Quality improvement in radiography in a neonatal intensive care unit.
Bibliographic record
Abstract
OBJECTIVE: The primary objective of this study was to ensure that X-rays performed consistently adhere to established technological quality standards and are achieved without compromising patient care while minimizing exposure risks. The secondary objective was to evaluate whether educational sessions targeting areas deemed suboptimal would facilitate improvement. METHODS: A retrospective, 1-week review of all neonatal X-rays and documentation of clinical information on X-ray requisitions (n = 132) was completed in a tertiary care neonatal intensive care unit (NICU), by a single observer. Standards for X-ray evaluation were defined a priori based on radiographic principles and essential documented medical information for correct interpretation. Targeted areas for improvement were identified and addressed through brief educational sessions and printed pamphlets. The review was repeated after recommendations were implemented, 1 month (n = 93) and 1 year (n = 76) later. RESULTS: Improvements were evident in both the completion of X-ray requisitions and image quality. In particular, there was a statistically significant improvement in requisition legibility (P = 0.019), completeness of the medical history (P < 0.001), reduction in X-ray rotation (P < 0.001), collimation to the specific area of interest (P < 0.001), gonadal shielding (P < 0.001), and decrease in monitor leads or artifacts obscuring views (P < 0.001). These improvements were sustained both 1 month and 1 year following the educational sessions. CONCLUSION: A neonatal X-ray audit is a simple, effective way to evaluate radiographic technique and encourage provision of basic clinical information for diagnostic interpretation by radiologists and neonatologists. As well, structured, collaborative educational sessions between radiology and neonatology staff appear to be a successful and sustainable method to effect overall improvement.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".