Objectives: To analyze the scientific production of primary care research in Latin American and Caribbean (LAC) countries from 1980 to 2024 and to provide recommendations for improvement.
Design: Observational, machine learning-based bibliometric study.
Data sources: Review and research articles indexed in the Web of Science database.
Selection of studies: Bibliometric analysis was performed on data from 33 LAC countries, retrieved from the Web of Science as of April 15, 2024.
Data extraction: For each record, data on the journal, year of publication, article title, abstract, keywords, authors, affiliations, countries, cited sources, cited first authors, and references were extracted for bibliometric and text mining analyses. We used a form of machine learning, Latent Dirichlet Allocation topic modeling, to identify the key topics of research.
Results: LAC countries contributed only 0.83% of the global literature on primary health care, with just 0.98% of this output comprising research and review articles. The majority of research originated from Brazil, Mexico, Colombia, and Chile, while many LAC countries produced little to no output. LAC countries frequently collaborated with the United States, Spain, Canada, and England. Research topics in the region predominantly focused on cancer, obesity, COVID-19, nutritional disorders, and food safety within the primary health care field.
Conclusions: The findings highlight significant potential for growth in primary health care research in LAC countries. Strengthening individual and collective strategies to build research capacity and fostering collaborations with global academic networks are recommended to enhance research output and impact.
Keywords: América Latina; Aprendizaje automático; Atención primaria de salud; Bibliometrics; Bibliometría; Evaluación de la investigación en salud; Health research evaluation; Latin America; Machine learning; Primary health care.
Copyright © 2025 The Author(s). Publicado por Elsevier España S.L.U. All rights reserved.
