With our partner Barwon Health we are embarking on questions that arise in examination of large, disparate and multimodal hospital data sets. Can we impact and inform the formation of dynamic health intervention and improved safety and care through:
- Predicting hospital visitation patterns of patients with chronic disease,
- Detection of sub-populations that have coherent patterns of disease, causal factors, and typical medical responses
- Identify data driven characteristics of chronic patients to enable personalized care plans
- Detect indicators that serve as early warning of chronic disease
- Monitor key factors that deliver value to patients in the areas of care experiences, care coordination and patient safety.
Our work led to the formation of an app that allows hospital administrators and clinicians to see at a glance what’s happening in the hospital, on the ward or to their patients. This was developed over several years of research, using machine learning to mine medical and hospital data to provide hospital cost efficiencies and better predictive patient support.