Universal Bilirubin Screening and Health Care Utilization
Bibliographic record
Abstract
OBJECTIVE: To evaluate the impact of the implementation of universal bilirubin screening on neonatal health care use in the context of a large jurisdiction with universal health insurance. METHODS: We conducted a population-based retrospective cohort study of all newborns discharged after birth between April 2003 and February 2011 from 42 hospitals that implemented universal bilirubin screening between July 2007 and June 2010 in Ontario, Canada. We surveyed hospitals to determine their screening implementation date. We used multiple linked administrative health data sets to measure phototherapy use, length of stay (LOS), jaundice-related emergency department visits, and jaundice-related readmissions. We modeled the relationship between universal bilirubin screening and outcomes using generalized estimating equations to account for clustering by hospital, underlying temporal trends, and important covariates. RESULTS: Screening was associated with an increase in phototherapy during hospitalization at birth (relative risk, 1.32; 95% confidence interval, 1.09-1.59) and a decrease in jaundice-related emergency department visits (relative risk, 0.79; 95% confidence interval, 0.64-0.96) but no statistically significant difference in phototherapy after discharge, LOS, or jaundice-related readmissions after accounting for preexisting temporal trends in health care service use and other patient sociodemographic and hospital characteristics. CONCLUSIONS: Universal bilirubin screening may not be associated with increased neonatal LOS or increased subsequent hospital use. Our findings are relevant for determining the resource implications of universal bilirubin screening in Ontario. They highlight the limitations in generalizability of previous research on health care utilization associated with similar programs and underline the importance of context-specific local evaluation of guideline implementation.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".