Standardization of Radiologic Procedures for Pediatric Videofluoroscopic Swallow Studies: A Service-based Quality Improvement Initiative
Bibliographic record
Abstract
INTRODUCTION: The videofluoroscopic swallow study (VFSS) remains the primary method to evaluate swallowing function in infants and children. However, limited standards exist to guide the image acquisition during pediatric VFSSs, leading to inadequate images, variable assessment quality, and potential for suboptimal diagnostic accuracy. The goal of this quality improvement project was to standardize the radiological procedure for radiologists at our institution. METHODS: A multidisciplinary team of project leaders established 3 imaging standards to target (magnification, the field of view, and pulse repetition rate), based on the best available evidence. The team used the Institute for Healthcare Improvement's Model for Improvement to guide the project, identified key drivers, and implemented specific interventions. Project leaders observed a total of 170 VFSS examinations, performed by radiology faculty, fellows, and residents over 24 months. The primary outcome for this project was physician compliance with 3 established imaging standards: field of view, magnification, and pulse repetition rate. Project leaders collected data without the radiologists' knowledge, and also recorded average radiation exposure as a balancing measure during this process. RESULTS: At baseline, compliance with all 3 criteria was 20%. Following interventions designed to improve radiologist performance with the 3 identified standards, the compliance rate reached 100% for the last 50 recorded VFSSs. During this same time, there was no meaningful increase in average radiation exposure compared with the 6 months before the implementation of this project. CONCLUSIONS: Compliance with standardized image acquisition of VFSSs can be accomplished using a systematic quality improvement protocol targeting simple, inexpensive interventions.
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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 | 0.104 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".