Is Medical Abortion Feasible in Primary Care? Regulating Mifepristone as a Normal Prescription: Effect on Abortion Workforce
Bibliographic record
Abstract
<h3>Context:</h3> Prior to 2017, most abortions in Canada were surgical and provided by a small number of physicians, mainly in urban areas. The medical abortion pill mifepristone first became available in Jan 2017. By Nov 2017 the regulations were globally unique; mifepristone was treated as a normal prescription drug. Both physicians and nurse-practitioners (NPs) can prescribe, and any pharmacist can dispense the pill for self-administration by the patient at a convenient time and place. We hypothesized the unique regulation of mifepristone would increase the size and distribution of the abortion workforce, particularly in primary care, and thus reduce rural-urban access disparity. <h3>Objective:</h3> We investigated trends for abortion rate, method, and workforce. <h3>Setting and Dataset:</h3> Ontario, including 40% of Canada’s residents, linked health administrative data. <h3>Study design and Analysis:</h3> We defined all abortions from Jan 1, 2012 to Mar 10, 2020, using practitioner visits, hospital, emergency and ambulatory care admissions, and dispensed pharmaceuticals. We used interrupted time series (ITS) analysis to compare temporal trends in abortion rate, method, and workforce composition. <h3>Population:</h3> All most responsible professionals providing abortion (MRP-A), defining one MRP-A per abortion. <h3>Intervention:</h3> We compared MRP-A prior to mifepristone (Jan 2012 to Jan 2017), to once it was available to prescribe normally (Nov 7, 2017 – Mar 10, 2020). <h3>Outcome Measures:</h3> Trends and rates for the number and characteristics of MRP-A: age, specialty, rural vs urban, abortion method, service volume and rate of providers per 1000 female residents aged 15-49 years (1Kfem15-49) per health region. <h3>Results:</h3> Among all 315,447 abortions we identified an MRP-A for 311,742 (98.3%). The abortion rate was stable 2012-2020, approximately 11 per 1Kfem15-49 while the percent as medical abortion increased from 2.2% to 31.4%. The rate of MRP per 1Kfem15-49 tripled. The rate of rural MRP-A increased seven-fold while the rate of rural physicians did not change. Mean age of MRP-As fell 6.9 years. By the end of the study period most MRP-As were GPs (66.5%) with 23.2% OBGyns and 9.1% NPs. <h3>Conclusions:</h3> When regulatory change supported primary care friendly approaches to medical abortion, it was rapidly implemented in both urban and rural primary care. We observed a tripling of the overall number of abortion providers, including a seven-fold increase in rural areas, while the abortion rate was stable.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".