Bibliographic record
Abstract
BACKGROUND: Socialized health systems face fiscal constraints due to a limited supply of resources and few reliable ways to control patient demand. Some form of prioritization must occur as to what services to offer and which programs to fund. A data-driven approach to decision making that incorporates outcomes, including safety and quality, in the setting of fiscal prudence is required. A value model championed by Michael Porter encompasses these parameters, in which value is defined as outcomes divided by cost. OBJECTIVES: To assess ambulatory cleft lip surgery from a quality and safety perspective, and to assess the costs associated with ambulatory cleft lip surgery in North America. Conclusions will be drawn as to how the overall value of cleft lip surgery may be enhanced. METHODS: A value analysis of published articles related to ambulatory cleft lip repair over the past 30 years was performed to determine what percentage of patients would be candidates for ambulatory cleft lip repair from a quality and safety perspective. An economic model was constructed based on costs associated with the inpatient stay related to cleft lip repair. RESULTS: On analysis of the published reports in the literature, a minority (28%) of patients are currently discharged in an ambulatory fashion following cleft lip repair. Further analysis suggests that 88.9% of patients would be safe candidates for same-day discharge. From an economic perspective, the mean cost per patient for the overnight admission component of ambulatory cleft surgery to the health care system in the United States was USD$2,390 and $1,800 in Canada. CONCLUSIONS: The present analysis reviewed germane publications over a 30-year period, ultimately suggesting that ambulatory cleft lip surgery results in preservation of quality and safety metrics for most patients. The financial model illustrates a potential cost saving through the adoption of such a practice change. For appropriately selected patients, ambulatory cleft surgery enhances overall health care value.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".