Understanding the Limitations of Maternity Cost Studies: Why Context Matters
Bibliographic record
Abstract
Background: Limited, publicly available evidence exists to inform maternity care workforce planning in Manitoba as well as elsewhere in Canada. This manuscript offers a discussion about how context is critical when considering how cost, efficiency, and efficacy data are used.Methods: Our cost analysis of maternity care in Manitoba, Canada, focused exclusively on women with low- risk pregnancies from combined dates (2004/05 to 2008/09 and 2009/10 to 2012/13). Results: Although our cost analysis found that maternity care provided by family physicians had the lowest overall expected cost, and that highest effectiveness, measured by avoided neonatal intensive care unit (NICU) admissions, midwives had the lowest hospital costs and similar cost-effectiveness to other provider types. Interpretation: The context of how different maternity care professions are integrated into the system has a substantial impact on the assessment of overall cost. Caution must be used in interpreting these findings from significantly different models of care. The roles of providers are rarely articulated in cost study analyses to capture the breadth of services beyond “in-patient” costs. This article has been peer reviewed.
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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 | 0.419 | 0.699 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".