Authors:
João Azevedo
1
;
Carlos Oliveira
1
;
Juliano Gaspar
2
and
Alberto Freitas
2
Affiliations:
1
CIDES – Department of Health Information and Decision Sciences, Portugal
;
2
CIDES – Department of Health Information and Decision Sciences, Faculty of Medicine and University of Porto, Portugal
Keyword(s):
Geographic information systems (GIS), Public health, Community health, Nursing, Family nursing, Primary care physicians.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Data Management and Quality
;
Data Manipulation
;
Data Visualization
;
Decision Support Systems
;
Design and Development Methodologies for Healthcare IT
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Medical and Nursing Informatics
;
Sensor Networks
Abstract:
Background: Family focused environment in Primary care is considered to be the future and help is required to implement new conceptualities. One theory consists in dividing patients accordingly to geographic clusters.
Aim: To study and implement methodologies for distribution of patients of a health unit, and develop a tool to aid in this process.
Methods: A health unit was selected to recollect and process bio-geographic data of patients. A manual division was executed and various methods were tested. An information system was developed in order to help divide and compare between manual and automatic.
Results: The original data contained a significant percentage of errors (25%). This led to the cross validation of addresses. This process took months. Only after, various patient division techniques could be applied. One showed itself as having the most advantages. A robust GIS system was developed.
Discussion: The analysis took a significant amount of time. The method of dividing
the patients proved itself appropriate to this situation, and could probably be applied in many urban locations. The obtained GIS provided time saving and better data comprehension.
Conclusion: Technologies in general and the system developed in particular can help patient allocation and represent a breakthrough in time-saving.
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