Evaluating variations in healthcare outcome using health insurance big data: a multilevel analysis

The presence of comorbid conditions along with heterogeneity in terms of healthcare practices and service delivery could have a significant impact on a patient's outcomes. Therefore, the current study was conducted to quantify the extent to which such variations influence the risk of hemodialysis-associated infection (HAI). A total of 6,111 patients with end-stage renal disease (ESRD) who received hemodialysis treatment between 1 October 2015 and 31 March 2016 were identified from an insurance claim database. Patients were followed for one year from 1 April 2016 to 31 March 2017. A total of 200 HAI cases were observed during the follow-up and 12 patients died within 90 days of the onset of HAI. The results of the multilevel analyses indicated that HAI variations were only significant at the care facility level and were largely explained by the heterogeneity between care facilities. The results of this study highlight the need to look beyond the influence of patient-level characteristics when developing policies that aim at improving the quality of haemodialysis health care and service delivery. UiTM, Faculty of business and management, Socio environment compendium.