System Architecture of a European Platform for Health Policy Decision Making: MIDAS

Xi Shi; Gorana Nikolic; Scott Fischaber; Michaela Black; Debbie Rankin; Gorka Epelde; Andoni Beristain; Roberto Alvarez; Monica Arrue; Joao Pita Costa; Marko Grobelnik; Luka Stopar; Juha Pajula; Adil Umer; Peter Poliwoda; Jonathan Wallace; Paul Carlin; Jarmo Pääkkönen; Bart De Moor

doi:10.3389/fpubh.2022.838438

System Architecture of a European Platform for Health Policy Decision Making: MIDAS

Xi Shi^*, Gorana Nikolic, Scott Fischaber, Michaela Black, Debbie Rankin, Gorka Epelde, Andoni Beristain, Roberto Alvarez, Monica Arrue, Joao Pita Costa, Marko Grobelnik, Luka Stopar, Juha Pajula, Adil Umer, Peter Poliwoda, Jonathan Wallace, Paul Carlin, Jarmo Pääkkönen, Bart De Moor

^*Corresponding author for this work

Research output: Contribution to journal › Article › Scientific › peer-review

2 Citations (Scopus)

Abstract

Background: Healthcare data is a rich yet underutilized resource due to its disconnected, heterogeneous nature. A means of connecting healthcare data and integrating it with additional open and social data in a secure way can support the monumental challenge policy-makers face in safely accessing all relevant data to assist in managing the health and wellbeing of all. The goal of this study was to develop a novel health data platform within the MIDAS (Meaningful Integration of Data Analytics and Services) project, that harnesses the potential of latent healthcare data in combination with open and social data to support evidence-based health policy decision-making in a privacy-preserving manner. Methods: The MIDAS platform was developed in an iterative and collaborative way with close involvement of academia, industry, healthcare staff and policy-makers, to solve tasks including data storage, data harmonization, data analytics and visualizations, and open and social data analytics. The platform has been piloted and tested by health departments in four European countries, each focusing on different region-specific health challenges and related data sources. Results: A novel health data platform solving the needs of Public Health decision-makers was successfully implemented within the four pilot regions connecting heterogeneous healthcare datasets and open datasets and turning large amounts of previously isolated data into actionable information allowing for evidence-based health policy-making and risk stratification through the application and visualization of advanced analytics. Conclusions: The MIDAS platform delivers a secure, effective and integrated solution to deal with health data, providing support for health policy decision-making, planning of public health activities and the implementation of the Health in All Policies approach. The platform has proven transferable, sustainable and scalable across policies, data and regions.

Original language	English
Article number	838438
Number of pages	13
Journal	Frontiers in Public Health
Volume	10
DOIs	https://doi.org/10.3389/fpubh.2022.838438
Publication status	Published - 2022
MoE publication type	A1 Journal article-refereed

Funding

This work was supported by KU Leuven: Research Fund (projects C16/15/059, C3/19/053, C32/16/013, and C24/18/022), Industrial Research Fund (Fellowship 13-0260), and several Leuven Research and Development bilateral industrial projects, Flemish Government Agencies: FWO [EOS Project no 30468160 (SeLMA), SBO project S005319N, Infrastructure project I013218N, TBM Project T001919N; Ph.D. Grants (SB/1SA1319N, SB/1S93918, SB/151622)]. This research received funding from the Flemish Government (AI Research Program). BD and XS are affiliated to Leuven.AI–KU Leuven institute for AI, B-3000, Leuven, Belgium. VLAIO [City of Things (COT.2018.018), Ph.D. grants: Baekeland (HBC.20192204) and Innovation mandate (HBC.2019.2209), Industrial Projects (HBC.2018.0405)], European Commission: This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant Agreement No 885682), (EU H2020-SC1-2016-2017 Grant Agreement No. 727721: MIDAS), and KOTK foundation.

