BigMedilytics

BigMedilytics

In the spring of 2018, ESHPM was awarded an EU Horizon2020 grant of approximately one million euro to conduct research into the use of Big Data in healthcare (grant agreement no. 780495). In this study, bearing the title BigMedilytics (full name: Big Data for Medical Analytics), in the coming three years we will conduct research into which conditions are needed for increasing productivity in healthcare using Big Data.

Big Medilytics

BigMedilytics project

 

The BigMedilytics study will focus on three themes:

  1. preventing chronic illnesses: by comparing databases, can we develop insights that could result in fewer patients with a chronic illness being referred to secondary care?
  2. personalised diagnostics in oncology: how can Big Data contribute to the development of personalised care and reduce complications in oncology?
  3. optimising the logistics of people and resources in hospitals.

Philips is the coordinator of the Big Medilytics project, and there are 35 partners consisting of hospitals, pharmaceutical organisations, healthcare insurers, organisations representing small and medium sized enterprises, and research institutes throughout Europe. At Erasmus School of Health Policy & Management, the project will be coordinated by Prof. Antoinette de Bont and Dr Anne Marie Weggelaar (MCM). (insert link to their personal pages).

ESHPM’s activities in this study will focus on the formulation of indicators to measure productivity gains, knowledge about formal and informal rules for using Big Data, business models for Big Data technologies and factors that inhibit or promote the use of Big Data in healthcare.

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Learn more about BigMedilytics:

Big Medilytics project website
Horizon 2020
Big Data Value Association

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 780495. Any dissemination of results presented here solely reflect the consortium view. The Commission is not responsible for any use that may be made of the information it contains.