Enabling Personalized Interventions - EPI


Knowledge is power -- and in healthcare, that holds absolutely true. Yet, for an industry that is under financial stress, increasing complexity of disease and comorbidity, and burdened by capacity constraints -- why has data not been healthcare’s savvier? Three major challenges have inhibited this: 1) data is not accessible and remains in siloes; 2) data is not analysed to derive meaningful clinical insights; 3) insight isn’t accessible for actioning by providers or patients to self/joint manage their condition. Our consortium of healthcare providers, data scientists, healthtech providers, strategists, and legal experts have designed Enabling Patient Interventions to liberate, analyse, and action that data in a trustworthy way. EPI aims to empowers patients and providers through self-management, shared management, and personalization across the full health spectrum. To do so, we will build a fuller picture of the person by linking traditional eHealth data sets with new sources of data. Further, we will develop a platform based upon a secure and trustworthy distributed data infrastructure, combining data analytics, including machine learning, and health decision support algorithms to create new, actionable, and personalized insights for prevention, management, and intervention to providers and patients. We will develop new machine learning methods for determining and analysing optimal interventions within small patient groups. Our insights will be applied in healthcare use cases representing a spectrum of health management challenges ranging from common chronic to highly lethal orphan diseases, and will empower better self/joint management of these conditions to improve cost, quality, and outcomes of care.


Project number


Main applicant

Prof. dr. ir. C.T.A.M. de Laat

Affiliated with

Universiteit van Amsterdam, Faculteit der Natuurwetenschappen, Wiskunde en Informatica, Instituut voor Informatica (IVI)


01/03/2018 to 28/02/2022