Elaboração e validação de conteúdo de uma matriz de competências em vigilância em saúde para profissionais da atenção primária à saúde

Abstract

Introduction: The integration between Health Surveillance (HS) and Primary Health Care (PHC) stands out as a key strategy for strengthening the Brazilian Unified Health System (SUS), requiring professionals trained in specific competencies that articulate surveillance actions within the territory. However, there is a lack of validated tools to guide the identification and development of these competencies in the context of PHC. Objective: To develop and validate a competency matrix in Health Surveillance for use by PHC professionals. Materials and Methods: This is a methodological study, applying the Delphi technique for content validation. The matrix was developed based on a previously conducted scoping review and the researchers’ expertise, encompassing three competency domains: knowledge, skills, and attitudes (KSA). After linguistic review, the matrix was evaluated by 22 experts from the four HS areas. Items were assessed for clarity and relevance using a five-point Likert scale, with results analyzed through the Content Validity Index (CVI) and modified Kappa coefficient (K*), across three rounds to reach consensus. Results: A total of 22 experts with broad academic and technical experience participated. The final matrix included 88 items, organized into five HS domains and its four areas (epidemiological, sanitary, environmental, and workers’ health surveillance). The CVI for clarity ranged from 0.80 to 0.96, and for relevance from 0.94 to 1.0. The overall CVI of the matrix was 0.91 for clarity and 0.97 for relevance, showing excellent agreement among reviewers. The process involved creating, excluding, and reformulating items, highlighting theoretical and linguistic refinement of the final version. Conclusion: The validated matrix is a robust instrument to support training, evaluation, and workforce management in PHC, enhancing its connection with HS. After undergoing future experimental and statistical procedures, this matrix may support more effective, interdisciplinary, and territorially-based actions, contributing to a more integrated and responsive SUS that meets the population’s needs.