MEDD) of prescribed opioids in primary care research and practice. The study leveraged the health system’s audit of adults treated with long-term opioids for chronic non-cancer pain to compare two EHR-based automated MEDD calculation methods: RxSignature (active prescriptions’ signature information) and RxQuantity (quantity dispensed for prescriptions issued within the past 90 days). Prescribed opioid EHR data were extracted from the target population at a large US academic health system in a 2-year assessment period. Forty-five ‘target patients’ were selected by the health system for a manual audit by an expert physician who then ‘manually’ calculated the actual MEDD over the past 90 days (RxAudit) for those with discrepancies in the MEDD calculated with RxSignature and RxQuantity. Paired samples t-test compared the MEDD generated by the RxSignature and RxQuantity methods by opioid type in the target population. The audit (n=45) revealed the RxSignature and RxQuantity methods yielded comparable MEDD results for 20 patients and discrepant results for 25 patients. The former group had opioid prescriptions issued at regular intervals for stable, scheduled doses of opioids; the latter group had opioid prescriptions issued irregularly or for changed daily dosing regimen, for as-needed use, or had changes in the dosing regimen or inactive prescriptions mislabeled as active. RxAudit of the EHR of those with discrepant MEDD results (n=25) produced consistent results with those yielded by the RxQuantity, but not the RxSignature, method. Significant differences in MEDD were found for most opioid types when the MEDD was calculated for the target population using the RxSignature and RxQuantity methods. In conclusion, different EHR-based methods for MEDD calculation can lead to vastly different estimates, with implications for research and clinical care outcomes. Standardising data extraction and MEDD calculation algorithms could overcome these challenges, enabling a more accurate and reproducible approach to the dose calculation for prescribed opioids, improving the quality of research and patient safety. BMJ Publishing Group 2021-11-24 /pmc/articles/PMC8614133/ /pubmed/34819321 http://dx.doi.org/10.1136/fmch-2021-001277 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Methodology and Research Methods
Tuan, Wen-Jan
Sehgal, Nalini
Zgierska, Aleksandra E
Using electronic health record’s data to assess daily dose of opioids prescribed for outpatients with chronic non-cancer pain
title Using electronic health record’s data to assess daily dose of opioids prescribed for outpatients with chronic non-cancer pain
title_full Using electronic health record’s data to assess daily dose of opioids prescribed for outpatients with chronic non-cancer pain
title_fullStr Using electronic health record’s data to assess daily dose of opioids prescribed for outpatients with chronic non-cancer pain
title_full_unstemmed Using electronic health record’s data to assess daily dose of opioids prescribed for outpatients with chronic non-cancer pain
title_short Using electronic health record’s data to assess daily dose of opioids prescribed for outpatients with chronic non-cancer pain
title_sort using electronic health record’s data to assess daily dose of opioids prescribed for outpatients with chronic non-cancer pain
topic Methodology and Research Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8614133/
https://www.ncbi.nlm.nih.gov/pubmed/34819321
http://dx.doi.org/10.1136/fmch-2021-001277
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