Keywords

data visualization
decision support system
epidemiology
machine learning
public health
Decision Making
Public Health
Delivery of Health Care
Humans
Information Storage and Retrieval
Health Policy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Cite this

Shi, X., Nikolic, G., Fischaber, S., Black, M., Rankin, D., Epelde, G., Beristain, A., Alvarez, R., Arrue, M., Pita Costa, J., Grobelnik, M., Stopar, L., Pajula, J., Umer, A., Poliwoda, P., Wallace, J., Carlin, P., Pääkkönen, J., & De Moor, B. (2022). System Architecture of a European Platform for Health Policy Decision Making: MIDAS. Frontiers in Public Health, 10, Article 838438. https://doi.org/10.3389/fpubh.2022.838438

@article{879e13e85df24ee6bb6115667769561c,

title = "System Architecture of a European Platform for Health Policy Decision Making: MIDAS",

abstract = "Background: Healthcare data is a rich yet underutilized resource due to its disconnected, heterogeneous nature. A means of connecting healthcare data and integrating it with additional open and social data in a secure way can support the monumental challenge policy-makers face in safely accessing all relevant data to assist in managing the health and wellbeing of all. The goal of this study was to develop a novel health data platform within the MIDAS (Meaningful Integration of Data Analytics and Services) project, that harnesses the potential of latent healthcare data in combination with open and social data to support evidence-based health policy decision-making in a privacy-preserving manner. Methods: The MIDAS platform was developed in an iterative and collaborative way with close involvement of academia, industry, healthcare staff and policy-makers, to solve tasks including data storage, data harmonization, data analytics and visualizations, and open and social data analytics. The platform has been piloted and tested by health departments in four European countries, each focusing on different region-specific health challenges and related data sources. Results: A novel health data platform solving the needs of Public Health decision-makers was successfully implemented within the four pilot regions connecting heterogeneous healthcare datasets and open datasets and turning large amounts of previously isolated data into actionable information allowing for evidence-based health policy-making and risk stratification through the application and visualization of advanced analytics. Conclusions: The MIDAS platform delivers a secure, effective and integrated solution to deal with health data, providing support for health policy decision-making, planning of public health activities and the implementation of the Health in All Policies approach. The platform has proven transferable, sustainable and scalable across policies, data and regions.",

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author = "Xi Shi and Gorana Nikolic and Scott Fischaber and Michaela Black and Debbie Rankin and Gorka Epelde and Andoni Beristain and Roberto Alvarez and Monica Arrue and {Pita Costa}, Joao and Marko Grobelnik and Luka Stopar and Juha Pajula and Adil Umer and Peter Poliwoda and Jonathan Wallace and Paul Carlin and Jarmo P{\"a}{\"a}kk{\"o}nen and {De Moor}, Bart",

note = "Copyright {\textcopyright} 2022 Shi, Nikolic, Fischaber, Black, Rankin, Epelde, Beristain, Alvarez, Arrue, Pita Costa, Grobelnik, Stopar, Pajula, Umer, Poliwoda, Wallace, Carlin, P{\"a}{\"a}kk{\"o}nen and De Moor.",

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doi = "10.3389/fpubh.2022.838438",

language = "English",

volume = "10",

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Shi, X, Nikolic, G, Fischaber, S, Black, M, Rankin, D, Epelde, G, Beristain, A, Alvarez, R, Arrue, M, Pita Costa, J, Grobelnik, M, Stopar, L, Pajula, J , Umer, A, Poliwoda, P, Wallace, J, Carlin, P, Pääkkönen, J & De Moor, B 2022, 'System Architecture of a European Platform for Health Policy Decision Making: MIDAS', Frontiers in Public Health, vol. 10, 838438. https://doi.org/10.3389/fpubh.2022.838438

TY - JOUR

T1 - System Architecture of a European Platform for Health Policy Decision Making

