Aksharananda Rambachan1, Margaret C Fang1, Priya Prasad1, Nicholas Iverson2. 1. Division of Hospital MedicineUniversity of California, San Francisco, San Francisco, California. 2. Division of Hospital Medicine, Priscilla Chan and Mark Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, California.
Abstract
BACKGROUND: Differential opioid prescribing patterns have been reported in non-White patient populations. However, these disparities have not been well described among hospitalized medical inpatients. OBJECTIVE: To describe differences in opioid prescribing patterns among inpatients discharged from the general medicine service based on race/ethnicity. DESIGN, SETTING, AND PARTICIPANTS: For this retrospective study, we performed a multivariable logistic regression for patient race/ethnicity and whether patients received an opioid prescription at discharge and a negative binomial regression for days of opioids prescribed at discharge. The study included all 10,953 inpatients discharged from the general medicine service from June 2012 to November 2018 at University of California San Francisco Medical Center who received opioids during the last 24 hours of their hospitalization. MAIN OUTCOMES AND MEASURES: We examined two primary outcomes: whether a patient received an opioid prescription at discharge, and, for patients prescribed opioids, the number of days dispensed. RESULTS: Compared with White patients, Black patients were less likely to receive an opioid prescription at discharge (predicted population rate of 47.6% vs 50.7%; average marginal effect [AME], -3.1%; 95% CI, -5.5% to -0.8%). Asian patients were more likely to receive an opioid prescription on discharge (predicted population rate, 55.6% vs 50.7%; AME, +4.9; 95% CI, 1.5%-8.3%). We also found that Black patients received a shorter duration of opioid days compared with White patients (predicted days of opioids on discharge, 15.7 days vs 17.8 days; AME, -2.1 days; 95% CI, -3.3 to -0.9). CONCLUSION: Black patients were less likely to receive opioids and received shorter courses at discharge compared with White patients, adjusting for covariates. Asian patients were the most likely to receive an opioid prescription.
BACKGROUND: Differential opioid prescribing patterns have been reported in non-White patient populations. However, these disparities have not been well described among hospitalized medical inpatients. OBJECTIVE: To describe differences in opioid prescribing patterns among inpatients discharged from the general medicine service based on race/ethnicity. DESIGN, SETTING, AND PARTICIPANTS: For this retrospective study, we performed a multivariable logistic regression for patient race/ethnicity and whether patients received an opioid prescription at discharge and a negative binomial regression for days of opioids prescribed at discharge. The study included all 10,953 inpatients discharged from the general medicine service from June 2012 to November 2018 at University of California San Francisco Medical Center who received opioids during the last 24 hours of their hospitalization. MAIN OUTCOMES AND MEASURES: We examined two primary outcomes: whether a patient received an opioid prescription at discharge, and, for patients prescribed opioids, the number of days dispensed. RESULTS: Compared with White patients, Black patients were less likely to receive an opioid prescription at discharge (predicted population rate of 47.6% vs 50.7%; average marginal effect [AME], -3.1%; 95% CI, -5.5% to -0.8%). Asian patients were more likely to receive an opioid prescription on discharge (predicted population rate, 55.6% vs 50.7%; AME, +4.9; 95% CI, 1.5%-8.3%). We also found that Black patients received a shorter duration of opioid days compared with White patients (predicted days of opioids on discharge, 15.7 days vs 17.8 days; AME, -2.1 days; 95% CI, -3.3 to -0.9). CONCLUSION: Black patients were less likely to receive opioids and received shorter courses at discharge compared with White patients, adjusting for covariates. Asian patients were the most likely to receive an opioid prescription.
Authors: Chandra L Ford; Mark Daniel; Jo Anne L Earp; Jay S Kaufman; Carol E Golin; William C Miller Journal: Am J Public Health Date: 2009-02-12 Impact factor: 9.308