Big Data and Dementia: Charting the Route Ahead for Research, Ethics, and Policy

Abstract

Emerging trends in pervasive computing and medical informatics are creating the possibility for large-scale collection, sharing, aggregation and analysis of unprecedented volumes of data, a phenomenon commonly known as big data. In this contribution, we review the existing scientific literature on big data approaches to dementia, as well as commercially available mobile-based applications in this domain. Our analysis suggests that big data approaches to dementia research and care hold promise for improving current preventive and predictive models, casting light on the etiology of the disease, enabling earlier diagnosis, optimizing resource allocation, and delivering more tailored treatments to patients with specific disease trajectories. Such promissory outlook, however, has not materialized yet, and raises a number of technical, scientific, ethical, and regulatory challenges. This paper provides an assessment of these challenges and charts the route ahead for research, ethics, and policy.

Keywords: Alzheimer’s disease; big data; dementia; ethics; health policy; m-health; mild cognitive impairment; real-world evidence.

Figure 1

Tackling the global dementia epidemic requires the deployment of all possible scientific and health policy means. Yet, success in this ongoing battle also depends, and in a crucial way, on targeting the right enemy and using available resources efficiently. As the big data turn starts to invest medicine, opportunities emerge to deploy new, effective weapons against this disabling condition. Our analysis revealed that the prospect of using big data for dementia research and care is still in its infancy, and that numerous challenges lie ahead on the way to furthering progress in this field. An integrative approach can overcome such obstacles and help reap the benefits of big data in dementia research and care.