Big data analysis for improved mental healthcare: A population-based perspective

Abstract

Introduction Mental disorder is a key public health challenge due to its high levels of disability and mortality and a leading cause of DALYs (Disability adjusted life years). Therefore, a small improvement on mental care provision and management could generate solid benefits on relieving the social burden of mental diseases. Objective Long-term vision of collaboration between Fujitsu Laboratories, Fujitsu Spain, and Hospital Clinico San Carlos is to generate value through predictive and preventive medicine improving healthcare outcomes for every clinical area, benefiting managers, clinicians, and patients. Aims The aim is to enable a data centric approach towards a value-based healthcare system via health informatics. The project fuses knowledge from heterogeneous sources for obtaining patterns for clinical decision-making. Methods This project leverages a data analytic platform named HIKARI (light in Japanese) to deliver the right information, to the right people, at the right time. HIKARI consists of a data-driven and evidence-based Decision Support and Recommendation System (DSRS), facilitating identification of patterns in large-scale datasets and linking of data from different sources and types. Results Using multiple, heterogeneous datasets, HIKARI detects correlations from data retrospectively and conducts early intervention when signs and symptoms prompt immediate actions. HIKARI also highlights resource consumption patterns and suggests future resource allocation, using real-life data. Conclusions With the advance of ICT, especially data-intensive computing paradigm, approaches mixing individual risk assessment and environmental conditions become increasingly prevalent. HIKARI DSRS can serve as a key tool for individuals and clinicians daily management of mental disorders.