Background:We live in a data rich, information driven society with numerous data sources available that have the potential to provide new insights into areas such as disease prevention, policy decisions, and personalised medicine. Data sources are not optimally utilised, existing in heterogeneous silos with no current solution to connect or integrate them with valuable open and social data1; a solution to enable evidence-based health policy decision making, leading to significant improvements in health care and quality of life2.Materials & Methods:The MIDAS project is developing a big data platform that facilitates the utilisation of healthcare data beyond existing isolated systems making that data amenable to enrichment with open and social data. The platform will enable the integration of heterogeneous data sources, provide privacy-preserving analytics, forecasting tools and bespoke visualisations of actionable information. Policy makers will have the capability to perform data-driven evaluations of the efficiency and effectiveness of proposed policies in terms of expenditure, delivery, wellbeing, and health and socio-economic inequalities, thus improving current policy risk stratification.Results:With a unique combination of data scientists, and a Policy Board comprising health policy makers and data guardians, MIDAS is producing a platform that empowers policy makers by providing actionable knowledge to support decision making at regional and national levels. The Policy Board’s involvement ensures that the platform meets real user requirements, is usable, effective, and respects governance, ethical, consent and privacy aspects.Conclusions:There is an urgent need to develop applications and tools to consume and map the variety of data from the public, patients and healthcare systems to make it more meaningful, insightful and useful for health policy makers3. MIDAS will exploit the enormous economic potential ofthis data and big data analytics to benefit the economy and society, setting in motion a newnetwork of knowledge pertinent to supporting enhanced public health decision-making.
|Title of host publication||Unknown Host Publication|
|Number of pages||1|
|Publication status||Published - 20 Sep 2017|
|Event||8th Annual Translational Medicine Conference - City Hotel, Derry/Londonderry, Northern Ireland|
Duration: 20 Sep 2017 → …
|Conference||8th Annual Translational Medicine Conference|
|Period||20/09/17 → …|
Bibliographical noteReference text: 1. Belle, A., Thiagarajan, R., Soroushmehr, S.M.R., Navidi, F., Beard, D.A., and Najarian, K.; Big Data Analytics in Health care; BioMed Research International; Volume 2015; 2015.2. Schroeck, M., Shockley, R., Smart, J., Romero-Morales, D. and Tufano, P.; Analytics: The real-world use of big data - How innovative enterprises extract value from uncertain data; IBM Institute for Business Value; 2013.3. Raghupathi, W. and Raghupathi, V.; Big data analytics in health care: promise and potential; Health Information Science and Systems; 2:3; 2014.
- big data
- data analytics