Desempenho da Atenção Primária à Saúde segundo o instrumento PCATool: uma revisão sistemática
Bibliographic record
Abstract
This study aims to analyze studies that evaluated the performance of Primary Health Care (PHC) services by using the Primary Care Assessment Tool (PCATool) under a worldwide user perspective. This is a systematic review that implemented the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) model, from the following databases: Lilacs, Medline, SciELO, PubMed and the Coordination for the Improvement of Higher Education Personnel (CAPES) Journals Website, using descriptors Primary Care Assessment Tool and PCATool. Considering inclusion and exclusion criteria, we analyzed 22 research papers published from 2007 to 2015. The best-evaluated attributes were cultural competence, first contact use and longitudinality. On the other hand, the worst evaluated were first contact accessibility, family orientation, community orientation and comprehensiveness. Most of the health services evaluated were from Brazil, applied to "traditional" primary care clinic (UBS) and the Health Family Strategy (FHS). Services evaluated should strengthen structure and process components to achieve a better performance in PHC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.071 | 0.142 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.026 | 0.029 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".