Aplicações de Business Intelligence na Saúde: Revisão de Literatura
Bibliographic record
Abstract
Este artigo revisa a literatura publicada entre 2009 e 2014 sobre aplicacao de Business Intelligence (BI) na saude, indexada nas bases de dados Scopus, PubMed, Bireme, Web of Science e Google Scholar. A busca pelos descritores “Business Intelligence” e “saude” e a sua combinacao retornou 339 artigos, sendo selecionados 17 adequados aos criterios estabelecidos. Os artigos foram classificados nas tematicas “cuidados em saude” e “gestao”. Nao houve predominância de tematicas. O ano 2010 foi o de maior numero de publicacoes e Portugal, Canada e EUA os paises de origem da maior parte dos autores. Com as praticas de BI a estruturacao e analise da informacao possibilitou o monitoramento do desempenho do ponto de vista assistencial e gerencial. Confirmou-se que as praticas de Business Intelligence podem ser aplicadas no setor de saude, com valorizacao das acoes gerenciais estrategicas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".