Knowledge is power -- and in healthcare, that holds
absolutely true. Yet, for an industry that is under financial stress,
increasing complexity of disease and co-morbidity, and burdened by
capacity constraints -- why has data not been healthcare's savvier?
Three major challenges have inhibited this:
- data is not accessible and remains in silos;
- data is not analysed to derive meaningful clinical insights;
- insight isn't accessible for actioning by providers or patients to self/joint manage their condition.
Our consortium of medical professionals, data
scientists, IT-infrastructure experts, machine learning researchers and
legal experts have designed Enabling Patient Interventions to liberate,
analyse, and action that data in a trustworthy way. EPI aims to empower
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.
Here are introductory slides about the project: in Dutch, and in English. This website is reachable under: https://epi-project.nl/ and https://enablingpersonalizedinterventions.nl/
The overall aim of this project is to explore the
use and effectiveness of data driven development of scientific
algorithms, supporting personalized self- and joint management during
medical interventions / treatments. The key objective is to use data
science promoting health practically with data from various sources to
formulate lifestyle advice, prevention, diagnostics, and treatment
tailored to the individual, and to provide personalized, effective,
real-time feedback via a concept referred in this proposal as a digital
health twin. The project addresses six research questions:
- Dynamically Analyzing Interventions
based on Small Groups: how can we determine, based on as little data as
possible, whether an intervention does or does not work for a small
group or even an individual patient? And how can we identify effective
intervention strategies and optimize personalization strategies
applicable for different patient and lifestyle profiles via dynamic
(on-line) clustering of patients?
- Lead CWI: Rosanne Turner, Peter Grunwald
- Data and Algorithm Distribution:
what are the consequences of a distributed, multi-platform,
multi-domain, multi-data-source big data infrastructure on the machine
learning algorithms and what are potential consequences on performance?
- Lead: VU, Corinne Allaart, Henri Bal
- Adaptive health diagnosis leading to
optimized intervention: how can we enhance self- / joint management by
dynamically integrating updated models generated from machine learning
from various data sources in state of the art health support systems
that based on personal health records, knowledge of health modes and
- Lead: UvA, Saba Amiri, Adam Belloum
- Regulatory constraints and data
governance: how can we create scalable solutions that meet legal
requirements and consent or medical necessity-based access to data for
allowed data processing and preventing breaches of these rules by
embedded compliance, providing evidence trails and transparency, thus
building trust in a sensitive big data sharing infrastructure?
- Lead: UvA, Milen Girma Kebede, Giovanni Sileno, Tom van Engers
- Infrastructure: how can the various
requirements from the use-cases be implemented using a single functional
- Lead: UvA, Jamila Kassem, Paola Grosso
- Principle Investigators: Prof.dr.ir.
C.T.A.M. de Laat, <firstname.lastname@example.org>, prof. dr. Sander Klous
- Project contact: Marloes Bons <Bons.Marloes@kpmg.nl> or +31 20 656 7859
- This work is part of the project Enabling Personalized Interventions (EPI) and is supported by NWO in the Commit2Data - Data2Person program under contract 628.011.028.
For more information see: https://enablingpersonalizedinterventions.nl
- Leon Gommans, John Vollbrecht, Betty Gommans -
de Bruijn, Cees de Laat, "The Service Provider Group Framework; A
framework for arranging trust and power to facilitate authorization of
network services.", Future Generation Computer Systems, (Accepted
paper), June 2014
- Leon Gommans, "Multi-Domain Authorization for e-Infrastructures", UvA, Dec 2014.
- Internet2 2012 session: "Trust Framework for Multi-Domain Authorization".
- speakers: Leon Gommans , John Vollbrecht, chair: Cees de Laat.
- Managing Our Hub Economy, Marco Iansiti, Karim R. Lakhani, Harvard Business review, September-October 2017 issue, [local copy]
- NWO press release: Enabling Personalized Interventions - EPI.
||Presentation and paper
by Onno Valkering at 17th IEEE eScience
2021, International Conference ReWorDS21 workshop: "Brane: A
Framework for Programmable Orchestration of Multi-site Applications."
||Presentation and paper by Jamila Alsayed Kassem at
17th IEEE eScience 2021, International Conference: "EPI Framework:
Approach for Traffic Redirection Through Containerised Network
||Presentation by Thomas van Binsbergen at
Communications of the ACM Europe Region Special Section Virtual Workshop
(CACM), aug 25 - 26, 2021: "Digital Data Marketplaces".
||Presentations at the EPI Quarterly meeting on July 1, 2021.
||Paper: Rosanne Turner, Alexander Ly,
Peter Grünwald, "Safe Tests and Always-Valid Confidence Intervals for
contingency tables and beyond", Published on arXiv:2106.02693 [stat.ME].
