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Evaluation and Use of Registry Data in a GIS Analysis of Diabetes

OBJECTIVES: to evaluate registry data routinely collected by the Chronic Disease Electronic Management System (CDEMS) in the monitoring of type 2 diabetes mellitus (T2DM) in the Eastern half of the island and use the data to describe the spatial epidemiological patterns of T2DM. DESIGN AND METHOD: T...

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Autores principales: Kameel, Mungrue, Steven, Sankar, Aleem, Kamalodeen, Dayna, Lalchansingh, Demeytri, Ramnarace, Shanala, Samodee, Craig, Sookhan, Navin, Sookar, Kristal, Sooknanan, Leah, St.George, Deonath, Suruj
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AIMS Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690238/
https://www.ncbi.nlm.nih.gov/pubmed/29546113
http://dx.doi.org/10.3934/publichealth.2015.3.318
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author Kameel, Mungrue
Steven, Sankar
Aleem, Kamalodeen
Dayna, Lalchansingh
Demeytri, Ramnarace
Shanala, Samodee
Craig, Sookhan
Navin, Sookar
Kristal, Sooknanan
Leah, St.George
Deonath, Suruj
author_facet Kameel, Mungrue
Steven, Sankar
Aleem, Kamalodeen
Dayna, Lalchansingh
Demeytri, Ramnarace
Shanala, Samodee
Craig, Sookhan
Navin, Sookar
Kristal, Sooknanan
Leah, St.George
Deonath, Suruj
author_sort Kameel, Mungrue
collection PubMed
description OBJECTIVES: to evaluate registry data routinely collected by the Chronic Disease Electronic Management System (CDEMS) in the monitoring of type 2 diabetes mellitus (T2DM) in the Eastern half of the island and use the data to describe the spatial epidemiological patterns of T2DM. DESIGN AND METHOD: The starting point was access and retrival of all exsisting data on the diabetes registry. This data was subsequently validated using handwritten medical records. Several clinical indicators were selected to evaluate the registry. The address of each patient was extracted and georeferenced using ArcGIS 10.0 and several maps were created. RESULTS: The registry had data for thirteen (13) out of the sixteen (16) health facilities. We found that less than 15 percent of all patients actually had diabetic indicator tests done according to World Health Organization (WHO) standards. The overall prevalence of T2DM was 20.8 per 1000 population. The highest prevalence of diabetes occurred at the northeastern tip of the island. In addition 57.58% of patients with T2DM resided inland and 40.75% of patients residing on the coastal areas. CONCLUSIONS: In conclusion, we provide evidence that the data collected by the diabetes registry although lacking in many areas was adequate for spatial epidemiological analysis.
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spelling pubmed-56902382018-03-15 Evaluation and Use of Registry Data in a GIS Analysis of Diabetes Kameel, Mungrue Steven, Sankar Aleem, Kamalodeen Dayna, Lalchansingh Demeytri, Ramnarace Shanala, Samodee Craig, Sookhan Navin, Sookar Kristal, Sooknanan Leah, St.George Deonath, Suruj AIMS Public Health Research Article OBJECTIVES: to evaluate registry data routinely collected by the Chronic Disease Electronic Management System (CDEMS) in the monitoring of type 2 diabetes mellitus (T2DM) in the Eastern half of the island and use the data to describe the spatial epidemiological patterns of T2DM. DESIGN AND METHOD: The starting point was access and retrival of all exsisting data on the diabetes registry. This data was subsequently validated using handwritten medical records. Several clinical indicators were selected to evaluate the registry. The address of each patient was extracted and georeferenced using ArcGIS 10.0 and several maps were created. RESULTS: The registry had data for thirteen (13) out of the sixteen (16) health facilities. We found that less than 15 percent of all patients actually had diabetic indicator tests done according to World Health Organization (WHO) standards. The overall prevalence of T2DM was 20.8 per 1000 population. The highest prevalence of diabetes occurred at the northeastern tip of the island. In addition 57.58% of patients with T2DM resided inland and 40.75% of patients residing on the coastal areas. CONCLUSIONS: In conclusion, we provide evidence that the data collected by the diabetes registry although lacking in many areas was adequate for spatial epidemiological analysis. AIMS Press 2015-07-23 /pmc/articles/PMC5690238/ /pubmed/29546113 http://dx.doi.org/10.3934/publichealth.2015.3.318 Text en © 2015 Kory J. Allred et al., licensee AIMS Press This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
spellingShingle Research Article
Kameel, Mungrue
Steven, Sankar
Aleem, Kamalodeen
Dayna, Lalchansingh
Demeytri, Ramnarace
Shanala, Samodee
Craig, Sookhan
Navin, Sookar
Kristal, Sooknanan
Leah, St.George
Deonath, Suruj
Evaluation and Use of Registry Data in a GIS Analysis of Diabetes
title Evaluation and Use of Registry Data in a GIS Analysis of Diabetes
title_full Evaluation and Use of Registry Data in a GIS Analysis of Diabetes
title_fullStr Evaluation and Use of Registry Data in a GIS Analysis of Diabetes
title_full_unstemmed Evaluation and Use of Registry Data in a GIS Analysis of Diabetes
title_short Evaluation and Use of Registry Data in a GIS Analysis of Diabetes
title_sort evaluation and use of registry data in a gis analysis of diabetes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690238/
https://www.ncbi.nlm.nih.gov/pubmed/29546113
http://dx.doi.org/10.3934/publichealth.2015.3.318
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