Is More Neonatal Intensive Care Always Better? Insights From a Cross-National Comparison of Reproductive Care
Bibliographic record
Abstract
BACKGROUND: Despite high per capita health care expenditure, the United States has crude infant survival rates that are lower than similarly developed nations. Although differences in vital recording and socioeconomic risk have been studied, a systematic, cross-national comparison of perinatal health care systems is lacking. OBJECTIVE: To characterize systems of reproductive care for the United States, Australia, Canada, and the United Kingdom, including a detailed analysis of neonatal intensive care and mortality. DESIGN/METHODS: Comparison of selected indicators of reproductive care and mortality from 1993-2000 through a systematic review of journal and government publications and structured interviews of leaders in perinatal and neonatal care. RESULTS: Compared with the other 3 countries, the United States has more neonatal intensive care resources yet provides proportionately less support for preconception and prenatal care. Unlike the United States, the other countries provided free family planning services and prenatal and perinatal physician care, and the United Kingdom and Australia paid for all contraception. The United States has high neonatal intensive care capacity, with 6.1 neonatologists per 10 000 live births; Australia, 3.7; Canada, 3.3; and the United Kingdom, 2.7. For intensive care beds, the United States has 3.3 per 10 000 live births; Australia and Canada, 2.6; and the United Kingdom, 0.67. Greater neonatal intensive care resources were not consistently associated with lower birth weight-specific mortality. The relative risk (United States as reference) of neonatal mortality for infants <1000 g was 0.84 for Australia, 1.12 for Canada, and 0.99 for the United Kingdom; for 1000 to 2499 g infants, the relative risk was 0.97 for Australia, 1.26 for Canada, and 0.95 for the United Kingdom. As reported elsewhere, low birth weight rates were notably higher in the United States, partially explaining the high crude mortality rates. CONCLUSIONS: The United States has significantly greater neonatal intensive care resources per capita, compared with 3 other developed countries, without having consistently better birth weight-specific mortality. Despite low birth weight rates that exceed other countries, the United States has proportionately more providers per low birth weight infant, but offers less extensive preconception and prenatal services. This study questions the effectiveness of the current distribution of US reproductive care resources and its emphasis on neonatal intensive care.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".