Population perinatal substance use and an environmental scan of health services in British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: Substance use during pregnancy is underreported globally and there is limited data on its prevalence and the availability of supportive services. This study determined population perinatal substance use in British Columbia (BC) by region and examined the availability of clinical and community-based programs. METHODS: Using linked provincial health administrative data, we conducted a population-based retrospective cohort study including all BC residents accessing care for substance use (alcohol, opioids, stimulants, sedatives, and cannabis) within 12 months of first perinatal care record to delivery during 2016-2021. We also conducted an environmental scan to identify all programs offering perinatal care and substance use treatment/support in BC as of December 2022 and described program components by region. RESULTS: The population included 12,439 people with perinatal substance use with 13,814 linked livebirths during the study period. The incidence rate of perinatal substance use was nearly eight times higher in rural/remote Northern BC compared to the metropolitan Vancouver Coastal region (1044.2 vs. 131.3 per 100,000 population, respectively). We identified 29 related services (19 wrap-around programs, 8 supportive housing, and only 2 acute care programs). Residents outside of Metro Vancouver accounted for 60 % (N=1745) of people with perinatal substance use; however, these regions represented only 35 % of BC's specialized acute care and supportive housing beds (N=140). CONCLUSIONS: Expanding supports for perinatal substance use - particularly acute care and supportive housing within more rural/remote regions in BC - will be critical to address geographic inequities in access to perinatal care and improve health outcomes for pregnant people who use substances and their infants.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".