Design of a geospatial model applied to Health management
ABSTRACT Objective: To identify geographically the beneficiaries categorized as prone to Type 2 Diabetes Mellitus, using the recognition of patterns in a database of a health plan operator, through data mining. Method: The following steps were developed: the initial step, the information survey. D...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Associação Brasileira de Enfermagem
2019-04-01
|
Series: | Revista Brasileira de Enfermagem |
Subjects: | |
Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-71672019000200420&lng=en&tlng=en |
id |
doaj-02895ad66f3b427b99d1266d4f7fada5 |
---|---|
record_format |
Article |
spelling |
doaj-02895ad66f3b427b99d1266d4f7fada52020-11-25T01:55:14ZengAssociação Brasileira de EnfermagemRevista Brasileira de Enfermagem1984-04462019-04-0172242042610.1590/0034-7167-2018-0589S0034-71672019000200420Design of a geospatial model applied to Health managementMarcelo Rosano DallagassaFranciele IachecenDeborah Ribeiro CarvalhoSergio Ossamu IoshiiABSTRACT Objective: To identify geographically the beneficiaries categorized as prone to Type 2 Diabetes Mellitus, using the recognition of patterns in a database of a health plan operator, through data mining. Method: The following steps were developed: the initial step, the information survey. Development, construction of the process of extraction, transformation, and loading of the database. Deployment, presentation of the geographical information through a georeferencing tool. Results: As a result, the mapping of Paraná according to its health care network and the concentration of Type 2 Diabetes Mellitus is presented, enabling the identification of cause-and-effect relationships. Conclusion: It is concluded that the analysis of georeferenced information, linked to health information obtained through the data mining technique, can be an excellent tool for the health management of a health plan operator, contributing to the decision-making process in Health.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-71672019000200420&lng=en&tlng=enAtención a la SaludMinería de DatosMapeo GeográficoSalud SuplementariaEnfermedades crónicas |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Marcelo Rosano Dallagassa Franciele Iachecen Deborah Ribeiro Carvalho Sergio Ossamu Ioshii |
spellingShingle |
Marcelo Rosano Dallagassa Franciele Iachecen Deborah Ribeiro Carvalho Sergio Ossamu Ioshii Design of a geospatial model applied to Health management Revista Brasileira de Enfermagem Atención a la Salud Minería de Datos Mapeo Geográfico Salud Suplementaria Enfermedades crónicas |
author_facet |
Marcelo Rosano Dallagassa Franciele Iachecen Deborah Ribeiro Carvalho Sergio Ossamu Ioshii |
author_sort |
Marcelo Rosano Dallagassa |
title |
Design of a geospatial model applied to Health management |
title_short |
Design of a geospatial model applied to Health management |
title_full |
Design of a geospatial model applied to Health management |
title_fullStr |
Design of a geospatial model applied to Health management |
title_full_unstemmed |
Design of a geospatial model applied to Health management |
title_sort |
design of a geospatial model applied to health management |
publisher |
Associação Brasileira de Enfermagem |
series |
Revista Brasileira de Enfermagem |
issn |
1984-0446 |
publishDate |
2019-04-01 |
description |
ABSTRACT Objective: To identify geographically the beneficiaries categorized as prone to Type 2 Diabetes Mellitus, using the recognition of patterns in a database of a health plan operator, through data mining. Method: The following steps were developed: the initial step, the information survey. Development, construction of the process of extraction, transformation, and loading of the database. Deployment, presentation of the geographical information through a georeferencing tool. Results: As a result, the mapping of Paraná according to its health care network and the concentration of Type 2 Diabetes Mellitus is presented, enabling the identification of cause-and-effect relationships. Conclusion: It is concluded that the analysis of georeferenced information, linked to health information obtained through the data mining technique, can be an excellent tool for the health management of a health plan operator, contributing to the decision-making process in Health. |
topic |
Atención a la Salud Minería de Datos Mapeo Geográfico Salud Suplementaria Enfermedades crónicas |
url |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-71672019000200420&lng=en&tlng=en |
work_keys_str_mv |
AT marcelorosanodallagassa designofageospatialmodelappliedtohealthmanagement AT francieleiachecen designofageospatialmodelappliedtohealthmanagement AT deborahribeirocarvalho designofageospatialmodelappliedtohealthmanagement AT sergioossamuioshii designofageospatialmodelappliedtohealthmanagement |
_version_ |
1724984349959389184 |