APPLICATION OF GENERATIVE ARTIFICIAL INTELLIGENCE IN PRIMARY HEALTH CARE DATA ANALYSIS
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Abstract
Primary Health Care (PHC) plays a central role in the longitudinal follow-up of the population, especially for users with chronic conditions, requiring nurses to possess a continuous capacity to analyze epidemiological, care, and territorial indicators. In this context, generative Artificial Intelligence (AI) emerges as a promising tool to support care and managerial planning in Basic Health Units. This study aimed to analyze the potential of using ChatGPT as a tool to support the interpretation of public PHC indicators, exploring its applicability in the planning of nurses' work. This is an observational, documentary, cross-sectional, and quantitative study, carried out based on the analysis of public data from the municipality of Senador Alexandre Costa – MA, obtained from official SUS platforms. The indicators were organized and analyzed with the support of ChatGPT through structured prompts focused on epidemiological, care, and organizational analysis. The results demonstrated that AI was able to integrate territorial, epidemiological, and care indicators, assisting in identifying priorities related to the monitoring of chronic diseases, home visits, and care organization. It is concluded that ChatGPT shows potential as a complementary analytical and organizational support tool for PHC nurses, provided it is used in a critical, ethical, and supervised manner.
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