The effects of early pregnancy loss on health outcomes and health care utilization and costs
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effects of early pregnancy loss on subsequent health care use and costs. DATA SOURCES: Linked administrative health databases from Manitoba, Canada. STUDY DESIGN: This was a population-based cohort study. The exposure of interest was first recorded ectopic pregnancy or miscarriage (EPM). Outcomes included visits to all ambulatory care providers, family physicians (FPs), specialists, and hospitals, as well as the costs associated with these visits. We also assessed the impact of EPM on a global measure of health service utilization and the incidence and costs of psychotropic medications. DATA COLLECTION/EXTRACTION METHODS: We identified women who experienced their first recorded loss (EPM) from 2003-2012 and created a propensity score model to match these women to women who experienced a live birth, with outcome measures available through 31 December 2014. We used a difference in differences approach with multivariable negative binomial models and generalized estimating equations (GEE) to assess the impact of EPM on the aforementioned health care utilization indicators. PRINCIPAL FINDINGS: EPM was associated with a short-term increase in visits to, and costs associated with, certain ambulatory care providers. These findings were driven in large part by increased visits/costs to FPs (rate difference [RD]: $19.92 [95% CI: $16.33, $23.51]) and obstetrician-gynecologists (OB-GYNs) (RD $9.41 [95% CI: $8.42, $10.40]) in the year immediately following the loss, excluding care associated with the loss itself. We also detected an increase in hospital stays and costs and a decrease in the use of psychotropic medications relative to matched controls. CONCLUSION: Pregnancy loss may lead to subsequent increases in certain types of health care utilization. While the absolute costs associated with post-EPM care are relatively small, the observed patterns of service utilization are informative for providers and policy makers seeking to support women following a loss.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".