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Cost Savings From Emergency Contraceptive Pills in Canada

2001· article· en· W4236738883 on OpenAlexaboutno aff
James Trussell, Ellen Wiebe, Tara Shochet, Édith Guilbert

Bibliographic record

VenueObstetrics and Gynecology · 2001
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEmergency contraceptionPillLiberian dollarFamily planningLevonorgestrelMedical emergencyUnintended pregnancyPopulationFinanceEnvironmental healthNursingResearch methodologyBusiness

Abstract

fetched live from OpenAlex

In Brief Objective To estimate cost savings from emergency contraceptive pills in Canada. Methods We modeled cost savings when a single emergency contraceptive treatment was provided after unprotected intercourse and when women were provided emergency contraceptive pills in advance. Results Each dollar spent on a single treatment saved $1.19–$2.35 (in Canadian currency), depending on the regimen and on assumptions about savings from costs avoided by preventing mistimed births. The dedicated products Preven (Shire Canada, Inc., Oakville, Ontario) and Plan B (Paladin Labs, Inc., Montreal) were cost-saving even under the least favorable assumption that mistimed births prevented today occur 2 years later. Each dollar spent on advance provision of Preven saved $1.24–$12.23, depending on the regular contraception method, on how consistently emergency contraception was used when needed, and on whether mistimed births were averted forever or simply delayed. Plan B was almost always cost-saving, although less so. Conclusion Emergency contraception was cost-saving whether provided when the emergency occurred or in advance to be used as needed. More extensive use of emergency contraception could save considerable medical costs by reducing unintended pregnancies. Emergency contraceptive pills saved medical care dollars in Canada.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.025
GPT teacher head0.277
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2001
Admission routes1
Has abstractyes

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