T2 - MIDAS

AU - Shi, Xi

AU - Nikolic, Gorana

AU - Fischaber, Scott

AU - Black, Michaela

AU - Rankin, Debbie

AU - Epelde, Gorka

AU - Beristain, Andoni

AU - Alvarez, Roberto

AU - Arrue, Monica

AU - Pita Costa, Joao

AU - Grobelnik, Marko

AU - Stopar, Luka

AU - Pajula, Juha

AU - Umer, Adil

AU - Poliwoda, Peter

AU - Wallace, Jonathan

AU - Carlin, Paul

AU - Pääkkönen, Jarmo

AU - De Moor, Bart

PY - 2022

Y1 - 2022

N2 - Background: Healthcare data is a rich yet underutilized resource due to its disconnected, heterogeneous nature. A means of connecting healthcare data and integrating it with additional open and social data in a secure way can support the monumental challenge policy-makers face in safely accessing all relevant data to assist in managing the health and wellbeing of all. The goal of this study was to develop a novel health data platform within the MIDAS (Meaningful Integration of Data Analytics and Services) project, that harnesses the potential of latent healthcare data in combination with open and social data to support evidence-based health policy decision-making in a privacy-preserving manner. Methods: The MIDAS platform was developed in an iterative and collaborative way with close involvement of academia, industry, healthcare staff and policy-makers, to solve tasks including data storage, data harmonization, data analytics and visualizations, and open and social data analytics. The platform has been piloted and tested by health departments in four European countries, each focusing on different region-specific health challenges and related data sources. Results: A novel health data platform solving the needs of Public Health decision-makers was successfully implemented within the four pilot regions connecting heterogeneous healthcare datasets and open datasets and turning large amounts of previously isolated data into actionable information allowing for evidence-based health policy-making and risk stratification through the application and visualization of advanced analytics. Conclusions: The MIDAS platform delivers a secure, effective and integrated solution to deal with health data, providing support for health policy decision-making, planning of public health activities and the implementation of the Health in All Policies approach. The platform has proven transferable, sustainable and scalable across policies, data and regions.

AB - Background: Healthcare data is a rich yet underutilized resource due to its disconnected, heterogeneous nature. A means of connecting healthcare data and integrating it with additional open and social data in a secure way can support the monumental challenge policy-makers face in safely accessing all relevant data to assist in managing the health and wellbeing of all. The goal of this study was to develop a novel health data platform within the MIDAS (Meaningful Integration of Data Analytics and Services) project, that harnesses the potential of latent healthcare data in combination with open and social data to support evidence-based health policy decision-making in a privacy-preserving manner. Methods: The MIDAS platform was developed in an iterative and collaborative way with close involvement of academia, industry, healthcare staff and policy-makers, to solve tasks including data storage, data harmonization, data analytics and visualizations, and open and social data analytics. The platform has been piloted and tested by health departments in four European countries, each focusing on different region-specific health challenges and related data sources. Results: A novel health data platform solving the needs of Public Health decision-makers was successfully implemented within the four pilot regions connecting heterogeneous healthcare datasets and open datasets and turning large amounts of previously isolated data into actionable information allowing for evidence-based health policy-making and risk stratification through the application and visualization of advanced analytics. Conclusions: The MIDAS platform delivers a secure, effective and integrated solution to deal with health data, providing support for health policy decision-making, planning of public health activities and the implementation of the Health in All Policies approach. The platform has proven transferable, sustainable and scalable across policies, data and regions.

KW - data visualization

KW - decision support system

KW - epidemiology

KW - machine learning

KW - public health

KW - Decision Making

KW - Public Health

KW - Delivery of Health Care

KW - Humans

KW - Information Storage and Retrieval

KW - Health Policy

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U2 - 10.3389/fpubh.2022.838438

DO - 10.3389/fpubh.2022.838438

M3 - Article

C2 - 35433572

AN - SCOPUS:85128398681

SN - 2296-2565

VL - 10

JO - Frontiers in Public Health

JF - Frontiers in Public Health

M1 - 838438

ER -

System Architecture of a European Platform for Health Policy Decision Making: MIDAS

Abstract

Funding

Keywords

UN SDGs

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