research-article

A system for geoanalysis of clinical and geographical data

Authors:

Giovanni Canino,

Pietro H. Guzzi,

Giuseppe Tradigo,

Pierangelo VeltriAuthors Info & Claims

HealthGIS '14: Proceedings of the Third ACM SIGSPATIAL International Workshop on the Use of GIS in Public Health

Pages 57 - 62

https://doi.org/10.1145/2676629.2676635

Published: 04 November 2014 Publication History

Abstract

Patients enrolled in clinical trials are regularly subject to biological analyses and related data is included in Electronic Medical Records (EMRs) to summarize patient health status and to support administrative information. Well defined protocols guide the bioanalytes studies on patients. Often EMRs also contain geographical data about patients, i.e. place of birth and place of living. The integration of geographical data and biological analytes may represent a meaningful way to extract hidden information from data. For instance, possible correlations among outlier patients and some feature of areas they live in.

In collaboration with the University Hospital of Catanzaro, we designed a framework able to integrate and analyze biological analytes. The system is able to relate biological data to diagnosis codes and to analyze integrated data against geographic areas of interest. The aim is to show correlations among patients features (e.g. cluster of patients with similar profiles or outlier patients) and areas features (e.g. presence of power grids or polluted sites). In addition we present a study on correlations between cardiovascular diseases and water quality in Calabria.

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Cited By

Mollalo AHamidi BLenert LAlekseyenko A(2024)Application of Spatial Analysis on Electronic Health Records to Characterize Patient Phenotypes: Systematic ReviewJMIR Medical Informatics10.2196/5634312(e56343)Online publication date: 15-Oct-2024
https://doi.org/10.2196/56343
Tradigo GVizza PBrescia GGuzzi PVeltri P(2019)A geographical patients based health information system2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/BIBM47256.2019.8983079(2300-2303)Online publication date: Nov-2019
https://doi.org/10.1109/BIBM47256.2019.8983079

Index Terms

A system for geoanalysis of clinical and geographical data
1. Information systems
  1. Information systems applications

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Published In

cover image ACM Conferences

HealthGIS '14: Proceedings of the Third ACM SIGSPATIAL International Workshop on the Use of GIS in Public Health

November 2014

74 pages

ISBN:9781450331364

DOI:10.1145/2676629

Editors:
Daniel W. Goldberg
Texas A&M University
,
Ori Gudes
Curtin University, Department of Spatial Sciences
,
Yaron Kanza
Jacobs Technion-Cornell Innovation Institute, Cornell Tech

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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New York, NY, United States

Publication History

Published: 04 November 2014

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SIGSPATIAL

SIGSPATIAL '14: 22nd SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 4, 2014

Texas, Dallas

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Cited By

Mollalo AHamidi BLenert LAlekseyenko A(2024)Application of Spatial Analysis on Electronic Health Records to Characterize Patient Phenotypes: Systematic ReviewJMIR Medical Informatics10.2196/5634312(e56343)Online publication date: 15-Oct-2024
https://doi.org/10.2196/56343
Tradigo GVizza PBrescia GGuzzi PVeltri P(2019)A geographical patients based health information system2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/BIBM47256.2019.8983079(2300-2303)Online publication date: Nov-2019
https://doi.org/10.1109/BIBM47256.2019.8983079

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