Data mining of administrative claims data for pathology services
| Autor: | S. Hawkins, O. Nielsen, T. Semenova, A. Smith, R.A. Baxter, M. Hegland, Fuchun Huang, Graham Williams, M.J. Fett, Peter Christen |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
Pathology
medicine.medical_specialty Universal health insurance Computer science business.industry media_common.quotation_subject Feature selection Commission Payment computer.software_genre Data science Work (electrical) Health care medicine Health insurance Patient treatment Data mining business Cluster analysis Tertiary sector of the economy Transaction data computer media_common |
| Zdroj: | HICSS |
| DOI: | 10.1109/hicss.2001.926572 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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