Provider Bias in prescribing opioid analgesics: a study of electronic medical Records at a Hospital Emergency Department.
Crowding
Electronic medical records
Emergency departments
Inequality
Opioids
Prescription bias
Undertreatment
Journal
BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562
Informations de publication
Date de publication:
06 08 2021
06 08 2021
Historique:
received:
03
04
2020
accepted:
26
07
2021
entrez:
7
8
2021
pubmed:
8
8
2021
medline:
12
8
2021
Statut:
epublish
Résumé
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. 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. 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. 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.
Sections du résumé
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.
Identifiants
pubmed: 34362330
doi: 10.1186/s12889-021-11551-9
pii: 10.1186/s12889-021-11551-9
pmc: PMC8344207
doi:
Substances chimiques
Analgesics, Opioid
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1518Subventions
Organisme : NICHD NIH HHS
ID : P2C HD065563
Pays : United States
Informations de copyright
© 2021. The Author(s).
Références
J Gen Intern Med. 2001 Apr;16(4):211-7
pubmed: 11318921
Nurs Clin North Am. 2000 Jun;35(2):375-83
pubmed: 10873249
J Clin Anesth. 2002 Aug;14(5):349-53
pubmed: 12208439
Soc Sci Med. 2004 Sep;59(5):1035-45
pubmed: 15186903
J Pain Symptom Manage. 2003 Jun;25(6):539-46
pubmed: 12782434
JAMA Pediatr. 2015 Nov;169(11):996-1002
pubmed: 26366984
J Health Soc Behav. 2014 Sep;55(3):342-59
pubmed: 25138201
Arch Intern Med. 2001 Dec 10-24;161(22):2721-4
pubmed: 11732938
Am J Public Health. 2012 May;102(5):988-95
pubmed: 22420817
Cureus. 2018 Dec 14;10(12):e3733
pubmed: 30800543
Ann Emerg Med. 2008 Jan;51(1):1-5
pubmed: 17913299
J Am Geriatr Soc. 2006 Feb;54(2):270-5
pubmed: 16460378
Pain Med. 2010 Dec;11(12):1859-71
pubmed: 21040438
Emerg Nurse. 2008 Feb;15(9):30-4
pubmed: 18330396
Am J Public Health. 2003 Dec;93(12):2067-73
pubmed: 14652336
J Pain. 2015 Jun;16(6):558-68
pubmed: 25828370
N Engl J Med. 2014 May 29;370(22):2063-6
pubmed: 24758595
Emerg Med J. 2012 Jun;29(6):437-43
pubmed: 22223713
Proc Natl Acad Sci U S A. 2016 Apr 19;113(16):4296-301
pubmed: 27044069
Soc Sci Med. 2016 Jun;159:108-15
pubmed: 27179146
Pain Med. 2006 Mar-Apr;7(2):119-34
pubmed: 16634725
J Pain. 2003 Nov;4(9):505-10
pubmed: 14636818
Pain Med. 2003 Sep;4(3):277-94
pubmed: 12974827
Soc Sci Med. 2017 May;181:66-73
pubmed: 28376357
J Health Soc Behav. 2010 Mar;51(1):1-15
pubmed: 20420291
JAMA Netw Open. 2019 Aug 2;2(8):e1910373
pubmed: 31469396
J Health Soc Behav. 2012 Sep;53(3):329-43
pubmed: 22811465