HomeResearchHealth Data Management & SemanticsClinical Data Aquisition, Integration, Visualisation & Analysis

Clinical Data Aquisition, Integration, Visualisation & Analysis

Breakthroughs in early diagnosis tools and interventions require the exploitation of numerous data sets, including those generated by clinical trials. Typically, clinical trials collect health information from volunteers over a number of years to correlate observations across the cohort and uncover new insights into disease progression or drug performance. The complexity of these data sets demands specialist skills and tools in its acquisition, integration, management, visualisation and analysis. The Australian e-Health Research Centre (AEHRC) has strong research and development capability in these areas, and this is being utilised to support research into neurodegenerative diseases such as Alzheimer's disease and Stroke for the CSIRO Preventative Health National Flagship.

Our approach to clinical data acquisition is driven by a number of challenges:

  • to respect the semantic meaning of clinical data by building tools that capture its inherent complexity. For example, cognitive decline captured by neuropsychological test results over time can be related to anatomical changes in the brain such as cortical thickness.
  • to ensure tools support being "bolted on" to the health information technology infrastructure at medical treatment facilities treating to ensure data is readily available.
  • to deal with patient information spread across the Australian health care system, in different disciplines, organisations and jurisdictions.

Where data already exist, our HDI technology will continue to provide a useful data integration capability and to provide HDI with more semantically meaningful data integration capabilities, we are developing new tools, the Snapper Platform, that more accurately capture the semantic meaning of clinical data using standard clinical terminologies. Typically, captured clinical data is stored in an information model, of which there are are several emerging standards around the world, including openEHR and the NHS Logical Record Architecture. Our involvement in clinical trials, along with our work with Queensland Health collaborators, provides opportunities to test these technologies in "real world" settings.

We are acting as data managers and part of the bio-statistical team for trials conducted with the CSIRO Preventative Health National Flagship; the Australian Imaging, Biomarker and Lifestyle (AIBL) Flagship Study of Ageing and START.

AIBL is globally significant due to its large scale: some 1112 volunteers are involved in the trial, including over 600 health control subjects who have completed a large battery of neuropsychological tests. Traditionally, Australian neuropsychologists assess individual patient cognitive performance using normative data gathered from low numbers of overseas subjects, while the scale of AIBL provides researchers with a unique opportunity to create a normative data set that more accurately reflects Australian cognitive performance norms. Access to such a data set would enable clinicians to compare the cognitive performance of a patient relative to healthy older Australians, and thereby assist them in developing strategies for disease sufferers and their families.

Software engineering expertise is being contributed to the research effort of AIBL and START in the following ways:

OpenClinica and AIBL


Due to the complexity inherent in the data, the visualisation of electronic health records in the clinical setting, and the comparison of a patient's health against clinical guidelines or a cohort, is becoming a key requirement for clinical systems. This project will continue its early Patient Journey Browser work by giving researchers with the ability to visualise the journey of participants through the trial.

Last Updated on Monday, 19 December 2011 12:49

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Simon McBride

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