Cost-Effectiveness Analysis of Predischarge Monitoring for Apnea of Prematurity
Bibliographic record
Abstract
OBJECTIVE: It is standard practice to defer discharge of premature infants until they have achieved a set number of days without experiencing apnea. The duration of this period, however, is highly variable across institutions, and there is scant literature on its effectiveness or value-for-money. Our objective was to establish the economic impact of varying durations of predischarge observation for apnea of prematurity. METHODS: Using computer simulation, we compared the alternatives of hospital monitoring for 1 to 10 days, after apparent cessation of apnea, with no monitoring and with the next longest period of monitoring. The daily probability of apnea requiring stimulation after a given number of apnea-free days was obtained from chart review of 216 infants, beginning on the day they attained both full feeds and temperature stability in an open crib. Baseline rates of survival or impairment, utilities for calculation of quality-adjusted life years (QALYs), outcomes for respiratory arrest at home, and long-run costs for neurodevelopmental impairment were derived from the literature. Hospital expenditures were obtained from itemized billing records for infants on each of the final 10 days of hospitalization and converted to costs using Medicare cost-to-charge ratios. Costs are reported in 2000 US dollars. RESULTS: For infants born at 24 to 26 weeks' gestation, each additional day of monitoring cost from $41000 per QALY saved for the first day to >$130000 per additional QALY gained for the tenth day. Cost-effectiveness was poorer for infants who were born at gestational ages >30 weeks. Results were sensitive to the proportion of charted apneas requiring stimulation that would actually progress, without intervention, to respiratory arrest. CONCLUSIONS: In this model, the cost-effectiveness of predischarge monitoring for apnea of prematurity declined significantly as the duration of monitoring was increased. Consideration should be given to alternative uses for resources in formulating neonatal discharge guidelines.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".