Data mining of administrative claims data for pathology services

Australia has a universal health insurance scheme called Medicare. Medicare payments for pathology services generate voluminous transaction data on patients, doctors and pathology laboratories. The Health insurance Commission (HIC) currently uses predictive models to monitor compliance with regulatory requirements. The HIC commissioned a project to investigate the generation of new features from the data. These features were summarised, visualised and used as inputs for clustering and outlier detection methods. Some initial interpretations and insights into the pathology service industry are discussed. Further work is required for feature selection, training of predictive models with the new features and the evaluation of performance against the currently deployed models.