Background and Objective: Health services management faces increasing complexity, particularly in developing countries such as Brazil. Digital tools play a central role in optimizing health service operations, yet synthesized evidence on manager-focused applications remains limited. This study aimed to survey digital innovations for management within the Brazilian context. Methods: We systematically reviewed the complete proceedings of the Brazilian Symposium on Computing Applied to Health (SBCAS) from 2001 to 2024, identifying 26 studies that met eligibility criteria based on managerial relevance. Results: Applications identified predominantly addressed hospital management (e.g., resource scheduling and process optimization) and public health surveillance (e.g., disease prediction and monitoring), employing technologies such as machine learning and simulation. These tools primarily leveraged structured administrative data from national health information systems, reflecting existing data infrastructure capabilities. The reported implications suggest improvements in decision-making through optimized resource allocation (e.g., ICU beds and staffing), streamlined operational processes (e.g., bottleneck identification), enhanced planning and monitoring capabilities (e.g., endemic disease control and telemonitoring programs), and more timely, targeted public health surveillance (e.g., georeferenced analysis). Conclusions: The identified research aligns with global digital health trends but is also tailored to the complex realities of the healthcare system. Despite significant technical advancements, these digital solutions predominantly remain at the prototype stage, highlighting a gap between academic innovation and real-world deployment. Realizing the benefits of these tools will require a concerted effort to move beyond technical validation, focusing on implementation science, supportive policies, and strategic partnerships to integrate these solutions into managerial practice.
Bellei et al. (2025) studied this question.