Health data mining with Medicare data.

Rohan Baxter
CSIRO-MIS

Tuesday 12 June at 11am

Abstract

CSIRO is helping the Commonwealth Department of Health and Aged Care to discover useful public health information from their massive collections of medical data. By using advanced data-mining techniques to analyse Medicare and PBS (Pharmaceutical Benefits Scheme) data, the team discovered what type of patients were most likely to miss out on full care and the range of diagnostic tests recommended for diabetes patients. They found that patients in rural areas and elderly patients were most likely to not receive full care.

The information allows the Department to assess the quality of the Australian health care system and to plan cost effective public health campaigns, or provide information or training to doctors, which target the areas of greatest need. Besides quality, the technique is being applied to investigate other major public health issues such as effectiveness, access and  financing. The technique allows rapid testing of many hypotheses on massively linked data sets. It also employs statistical algorithms for identifying similar patterns of care. 

This seminar describes the methodology employed and the trials and tribulations behind the scenes of this health data mining project.

Short resume

Rohan Baxter is a Research Scientist in the Enterprise Data Mining at CSIRO Mathematical and Information Sciences Division, based in Canberra. In 1997, he founded Ultimode Inc., a data mining research and consultancy firm, in Berkeley, California. He obtained funding as a NSF and NASA SBIR principal investigator. Ultimode developed a recommendation engine based on patented dyanamic segmentation algorithms to provide internet personalisation and customer profiling services to e-commerce companies. He has a PhD in Computer Science (Machine Learning) from the Department of Computer Science, Monash University in Melbourne, Australia.

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