Artículos de revistas
Latin American Collaborative Study of Congenital Malformations (ECLAMC): a model for health collaborative studies
Fecha
2014-01Registro en:
Gili, Juan Antonio; Castilla, Eduardo Enrique; Poletta, Fernando Adrián; Latin American Collaborative Study of Congenital Malformations (ECLAMC): a model for health collaborative studies; Karger; Public Health Genomics; 17; 2; 1-2014; 61-67
1662-4246
1662-8063
CONICET Digital
CONICET
Autor
Poletta, Fernando Adrián
Gili, Juan Antonio
Castilla, Eduardo Enrique
Resumen
BACKGROUND: For the past 46 years, the Latin American Collaborative Study of Congenital Malformations (ECLAMC) has successfully dealt with a low-priority health problem in the region, using installed capacity and low technological complexity, aimed at research rather than health information and action. Originally planned for a city, but rapidly expanded to whole South America and beyond, involving more than 200 hospitals from 12 Latin American countries: Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, Paraguay, Peru, Uruguay, and Venezuela. In the present study, the ECLAMC structure is shown as a social network with the aim to facilitate its transfer.
METHODS: Data from 261 hospitals from 12 countries that have participated in the ECLAMC program during 1967-2012 were included in this work. Three types of data were evaluated for network analysis: data collection, participation in special research projects, and co-authorships. Indicators as total size (number of nodes), path count, density, degree centrality, closeness centrality, and betweenness centrality were estimated to compare the structural characteristics and attributes of the networks.
RESULTS: The ECLAMC networks can be defined, from the social network analysis point of view, as a centralized, unimodal, afferent network for data collection; as a decentralized, bimodal, interactive network for special projects; and co-authorship of published papers. Conclusions: The key elements in the ECLAMC program are: collaboration between motivated expert people, voluntarily accepting the same research protocol, with a sense of belonging to the working-team, based on mutual trustfulness within a transparent framework, with explicit rules, aimed at producing data of internationally competitive quality. This example is proposed for future health programs, mainly in low- and middle-income areas.