Provision of Postpartum Contraception Before and After the Start of the COVID-19 Pandemic in Maine
Bibliographic record
Abstract
OBJECTIVE: Preliminary findings from selected health systems revealed interruptions in reproductive health care services due to the COVID-19 pandemic. We estimated changes in postpartum contraceptive provision associated with the start of the COVID-19 pandemic in Maine. METHODS: We used the Maine Health Data Organization's All Payer Claims Database for deliveries from October 2015 through March 2021 (n = 45 916). Using an interrupted time-series analysis design, we estimated changes in provision rates of long-acting reversible contraception (LARC), permanent contraception, and moderately effective contraception within 3 and 60 days of delivery after the start of the COVID-19 pandemic. We performed 6- and 12-month analyses (April 2020-September 2020, April 2020-March 2021) as compared with the reference period (October 2015-March 2020). We used Poisson regression models to calculate level-change rate ratios (RRs) and 95% CIs. RESULTS: The 6-month analysis found that provision of LARC (RR = 1.89; 95% CI, 1.76-2.02) and moderately effective contraception (RR = 1.51; 95% CI, 1.33-1.72) within 3 days of delivery increased at the start of the COVID-19 pandemic, while provision of LARC (RR = 0.95; 95% CI, 0.93-0.97) and moderately effective contraception (RR = 1.08; 95% CI, 1.05-1.11) within 60 days of delivery was stable. Rates of provision of permanent contraception within 3 days (RR = 0.70; 95% CI, 0.63-0.78) and 60 days (RR = 0.71; 95% CI, 0.63-0.80) decreased. RRs from the 12-month analysis were generally attenuated. CONCLUSION: Disruptions in postpartum provision of permanent contraception occurred at the beginning of the COVID-19 pandemic in Maine. Public health policies should include guidance for contraceptive provision during public health emergencies and consider designating permanent contraception as a nonelective procedure.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".