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Provider Bias in prescribing opioid analgesics: a study of electronic medical Records at a Hospital Emergency Department
BACKGROUND: Physicians do not prescribe opioid analgesics for pain treatment equally across groups, and such disparities may pose significant public health concerns. Although research suggests that institutional constraints and cultural stereotypes influence doctors’ treatment of pain, prior quantit...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8344207/ https://www.ncbi.nlm.nih.gov/pubmed/34362330 http://dx.doi.org/10.1186/s12889-021-11551-9 |
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author | Keister, Lisa A. Stecher, Chad Aronson, Brian McConnell, William Hustedt, Joshua Moody, James W. |
author_facet | Keister, Lisa A. Stecher, Chad Aronson, Brian McConnell, William Hustedt, Joshua Moody, James W. |
author_sort | Keister, Lisa A. |
collection | PubMed |
description | BACKGROUND: Physicians do not prescribe opioid analgesics for pain treatment equally across groups, and such disparities may pose significant public health concerns. Although research suggests that institutional constraints and cultural stereotypes influence doctors’ treatment of pain, prior quantitative evidence is mixed. The objective of this secondary analysis is therefore to clarify which institutional constraints and patient demographics bias provider prescribing of opioid analgesics. METHODS: We used electronic medical record data from an emergency department of a large U.S hospital during years 2008–2014. We ran multi-level logistic regression models to estimate factors associated with providing an opioid prescription during a given visit while controlling for ICD-9 diagnosis codes and between-patient heterogeneity. RESULTS: A total of 180,829 patient visits for 63,513 unique patients were recorded during the period of analysis. Overall, providers were significantly less likely to prescribe opioids to the same individual patient when the visit occurred during higher rates of emergency department crowding, later times of day, earlier in the week, later years in our sample, and when the patient had received fewer previous opioid prescriptions. Across all patients, providers were significantly more likely to prescribe opioids to patients who were middle-aged, white, and married. We found no bias towards women and no interaction effects between race and crowding or between race and sex. CONCLUSIONS: Providers tend to prescribe fewer opioids during constrained diagnostic situations and undertreat pain for patients from high-risk and marginalized demographic groups. Potential harms resulting from previous treatment decisions may accumulate by informing future treatment decisions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-11551-9. |
format | Online Article Text |
id | pubmed-8344207 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83442072021-08-09 Provider Bias in prescribing opioid analgesics: a study of electronic medical Records at a Hospital Emergency Department Keister, Lisa A. Stecher, Chad Aronson, Brian McConnell, William Hustedt, Joshua Moody, James W. BMC Public Health Research Article BACKGROUND: Physicians do not prescribe opioid analgesics for pain treatment equally across groups, and such disparities may pose significant public health concerns. Although research suggests that institutional constraints and cultural stereotypes influence doctors’ treatment of pain, prior quantitative evidence is mixed. The objective of this secondary analysis is therefore to clarify which institutional constraints and patient demographics bias provider prescribing of opioid analgesics. METHODS: We used electronic medical record data from an emergency department of a large U.S hospital during years 2008–2014. We ran multi-level logistic regression models to estimate factors associated with providing an opioid prescription during a given visit while controlling for ICD-9 diagnosis codes and between-patient heterogeneity. RESULTS: A total of 180,829 patient visits for 63,513 unique patients were recorded during the period of analysis. Overall, providers were significantly less likely to prescribe opioids to the same individual patient when the visit occurred during higher rates of emergency department crowding, later times of day, earlier in the week, later years in our sample, and when the patient had received fewer previous opioid prescriptions. Across all patients, providers were significantly more likely to prescribe opioids to patients who were middle-aged, white, and married. We found no bias towards women and no interaction effects between race and crowding or between race and sex. CONCLUSIONS: Providers tend to prescribe fewer opioids during constrained diagnostic situations and undertreat pain for patients from high-risk and marginalized demographic groups. Potential harms resulting from previous treatment decisions may accumulate by informing future treatment decisions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-11551-9. BioMed Central 2021-08-06 /pmc/articles/PMC8344207/ /pubmed/34362330 http://dx.doi.org/10.1186/s12889-021-11551-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Article Keister, Lisa A. Stecher, Chad Aronson, Brian McConnell, William Hustedt, Joshua Moody, James W. Provider Bias in prescribing opioid analgesics: a study of electronic medical Records at a Hospital Emergency Department |
title | Provider Bias in prescribing opioid analgesics: a study of electronic medical Records at a Hospital Emergency Department |
title_full | Provider Bias in prescribing opioid analgesics: a study of electronic medical Records at a Hospital Emergency Department |
title_fullStr | Provider Bias in prescribing opioid analgesics: a study of electronic medical Records at a Hospital Emergency Department |
title_full_unstemmed | Provider Bias in prescribing opioid analgesics: a study of electronic medical Records at a Hospital Emergency Department |
title_short | Provider Bias in prescribing opioid analgesics: a study of electronic medical Records at a Hospital Emergency Department |
title_sort | provider bias in prescribing opioid analgesics: a study of electronic medical records at a hospital emergency department |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8344207/ https://www.ncbi.nlm.nih.gov/pubmed/34362330 http://dx.doi.org/10.1186/s12889-021-11551-9 |
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