TY - JOUR
T1 - Antiemetic prophylaxis as a marker of health care disparities in the national anesthesia clinical outcomes registry
AU - Andreae, Michael H.
AU - Gabry, Jonah S.
AU - Goodrich, Ben
AU - White, Robert S.
AU - Hall, Charles
N1 - Funding Information:
Funding: This research is supported in part by the National Center for Advancing Translational Sciences, a component of the National Institutes of Health, through CTSA grants 5KL2TR001071-03 and UL1TR001073. Copyright © 2017 International Anesthesia Research Society
Publisher Copyright:
© 2017 International Anesthesia Research Society.
PY - 2018
Y1 - 2018
N2 - BACKGROUND: US health care disparities persist despite repeated countermeasures. Research identified race, ethnicity, gender, and socioeconomic status as factors, mediated through individual provider and/or systemic biases; little research exists in anesthesiology. We investigated antiemetic prophylaxis as a surrogate marker for anesthesia quality by individual providers because antiemetics are universally available, indicated contingent on patient characteristics (gender, age, etc), but independent of comorbidities and not yet impacted by regulatory or financial constraints. We hypothesized that socioeconomic indicators (measured as insurance status or median income in the patients' home zip code area) are associated with the utilization of antiemetic prophylaxis (as a marker of anesthesia quality). METHODS: We tested our hypothesis in several subsets of electronic anesthesia records from the National Anesthesia Clinical Outcomes Registry (NACOR), fitting frequentist and novel Bayesian multilevel logistic regression models. RESULTS: NACOR contained 12 million cases in 2013. Six institutions reported on antiemetic prophylaxis for 441,645 anesthesia cases. Only 173,133 cases included details on insurance information. Even fewer (n = 92,683) contained complete data on procedure codes and provider identifiers. Bivariate analysis, multivariable logistic regression, and our Bayesian hierarchical model all showed a large and statistically significant association between socioeconomic markers and antiemetic prophylaxis (ondansetron and dexamethasone). For Medicaid versus commercially insured patients, the odds ratio of receiving the antiemetic ondansetron is 0.85 in our Bayesian hierarchical mixed regression model, with a 95% Bayesian credible interval of 0.81-0.89 with similar inferences in classical (frequentist) regression models. CONCLUSIONS: Our analyses of NACOR anesthesia records raise concerns that patients with lower socioeconomic status may receive inferior anesthesia care provided by individual anesthesiologists, as indicated by less antiemetics administered. Effects persisted after we controlled for important patient characteristics and for procedure and provider influences. Findings were robust to sensitivity analyses. Our results challenge the notion that anesthesia providers do not contribute to health care disparities.
AB - BACKGROUND: US health care disparities persist despite repeated countermeasures. Research identified race, ethnicity, gender, and socioeconomic status as factors, mediated through individual provider and/or systemic biases; little research exists in anesthesiology. We investigated antiemetic prophylaxis as a surrogate marker for anesthesia quality by individual providers because antiemetics are universally available, indicated contingent on patient characteristics (gender, age, etc), but independent of comorbidities and not yet impacted by regulatory or financial constraints. We hypothesized that socioeconomic indicators (measured as insurance status or median income in the patients' home zip code area) are associated with the utilization of antiemetic prophylaxis (as a marker of anesthesia quality). METHODS: We tested our hypothesis in several subsets of electronic anesthesia records from the National Anesthesia Clinical Outcomes Registry (NACOR), fitting frequentist and novel Bayesian multilevel logistic regression models. RESULTS: NACOR contained 12 million cases in 2013. Six institutions reported on antiemetic prophylaxis for 441,645 anesthesia cases. Only 173,133 cases included details on insurance information. Even fewer (n = 92,683) contained complete data on procedure codes and provider identifiers. Bivariate analysis, multivariable logistic regression, and our Bayesian hierarchical model all showed a large and statistically significant association between socioeconomic markers and antiemetic prophylaxis (ondansetron and dexamethasone). For Medicaid versus commercially insured patients, the odds ratio of receiving the antiemetic ondansetron is 0.85 in our Bayesian hierarchical mixed regression model, with a 95% Bayesian credible interval of 0.81-0.89 with similar inferences in classical (frequentist) regression models. CONCLUSIONS: Our analyses of NACOR anesthesia records raise concerns that patients with lower socioeconomic status may receive inferior anesthesia care provided by individual anesthesiologists, as indicated by less antiemetics administered. Effects persisted after we controlled for important patient characteristics and for procedure and provider influences. Findings were robust to sensitivity analyses. Our results challenge the notion that anesthesia providers do not contribute to health care disparities.
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U2 - 10.1213/ANE.0000000000002582
DO - 10.1213/ANE.0000000000002582
M3 - Article
C2 - 29116968
AN - SCOPUS:85051713411
SN - 0003-2999
VL - 126
SP - 588
EP - 599
JO - Anesthesia and Analgesia
JF - Anesthesia and Analgesia
IS - 2
ER -