Advanced clinical analyticsAbout advanced clinical analytics

The rapid growth in EHRs has created a major opportunity to create a ‘learning health system’ that uses all available information to improve the quality and safety of care. Clinical analytics and ‘big data’ represent a major new frontier in health service delivery, fuelled by informatics methods for data capture, linkage and analysis. EHRs contain rich phenotype data sets, including information about co-morbidities, and increasingly contain biomarker and genetic data. Such data can fill the evidence gap when clinical trial data is unavailable or does not match the particular circumstances of a patient, to provide highly targeted information on prognosis and therapeutic options.

The CRE will undertake a research program to help translate the next generation in decision support technologies into practice, in support of better, and safer, clinical and population decision-making. It will undertake an internationally innovative research program to evaluate the impact of data and text analytics decision support tools such as dashboards for clinical and public health decision-making. A major focus of the work will be to identify which clinical decisions are most in need of decision support, how this decision support fits into the clinical workflow, and the formulation of design and implementation processes for these new tools.

Key outcomes for clinical analytics

  1. Evaluated decision-support tools including: a patient journey board for risks of deterioration and expected remaining days of hospitalisation; a research evidence retrieval and summarisation system; and a data analytics “Green Button” system.
  2. Research evidence and guidelines for the safe and effective implementation of these tools into clinical settings.

Partners and collaborators

Alcidion
CSIRO Molecular and Health Technologies – Australian e-Health Research Centre
University of Melbourne – Health and Biomedical Informatics Centre
Health Roundtable
ICPMR-Pathology West
Macquarie University – Centre for Health Informatics
St Vincent’s Hospital Sydney
Stanford University
UCLA
University of California San Diego (UCSD)
Westmead Hospital, Sydney