FAILURES IN AUDITS AND MEDICAL BOARDS IN THE EVALUATION FOR SPINE SURGERY AUTHORIZATION IN BRAZIL
Bibliographic record
Abstract
ABSTRACT Objective: The audit and medical board in surgeries focuses on the evaluation and adequacy of surgical procedures. The objective was to compare whether the evaluations were in line with the resolutions of the Federal Council of Medicine (CFM) and the standards of the National Health Agency (ANS) in conducting audits for the release of spinal surgical procedures. Methods: The research was conducted through document analysis of the results of audits and medical boards for the evaluation and release of surgical procedures in neurosurgery and spinal surgery. Results: A total of 55 audits were evaluated. The most frequent failures on the part of the audit were the denial of material in 49 audits (89.09%) and the denial of procedure in 46 audits (83.63%), which effectively vetoed the procedure. Conclusion: The failures identified in the audits and medical boards of surgeries can compromise the impartiality and quality of the audit process. These failures can lead to an increase in complaints from health insurance companies to other regulatory agencies. Level of Evidence IV; Economic and Decision Analysis.
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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 | 0.096 | 0.282 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".