Visual and Decision Analytics (VIDEA) Lab

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About

The Visual and Decision Analysis (VIDEA) Lab is a new service and research organisation. The VIDEA Lab is Australia’s first lab combining expertise in two recent and related areas of knowledge: visual analytics and decision analytics. The VIDEA’s powerful approach creates new opportunities for better mental and public health planning.

The VIDEA Lab aims to be at the centre of a national and international visual and decision analytics hub coordinated by the CMHR/RSPH/CHM at ANU. This hub will bring together decision-scientists and visual analytics experts from many disciplines across Australia and worldwide to research specific areas of policy and society.

  • Visual Analytics

We are using new and advanced technologies and methods (e.g., machine learning, artificial intelligence and network analysis) with data science capacity to visually analyse patterns of mental healthcare across community to provide a better knowledge base as well as optimising communication with policy makers and stakeholders mainly in the public health sector. Our existing capacity in machine learning, data visualisation, modelling and advanced data mining enables us to apply this unique expertise to analyse and visualise complex healthcare data sets.

  • Decision Analytics

Decision analytics applies a unique participatory approach to developing the models, providing better transparency of models and their assumptions, and enabling us to generate evidence-informed knowledge in a way that captures the complex and dynamic nature of health and social problems. In bringing together researchers with the end users and deeply engaging them in the process of developing these tools, our models incorporate insights from policy and practice, and are driven by policy priorities. Decision analytics utilises technologies and methods (visual analytics approaches) to develop adaptable decision support tools that forecast the impact of alternative decision options before they are implemented in the real world.

  • Healthcare Ecosystem and Systems Dynamics

In healthcare ecosystem and systems dynamics approach, all elements of healthcare interact with each other at different levels: micro (individual level), meso (regional level) and macro level (national level). Visual and decision analytics will help us to quantify contextual factors in healthcare ecosystem and link with health provider attributes to provide better understanding of healthcare landscape. Policy makers can use the output of decision analytics to prioritise policy planning and intervention.

  • Geospatial Analysis

Another arm of the VIDEA Lab is capacity of geospatial analysis and spatial visualisation of healthcare patterns using GIS (Geographical Information Systems) technology. VIDEA Lab has extensive expertise in medical geography and spatial epidemiology to support spatial analysis at CMHR and RSPH levels.

 

Activities

  • International development of Integrated Atlases of Mental Health
  • Application of machine learning approaches to mental healthcare systems
  • Development of index of contextual factors of healthcare ecosystem
  • Geospatial analysis of rural and urban mental health
  • Contribution to inaugural ANU grand challenges in visualising healthcare systems in particular for neurological disorders and type I diabetes
  • Collaboration across disciplines and colleges at ANU and worldwide (e.g. cross-college collaboration: joint workshops and training courses with ANU college of Engineering and Computer Science and School of Demography)
  • Organisation of a series of seminars and workshops on systems thinking and decision analytics for different audience at different levels of visual and decision analytics
  • Engagement and communication with national and international research and policy in healthcare (e.g. policy makers at PHNs, National Mental Health Commission, Department of Health and international organisations)
  • Hosting of international and national scholars in the VIDEA Lab and exchanging knowledge between academic colleagues around the world
  • Supervision of early career researchers and students
  • Development of Healthcare Systems Engineering course at graduate level

 

Global/Local Mental Health Projects

  • Integrated Mental Health Atlas of PHNs in Australia
  • Social Fragmentation and Mental Health (GIS)
  • Dementia Risk Hot Spots Analysis
  • Visual Data Mining and Complex Mental Healthcare Systems

 

Visual Tools

  • SOMNET
  • GIS and complex indices (i.e. social fragmentation index)
  • Spider graphs of patterns of care
  • Balance of care

 

Members