Cost-Effectiveness of Supplemental Donor Milk Versus Formula for Very Low Birth Weight Infants
Bibliographic record
Abstract
OBJECTIVES: To determine the cost-effectiveness of supplemental donor human milk (DHM) versus preterm formula (PTF) for very low birth weight (VLBW, <1500 g) infants from a societal perspective to 18 months’ corrected age. METHODS: This prospective cost-effectiveness analysis of 363 VLBW infants was conducted for a randomized control trial. Infants recruited from October 2010 to December 2012 were fed DHM or PTF whenever mother’s milk was unavailable. Formal health care costs for initial hospitalization and readmissions were obtained from standardized cost-accounting systems and physician fees. Informal and nonhealth care sector costs (eg, caregiver transportation, labor market earnings) were calculated from parent reports. RESULTS: Mean infant birth weight was 996 (SD, 272) grams. Incidence of necrotizing enterocolitis (NEC) differed between groups (all stages 3.9% DHM, 11.0% PTF; P = .01). Costs to 18 months did not differ with a mean (95% confidence interval) of 217 624 (197 697–237 551) and 217 245 (196 494–237 995) 2015 Canadian dollars in the DHM and PTF groups. Postdischarge costs were lower in the DHM (46 440 [40 648–52 233]) than PTF group (55 102 [48 269–61 934]) (P = .04), driven by parent lost wages. DHM cost an additional $5328 per case of averted NEC. CONCLUSIONS: In a high mother’s milk use setting, total costs from a societal perspective to 18 months of providing supplemental DHM versus PTF to VLBW infants did not differ, although postdischarge costs were lower in the DHM group. Although supplemental DHM was not cost-saving, it reduced NEC supporting its use over PTF.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".