A Cross-Sectional Analysis of the BC Children’s Hospital Cleft Palate Program Waitlist
Bibliographic record
Abstract
OBJECTIVE: A 2016 review of the BC Children's Hospital Cleft Palate - Craniofacial Program (CPP) revealed that one-third of patients met the program's care recommendations and half met the American Cleft Palate-Craniofacial Association guidelines. This study reviews patients on the CPP waitlist and determines median wait times and missed clinical assessments as well as identifies how wait times are influenced by medical complexity, specialized speech service needs, vulnerability, and distance from clinic. DESIGN: Cross-sectional. SETTING: BC Children's Hospital Cleft Palate-Craniofacial Program. PATIENTS: Five hundred seventy-six waitlisted patients. MAIN OUTCOME MEASURES: Additional wait time after recommended appointment date. Correlation of additional wait time with diagnosis, number of specialists required, speech services needed, vulnerability, and distance from the clinic. Missed plastic surgery, speech, and orthodontic assessments according to CPP team recommendations and ACPA guidelines. RESULTS: < .001). Vulnerability and distance from clinic did not affect wait times. Plastic surgery assessments were not available at the preschool and preteen time points for 45 (8%) patients, 355 (62%) patients were unable to access speech assessments, and 120 (21%) were unable to complete an orthodontic assessment. CONCLUSION: Patients wait up to an additional year to be seen by the CPP and miss speech, orthodontic, and surgical assessments at key developmental milestones. Additional resources are required to address these concerns.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".