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Geographical information system (GIS) as a new tool to evaluate epidemiology based on spatial analysis and clinical outcomes in acromegaly

Geographical information systems (GIS) have emerged as a group of innovative software components useful for projects in epidemiology and planning in Health Care System. This is an original study to investigate environmental and geographical influences on epidemiology of acromegaly in Brazil. We aime...

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Detalles Bibliográficos
Autores principales: Naves, Luciana Ansaneli, Porto, Lara Benigno, Rosa, João Willy Corrêa, Casulari, Luiz Augusto, Rosa, José Wilson Corrêa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4297616/
https://www.ncbi.nlm.nih.gov/pubmed/24368684
http://dx.doi.org/10.1007/s11102-013-0548-3
Descripción
Sumario:Geographical information systems (GIS) have emerged as a group of innovative software components useful for projects in epidemiology and planning in Health Care System. This is an original study to investigate environmental and geographical influences on epidemiology of acromegaly in Brazil. We aimed to validate a method to link an acromegaly registry with a GIS mapping program, to describe the spatial distribution of patients, to identify disease clusters and to evaluate if the access to Health Care could influence the outcome of the disease. Clinical data from 112 consecutive patients were collected and home addresses were plotted in the GIS software for spatial analysis. The buffer spatial distribution of patients living in Brasilia showed that 38.1 % lived from 0.33 to 8.66 km, 17.7 % from 8.67 to 18.06 km, 22.2 % from 18.07 to 25.67 km and 22 % from 25.68 to 36.70 km distant to the Reference Medical Center (RMC), and no unexpected clusters were identified. Migration of 26 patients from 11 others cities in different regions of the country was observed. Most of patients (64 %) with adenomas bigger than 25 mm lived more than 20 km away from RMC, but no significant correlation between the distance from patient’s home to the RMC and tumor diameter (r = 0.45 p = 0.20) nor for delay in diagnosis (r = 0.43 p = 0.30) was found. The geographical distribution of diagnosed cases did not impact in the latency of diagnosis or tumor size but the recognition of significant migration denotes that improvements in the medical assistance network are needed.