Background

@Forcare in Zeist: The adoption of electronic healthcare records within institutions is expanding rapidly. In parallel healthcare institutions get more and more connected; to exchange medical information and facilitate collaboration on location and specialty level. This is necessary to increase healthcare efficiency of healthcare delivery in the context of lowering costs and provide more complex healthcare products. Another trend is the rise of consumer healthcare apps for monitoring health and wellness status (Quantified Self). Generation of massive amounts of patient centered healthcare data and infrastructures to connect different sources gives us the opportunity analyzing these data and use this in a clinical prevention context. A number of studies have been published were Electronic Healthcare Record (EHR) data are analyzed for defining parameters relevant for diseases, e.g. diabetes. These parameters can be used to detect patients from the EHR database that potentially suffer from a latent form of diabetes. Detection algorithms can be even more powerful if data from different providers/sources are combined (to the scale of Population Health). Data quality and uniformity are big challenges.

Tentative research question

How can data from Health Information Exchanges (HIE’s) be used for big data. What trends can we expect in the upcoming years and what are the challenges?

Deliverables

White paper and prototype