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Big data - creating new insights into heart failure

57 months
Approved budget:
Associate Professor Hamish Jamieson
Health issue:
Proposal type:
Sir Charles Hercus Fellowship
Lay summary
This ground-breaking study will link existing New Zealand health data from multiple sources to develop an improved statistical model to predict outcomes for older people with heart failure. Heart failure is the most common cause of hospital admission in older adults and has a five-year mortality of 50%. Multiple studies have shown that outcomes for patients with heart failure are difficult to predict, particularly older people who frequently have multiple comorbidities. This study will use cutting edge statistical methods to mine the world leading datasets that NZ is currently collecting on older people, to make a significant difference to people’s health status. The improved risk model for outcomes in older people with heart failure will provide information that will be used directly to better target health services and improve patient care as well as growing understanding of the causative factors resulting in poor outcomes.