Race, Gender, and Primary Language Were Not Associated With Changes in Opioid Prescribing in Children: Results From a Single Institution, 2010 to 2020.

Abstract

Patients should be prescribed medication based on their medical condition, without prejudice because of their race, gender, or primary language. However, previous research has shown that men are prescribed more medication than women, patients who are White are prescribed more medications than patients who are non-White, and English-speaking people are prescribed more medications than non-English-speaking patients. However, it is unclear whether these differences also occur in pediatric orthopaedic populations. We asked: (1) Was the amount of opiates prescribed at discharge associated with patient age, gender, race, or primary language? (2) Did the amount of opiates prescribed to patients at discharge change from 2010 to 2020? In a single center, between January 2010 and December 2019, we treated 331 patients younger than 18 years surgically for upper and lower long-bone extremity fractures. Patients were considered eligible if they had a nonpathologic fracture. Femur fractures were not included. Based on these criteria, all patients were eligible. The mean age was 12 ± 4 years. The mean weight was 57 ± 33 kg. Among these patients, 76% (253 of 331) were boys and 24% (78 of 331) were girls. From the hospital discharge records, we recorded the amount of opiates prescribed at the time of discharge as measured by morphine milligram equivalents (MMEs). We examined the association of age, gender, race, primary language, weight, and year of treatment using this measurement. We determined a patient's race retrospectively by information given by their parents at time of admission. We did not attempt to contact patients to obtain more nuanced information about their racial background. These data were obtained from the electronic health record. The Wilcoxon rank sum test, t-test, or chi-square test was used to assess associations depending on the distribution of variables, as appropriate. Because opioids as measured in MMEs is zero-inflated, a two-part model analysis was used to adjust for confounding variables. One component of the model was for the probability of having any opiate prescription and another was for the mean number of opioids received. Findings were considered statistically significant if p values were < 0.05. In total, 57% (189 of 331) of children were prescribed opiates at discharge after surgery for long-bone fractures. Opiate MMEs increased with patient age (r = 0.38; p < 0.01). Boys and girls showed no difference in the amounts of pain medication (adjusted odds ratio [OR] 1.38 [95% confidence interval (CI) 0.80 to 2.39]; p = 0.71; adjusted opioid difference: 0.35 MME [95% CI -51.7 to 52.4]; p = 0.99), nor were there differences between patients who were White and those who were non-White (adjusted OR 0.78 [95% CI 0.49 to 1.23]; p = 0.28; adjusted opioid difference: 21.5 MME [95% CI -19.3 to 62.4]; p = 0.30), or between patients for whom English was there primary language and those for whom English was not their primary language (adjusted OR 1.16 [95% CI 0.52 to 2.57]; p = 0.71; adjusted opioid difference: 22.7 MME [95% CI -55.7 to 101.3]; p = 0.57) when adjusted for age and weight. There was no change in opioid prescription amounts from 2010 to 2020 after adjusting for changes in patient age across years (Spearman r = -0.08; p = 0.16). Fairness in opioid prescribing based on race, gender, or primary language is possible. Additional research is needed to determine what factors in our institution led to this result. We suggest that prescribers should apply consistent protocols based on factors such as weight or injury type rather than making individual decisions for each patient. This will lead to fairer opioid prescribing to patients from different race and gender groups. Level III, therapeutic study.