||Presentations at the EPI April 22, 2021: Tiny Workshop & Consortium Meeting Enabling Personalized Interventions.
||Presentation and abstract at ICT-Open 2021 Feb 10-11, 2021: Jamila Alsayed Kassem, "EPI Framework: A dynamic infrastructure to support health applications."
||Paper: Kebede Girma, M., "Automating
Normative Control for Healthcare Research", Position paper at AICOL
workshop in the doctoral consortium panel. http://www.aicol.eu
||Paper: Kebede Girma, M., Sileno, G., and van Engers,
T., A critical reflection on ODRL. Proceedings of the 11th Workshop on
Artificial Intelligence and the Complexity of Legal Systems AICOL2020,
in conjunction with JURIX 2020.
||Short Paper: R.J. Turner and P.D. Grünwald. "Safe
Tests for 2 x 2 Contingency Tables and the Cochran-Mantel-Haenszel Test"
presentation at BNAIC/ BENELEARN 2020.
||Paper: Jamila Alsayed Kassem, Cees de Laat, Arie
Taal, and Paola Grosso, The EPI Framework: A dynamic data sharing
framework for healthcare use cases", IEEE Acees journal, Digital
Object Identifier DOI 10.1109/ACCESS.2020.3028051
||Paper: Wouter van Haaften, Alex Sangers, Tom van
Engers, Somayeh Djafari, "Coping with the general data protection
regulation: Anonymization through multi-party computation technology.",
IRIS/SCIS Conference, 9-12 August 2020, Sundsvall, Sweden, <https://www.irisscis2020.com>
||Rosanne J. Turner, "Safe Statistics for Means and Proportions", video presentation at the Machine Learning Summer School 2020 by the Max Planck Institute for Intelligent Systems, Tübingen, Germany. Link to the video: https://youtu.be/H5RMtnydAQI
||Presentation at the EPI-PHD online quarterly
meeting: Freek Dijkstra, "Data Exchange Demo: Share data while retaining
control and confidentiality of your data."
||Presentation at the EPI-PHD online quarterly meeting: Guido van 't Noordende, "Push authorization - the Whitebox model."
||Poster and short paper at ICT.OPEN
2020 (cancelled): Rosanne J. Turner, Alexander Ly, Judith ter Schure,
Peter D. Grünwald , "Safe Testing: online, anytime valid hypothesis
||Poster and short paper at ICT.OPEN
2020 (cancelled): Jamila Alsayed Kassem, "EPI infrastructure: A dynamic
infrastructure to secure data sharing in healthcare applications."
||Poster and short paper at ICT.OPEN
2020 (cancelled): Milen G. Kebede, Giovanni Sileno, Tom Van Engers,
"Automated regulatory constraints and data governance for healthcare,"
||Poster at NWO COMMIT2DATA PI meeting, Utrecht: "Enabling Personalized Interventions (EPI)."
||Presentation by Cees de Laat: Department
of Computer Science, AGH University of Science and Technology Krakow:
"ICT to support the transformation of Science in the Roaring Twenties."
||Poster by Corrine Allaart (VU) at Big Data Health
and Data2Person event, Amersfoort: " Distributed Deep Learning voor
||Presentation Pitch by Corinne Allaart (VU) at Big
Data Health and Data2Person event, Amersfoort: " Distributed Deep
Learning voor Cerebrovascular Accident."
||Presentation by Cees de Laat: eScience conference Visionary track, San Diego: "ICT to support the transformation of Science in the Roaring Twenties."
||Presentation by Cees de Laat: CIENA executive
briefing invited science presentation, Ottawa: "ICT to support the
transformation of Science in the Roaring Twenties."
||Presentation by Cees de Laat: Global Research Platform (GRP) workshop, San Diego: "Globally Distributed Secure Data Exchange Fabrics."
||Presentation by Cees de Laat, Sander Klous, Josine Janus at kick off meeting: "Enabling personalized Intervetions".
||SURFSARA Superdag 2018 talk: "Digital Data Markets: Trusted Data Processing in Untrusted Environments".
||Session organized by Cees de Laat (chair) at
Internet2 Summit, Washington, May 9, 2018; "Digital Marketplaces Using
Novel Infrastructure Models."
||Report from NWO/STW Workshop "ICT with Industry
2016" Lorenz Centre Leiden, Nov. 7-11th 2016; Prof. dr. Tom M. van
Engers (UvA), Prof. dr. Robert Meijer (UvA, TNO), Dr. ing. Leon Gommans
(Air France KLM Group ICT Technology Office R&D, UvA), Dr. Kees
Nieuwenhuis (Thales Nederland B.V., CTO Office), "Trusted Big Data
Sharing for Aircraft MRO using a Secure Digital Market Place mechanism."