En español
Objetivo: Cuidar selectivamente la salud identificando y georrefenciando la totalidad de la población, y no sólo para aquellos que demandan atención.
Métodos: Un total de 48 800 habitantes de Ensenada, Buenos Aires-Argentina fueron censados en aspectos socio-económico-sanitarios y sus datos georreferenciados en mapas catastrales (software Arc-GIS-ESRI-2002). Equipos de Salud (EDS) identificaron población en riesgo y efectuaron acciones de prevención. Variables como calidad de atención, conocimiento del área, efectividad, cantidad de actividades extramuros, participación comunitaria, y grado de satisfacción, fueron evaluadas pre y post-PANDELAS.
Resultados: PANDELAS permitió focalizar hogares con inconvenientes estructurales (ausencia de agua potable, cloacas); individuos vulnerables, con características especiales o enfermos con patología crónica. Se georreferenciaron niños < 1 año, embarazadas, individuos con controles incompletos. Con esta información se incrementaron estos controles en 300 %. El EDS triplicó el conocimiento del área e información de las necesidades de la población; sextuplicó actividades comunitarias extramuros e incrementó la participación comunitaria del 0,1 % al 3,9 %. La satisfacción comunitaria y del EDS con la labor realizada tuvo 85 % y 89 % respuestas favorables respectivamente.
Conclusiones: PANDELAS logró mayor compromiso del EDS para con su comunidad, planificando actividades en base a acciones preventivas e incrementando la cantidad de destinatarios de las mismas.
En inglés
Objective: Identifying families having health risks using GIS technology to plan health care action which would include the whole community and not just that part of the population demanding attention. Methods: 48 800 inhabitants from Ensenada county near Buenos Aires, Argentina were registered and questioned regarding socio-economic-sanitary aspects and their data was georeferenced to cadastral maps (using Arc-GIS-ESRI-2002 software). Health teams (HT) from each local health centre (LHC) were instructed in how to identify the population at risk and plan and carry out preventative health action using the software. Variables such as the quality of attention received, knowledge of the area and its inhabitants, the effectiveness of LHC action, the amount of extramural activities engaged in, community participation and the degree of satisfaction were evaluated pre- and post-PANDELAS. Results: PANDELAS led to focusing attention on homes having structural disadvantages (i.e. the absence of drinking water or drains), vulnerable inhabitants having special characteristics or sick people suffering from a chronic pathology. Children aged <1 year, patients affected by chronic disease, the aged, pregnant women and people lacking routine controls (such as Papanicolau, etc) were georeferenced. Controls were increased by 300 % based on this information. LHC tripled their knowledge of the area for which they were responsible and the needs of their target population; outdoor community activities increased 6-fold and community participation increased from 0,1 % to 3,9 %. LHC satisfaction and that of the community with the work done was reflected in 89 % and 85 % favourable answers, respectively. Conclusions: PANDELAS brought greater LHC commitment towards their community, planning their activities on the basis of preventative action and increasing accessibility to the heath care system.