identified from the MEPS data based on the Andersen's Behavioral Model of Health Services Use. Generalized linear models were performed to determine the presence of mediation using the Barron and Kenny approach. Results: A total of 119 eligible individuals, representing 1,360,803 individuals were included in this study. The sample included 76% females, 75% Caucasians, 38% over the age of 65 years, and 84% reporting at least one comorbidity, with a mean family income of $61,323. The mediation analysis showed that after controlling for covariates, race was significantly associated with direct medical costs (Estimate = 0.96; SE = 0.26; p < 0.05), and but not medication adherence (Estimate = 0.033; SE: 12; p > 0.05). Medication adherence was significantly related to medical costs (Estimate = 0.40; SE: 0.14; p < 0.05). ConClusions: Adherence to DMARDs was not found to be a mediator of the relationship between race/ethnicity and healthcare cost. Further analysis needs to be conducted to explore the mediators of racial disparities in overall medical costs among patients with RA.
S95 database compared with the patient diagnosis based on patient medical charts. Claims and administrative data were extracted for fiscal years 2013 (2013/4/1 to 2014/3/31) from Jichi-Medical school hospital in Japan. One hundred potential cases for each of the three cardiovascular events were randomly selected using the ICD-10 code. An independent clinical event committee (iCEC) reviewed the identified potential cases with medical charts to determine whether the cases met pre-specified criteria for the events. We selected the potential event data set based on algorithms combining conditions in the ICD-10 code, medical treatment and medication data, and calculated the positive predictive values (PPVs) of each outcome. Of the 100 patients for each cardiovascular event, all medical records were adjudicated by three physicians (two cardiologists and one neurologist) independently. RESULTS: Preliminary results showed the algorithm PPVs based only on the ICD-10 code were 81.6% (95%CI: 72.5-88.7%) for AMI, 31.0% (95%CI: 22.8-40.3%) for IS and 34.4% (95%CI: 26.1-43.6%) for HS. The PPV value for AMI was higher than previous studies in the US. Additional research is needed for IS and HS to identify the combination of conditions which demonstrate higher PPVs. CONCLUSIONS: This is the first study in Japan to evaluate PPV for cardiovascular events identified using the ICD-10 code based algorithms. The results indicate that using the ICD-10 code, it is possible to identify AMI cases from Japanese claims database.
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