A METHOD FOR ASSESSING THE IMPACT OF MASSIVE HEALTH EDUCATION: CASE STUDIES IN THE BRAZILIAN UNIFIED HEALTH SYSTEM
Evaluation method, Impact, Massive health education, AVASUS, Unified Health System, SUS, Case studies
Massive health education has been consolidated as an essential strategy for professional qualification in Brazil, especially in view of the structural challenges of the Unified Health System (SUS). In this context, the Virtual Learning Environment of the SUS (AVASUS) has become the main platform supporting continuing education in health, bringing together more than 1.3 million learners enrolled in over 400 courses organized into 12 learning tracks. The platform has played a strategic role in public health emergencies, such as the response to the syphilis epidemic, the COVID-19 pandemic, and the training of more than 11,000 physicians linked to the Mais Médicos Program. This study presents the development and validation of a method for evaluating the impact of massive health education within the context of Brazilian public health, using as a case study the educational offerings of the Virtual Learning Environment of the SUS (AVASUS). The proposed methodology integrates quantitative and qualitative analyses, encompassing epidemiological databases, educational records, and questionnaires applied to health professionals. The approach was applied in three case studies: (i) the response to the syphilis epidemic in Brazil; (ii) professional qualification in prison health; and (iii) the training of physicians for the Mais Médicos Program. The results show that massive education, when supported by robust virtual environments such as AVASUS, is capable of inducing changes in work processes, strengthening public policies, and producing measurable impacts on health indicators. It is therefore concluded that defining a systematic methodology for impact evaluation represents a strategic advance for continuing health education, contributing both to the management of the SUS and to the strengthening of public health policies based on scientific evidence.