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Front. Digit. Humanit. | doi: 10.3389/fdigh.2018.00008

Big Data as a driver for Clinical Decision Support Systems: a Learning Health Systems perspective

Arianna Dagliati1,  Valentina Tibollo1, Lucia Sacchi2, Alberto Malovini1,  Ivan Limongelli3, Matteo Gabetta4, Carlo Napolitano1, Andrea Mazzanti1, Pasquale De Cata1,  Luca Chiovato1, Silvia Priori1 and  Riccardo Bellazzi1, 2*
  • 1IRCCS Istituti Clinici Scientifici Maugeri (ICS Maugeri), Italy
  • 2Electrical, Computer and Biomedical Engineering, University of Pavia, Italy
  • 3enGenome srl, Italy
  • 4Biomeris s.r.l., Italy

Big data technologies are nowadays providing health care with powerful instruments to gather and analyze large volumes of heterogeneous data collected for different purposes, including clinical care, administration and research. This makes possible to design IT infrastructures that favor the implementation of the so-called "Learning Healthcare System Cycle", where healthcare practice and research are part of a unique and synergic process. In this paper we highlight how "Big Data enabled" integrated data collections may support clinical decision-making together with biomedical research. Two effective implementations are reported, concerning decision support in Diabetes and in Inherited Arrhythmogenic Diseases.

Keywords: big data, learning health care cycle, Data Warehouses, data integration, data analytics

Received: 30 Jan 2018; Accepted: 09 Apr 2018.

Edited by:

Pierpaolo Cavallo, Università degli Studi di Salerno, Italy

Reviewed by:

Gokarna Sharma, Kent State University, United States
AMAR KOLETI, University of Miami, United States  

Copyright: © 2018 Dagliati, Tibollo, Sacchi, Malovini, Limongelli, Gabetta, Napolitano, Mazzanti, De Cata, Chiovato, Priori and Bellazzi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Riccardo Bellazzi, University of Pavia, Electrical, Computer and Biomedical Engineering, Via Ferrata 5, Pavia, 27100, Italy, riccardo.bellazzi@unipv.it