Table 4.

Bayesian Hierarchical Model

	odds.ratios	2.5%	97.5%
(Intercept)	3.05	1.14	7.58
payMEDICAID	0.85	0.81	0.89
payMedicare	0.85	0.80	0.90
paySELF	0.85	0.72	1.01
age_groupUnder 1	0.06	0.05	0.08
age_group1–18	0.91	0.82	1.01
age_group50 – 64	0.86	0.81	0.91
age_group65 – 79	0.85	0.80	0.91
age_group80+	0.68	0.62	0.75
sexmale	0.75	0.72	0.78
ASA2	0.88	0.80	0.97
ASA3	0.67	0.61	0.74
ASA4	0.25	0.22	0.28
ASA5	0.01	0.01	0.02
anes_typeNeuroaxial	0.09	0.08	0.10
anes_typeRegional	0.09	0.08	0.11
anes_typeMAC	0.09	0.08	0.10
practiceD	1.58	0.63	4.27
practiceE	4.19	1.61	11.28
practiceF	1.83	0.71	4.74

Table 4 lists the regression coefficients of our Bayesian hierarchical mixed effects model in the limited NACOR subset with complete data on insurance status, antiemetic administration and procedure code (n= 92683, two institutions). Compared to commercial insurance, Medicaid patients were less likely to receive antiemetic prophylaxis with ondansetron (OR 0.85, with Bayesian Credible 95% Intervals 0.8, 0.9) after controlling for age, gender, ASA risk classification, anesthesia type, and practice as fixed effects, allowing providers and procedures a random intercept, with very similar results for Medicare patients. As we would expect given the known riks for PONY, woman and younger (reference age group 19–49 years) patients were more likely to recieve prophylaxis (as indicated by older patients’ OR below 1); more prophylaxis was administered in cases using general anesthesia. Increasing ASA risk classification was associatated with lower odds of prophylaxis. Differences in odds ratios between institutions and procedure codes were large.