Impact of birth tourism on health care systems in Calgary, Alberta
Bibliographic record
Abstract
Abstract Background Birth tourism refers to non-resident women giving birth in a country outside of their own in order to obtain citizenship and/or healthcare for their newborns. We undertook a study to determine the extent of birth tourism in Calgary, the characteristics and rationale of this population, and the financial impact on the healthcare system. Methods A retrospective analysis of 102 women identified through a Central Triage system as birth tourists who delivered in Calgary between July 2019 and November 2020 was performed. Primary outcome measures were mode of delivery, length of hospital stay, complications or readmissions within 6 weeks for mother or baby, and NICU stay for baby. Results Birth Tourists were most commonly from Nigeria (24.5%). 77% of Birth Tourists stated that their primary reason to deliver their baby in Canada was for newborn Canadian citizenship. The average time from arrival in Calgary to the EDD was 87 days. Nine babies required stay in the neonatal intensive care unit (NICU) and 3 required admission to a non NICU hospital ward in first 6 weeks of life, including 2 sets of twins. The overall amount owed to Alberta Health Services for hospital fees for this time period is approximately $694 000.00. Conclusion Birth Tourists remain a complex and poorly studied group. The process of Central Triage did help support providers in standardizing process and documentation while ensuring that communication was consistent. These findings provide preliminary data to guide targeted public health and policy interventions for this population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".