Using big data to improve vascular risk prediction and targeted treatment (Video) Event as iCalendar

(Seminars)

26 July 2016

4 - 5pm

Venue: Ground Floor Seminar Room (G10)

Location: 70 Symonds Street, Auckland Central

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An ABI seminar by Professor Rod Jackson, School of Population Health, University of Auckland

Abstract

Readily available treatments can halve the risk of premature vascular disease but under- and over-treatment is common and there are substantial ethnicity- and deprivation-related inequities in vascular disease burden. The effectiveness of most treatments depends on patients’ risks of developing vascular disease but estimating risk is difficult without risk prediction algorithms and few valid algorithms have been developed.

We have established three overlapping ‘big-data’ cohort studies: a primary care cohort, a hospital cohort and a national cohort. These cohorts are electronically linked to the same routine national health datasets of laboratory investigations, drug treatment, hospitalisations and deaths. Using these linked data we will: (1) develop new risk prediction algorithms to assist clinicians estimate vascular risk in multiple high-risk populations; (2). determine in whom, where and why, under- and over-treatment and inequities in vascular risk and risk management occur; and (3) develop and implement a multi-algorithm risk prediction engine and a ‘big-data’ vascular health information platform to support initiatives to increase appropriate treatment, reduce inequities in vascular disease outcomes and improve overall vascular health.