Infertility insurance: What coverage exists for physician trainees?
Bibliographic record
Abstract
INTRODUCTION: We aimed to describe infertility insurance coverage provided to male and female fellows working at institutions that offer advanced infertility training. METHODS: Faculty and fellows working within U.S. and Canadian andrology or reproductive endocrinology and infertility (REI) programs were contacted and asked for a copy of their institutional health insurance summary of benefits. Documents were assessed for coverage of diagnosis and treatment, shared costs, and maximum lifetime coverage for infertility care. RESULTS: Insurance policies from 24 institutions were reviewed; 16 of 24 (66%) institutions covered costs related to the diagnosis of infertility. Six institutions (25%) offered coverage for diagnosis but not treatment. There were 15 (62.5%) institutions that offered some amount of coverage for the treatment of infertility, and the average lifetime maximum was $16 100. Only six of 24 (25%) plans explicitly described a covered male-specific treatment, which included sperm extraction (12.5%), varicocele repair (4.2%), and sperm cryopreservation (8.3%). CONCLUSIONS: For physician trainees, infertility insurance coverage is not universal, policies are not transparent, and treatment for male factor infertility is often omitted. With high costs of infertility treatment, variable insurance coverage, and debt and time constraints, residents and fellows are a particularly vulnerable population that may experience significant financial toxicity when faced with infertility.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".