Brazilian Development Bank

Introduction: Structured clinical records are essential for ensuring the quality and continuity of palliative care, particularly in socially vulnerable contexts. Existing digital systems rarely capture psychosocial or subjective data, limiting interdisciplinary collaboration and person-centered care planning. Objective: To describe the development and preliminary usability assessment of Prontuário Compassivo , a Brazilian digital platform designed to support clinical documentation and coordination of community-based palliative care. Method: This methodological study was conducted between 2022 and 2025, adopting an agile development approach grounded in the Scrum framework and guided by user-centered design principles. The platform was implemented as a responsive web system with secure authentication mechanisms, interoperability through REST (Representational State Transfer) application programming interfaces, and modules integrating standardized palliative care assessment tools. Usability assessment was conducted prospectively between February 2024 and January 2025 within the Favela Compassiva project in Rio de Janeiro. Data collection included direct observation of home visits, field diaries, and interdisciplinary meetings documenting professionals’ interactions with the platform. Usability aspects explored included learnability, ease of use, navigation clarity, and integration into routine clinical workflows. Results: By January 2025, the system had generated 520 clinical records used by 71 interdisciplinary health professionals involved in community-based palliative care. Three analytical categories emerged: (1) routine use, (2) challenges related to features and user diversity, and (3) contextual adjustments. These findings indicate that the platform became embedded in routine home-based care activities, although its use varied depending on users’ familiarity with digital tools. Iterative refinements included simplified and extended versions, reorganized navigation flows, and automated referral features. Conclusion: Prontuário Compassivo demonstrated technical feasibility, contextual usability, and adaptability in resource-limited environments. Its integration of interprofessional documentation, artificial intelligence resources, and interoperability positions it as a promising digital health solution for improving documentation, communication, and continuity of palliative care in socially vulnerable settings. Future studies should conduct standardized usability testing and evaluate the platform’s impact on clinical outcomes.

Artificial intelligence (AI) has become a key enabling technology for business organisations, increasingly embedded in production systems and decision-making workflows. AI models and tools in these settings must satisfy diverse requirements, such as accuracy, traceability, explainability, fairness, and trust, while meeting compliance obligations, service-level agreements, and governance frameworks. However, the non-deterministic and evolving nature of modern AI models challenges traditional validation approaches based primarily on quantitative metrics. This paper investigates how techniques from empirical software engineering, particularly expert opinions and peer review, can support AI-enabled systems engineering. The paper presents an experience report grounded in a literature review and an experiment. The experiment is based on a precisely specified, complex problem that analyses the responses of contemporary AI models when prompted with the given problem. It examines how expert judgment and peer review can improve the plausibility and correctness of model outputs. This study proposes a lifecycle model that treats problem and ground-truth specifications, expert judgments, and review rationales as first-class artefacts. The paper concludes by discussing challenges, limitations, and opportunities for incorporating these techniques into AI engineering, particularly for next-generation models and tools.

Contract management in public institutions demands rigorous oversight of service execution and financial compliance, posing operational challenges for managers. This study introduces an LLM question-and-answer (Q A) system to retrieve structured and unstructured contract information. The solution integrates text-to-SQL extraction for data querying, prompt engineering for response standardization, and intelligent agents for context-aware answer generation. Implemented as a containerized Python application and combining generative AI with customized LLMs, the system overcomes the limitations of traditional contract management systems. The results demonstrate an effective architecture for deploying a Q A system to address one of the main challenges in understanding administrative contracts and their specifics.

Resumo Apesar do uso disseminado da repetência escolar na América Latina, seu impacto sobre os resultados acadêmicos segue sendo objeto de debate. Este artigo examina os efeitos da repetência utilizando um conjunto de dados longitudinais em nível de aluno (2012-2017) do município do Rio de Janeiro, a segunda maior rede municipal de ensino do Brasil. Aplicando um modelo de diferenças em diferenças com efeitos fixos para o aluno, encontramos que a repetência melhora significativamente o desempenho acadêmico de curto prazo, com resultados consistentes em diversas verificações de robustez. Nossa análise sugere que essa melhoria se deve, em parte, ao medo da repetência e ao suporte adicional oferecido aos alunos em risco de repetição. No entanto, o impacto da repetência vai além desses fatores, indicando seu papel como intervenção direta na melhoria da aprendizagem. Este estudo contribui para a literatura sobre repetência ao oferecer evidências em um contexto de país em desenvolvimento, destacando os benefícios potenciais e a complexidade dessa política amplamente debatida. Embora a repetência incentive ganhos acadêmicos de curto prazo, seus efeitos de longo prazo e custos associados merecem maior consideração.

Limited access to education from economic hardship and remote locations leads many rural students to migrate for better schooling, scholarships, and learning facilities. This study examines how regional students adapt at Widyalaya Wira Dharma Palu Main High School and identifies the factors that help this process. The research uses a descriptive, qualitative method, with the researcher as the main instrument. Data was gathered through observation, documentation, and interviews with ten students from Central Sulawesi villages. The study finds adaptation happens in three phases: first, students experience culture shock and adjust to new surroundings; second, they seek social support and build self-identity; third, they reach acceptance and social integration, shown through comfort in school and dormitory life. Teachers, peers, and extracurricular activities support this process. Obstacles include differences in daily habits, language, and limited opportunities outside school. These findings will inform mentoring programs to improve student experiences and academic success.