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
N1 - Copyright © 2022 Shi, Nikolic, Fischaber, Black, Rankin, Epelde, Beristain, Alvarez, Arrue, Pita Costa, Grobelnik, Stopar, Pajula, Umer, Poliwoda, Wallace, Carlin, Pääkkönen and De Moor.
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
UR - http://www.scopus.com/inward/record.url?scp=85128398681&partnerID=8YFLogxK
U2 - 10.3389/fpubh.2022.838438
DO - 10.3389/fpubh.2022.838438
M3 - Article
C2 - 35433572
AN - SCOPUS:85128398681
VL - 10
JO - Frontiers in Public Health
JF - Frontiers in Public Health
SN - 2296-2565
M1 - 838438
ER -
