Integration of Administrative, Clinical, and Environmental Data to Support the Management of Type 2 Diabetes Mellitus: From Satellites to Clinical Care

Arianna Dagliati, Andrea Marinoni, Carlo Cerra, Pasquale Decata, Luca Chiovato, Paolo Gamba, Riccardo Bellazzi

Research output: Contribution to journalArticlepeer-review

Abstract

A very interesting perspective of "big data" in diabetes management stands in the integration of environmental information with data gathered for clinical and administrative purposes, to increase the capability of understanding spatial and temporal patterns of diseases. Within the MOSAIC project, funded by the European Union with the goal to design new diabetes analytics, we have jointly analyzed a clinical-administrative dataset of nearly 1.000 type 2 diabetes patients with environmental information derived from air quality maps acquired from remote sensing (satellite) data. Within this context we have adopted a general analysis framework able to deal with a large variety of temporal, geo-localized data. Thanks to the exploitation of time series analysis and satellite images processing, we studied whether glycemic control showed seasonal variations and if they have a spatiotemporal correlation with air pollution maps. We observed a link between the seasonal trends of glycated hemoglobin and air pollution in some of the considered geographic areas. Such findings will need future investigations for further confirmation. This work shows that it is possible to successfully deal with big data by implementing new analytics and how their exploration may provide new scenarios to better understand clinical phenomena.

Original languageEnglish
Pages (from-to)19-26
Number of pages8
JournalJournal of Diabetes Science and Technology
Volume10
Issue number1
DOIs
Publication statusPublished - 1 Dec 2015

Keywords

  • big data
  • data analytics
  • data integration
  • diabetes mellitus
  • environmental data
  • remote sensing

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