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The Gaps · translation
The Translation Gap
A finding can be settled, published, and written into guidance, and still take years to reach the exam room. No new product is required and no new trial is needed. The distance between what the literature knows about sex-based differences and what happens at the point of care is its own gap, with its own causes, and its own set of people working to close it.
what the effect is
The effect is measurable in individual cases and, so far, unmeasured in aggregate. Zolpidem was approved in 1992 and the FDA halved the recommended dose for women in 2013, a 21-year span; six months after that very public action, 15.5% of new prescriptions to women followed the lower dose, up from 10.9% before it. High-sensitivity troponin with a sex-specific threshold doubles the proportion of women diagnosed with myocardial infarction, from 11% to 22%, and there is no published figure for how many US laboratories report sex-specific cut-offs. Cardiac rehabilitation is a long-standing Class I recommendation that women benefit from more than men, and women’s enrollment runs 36% below men’s. What is worth saying plainly is that nobody has yet measured whether sex-specific findings travel more slowly than findings in general. The studies that exist count whether sex-specific guidance is present in guidelines, not how long it took to arrive. Building that measurement is one of the things this field still needs, and it is the kind of work the Hub’s database is positioned to support.
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Source: FDA zolpidem dosing revision, 2013, with the North Carolina pharmacy cohort; sex-specific high-sensitivity troponin thresholds, BMJ, 2015; American Heart Association scientific statement on cardiac rehabilitation in women, 2025.
What's still missing
The measurement itself. No published study compares how long sex-specific findings take to reach practice against a matched set of findings in general. The research that exists counts whether sex-specific content appears in a guideline, not how long it took to get there. This is the single most useful thing the field could add, and it would make every other claim on this page more precise.
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Decision support at the moment of care. Of 821 clinical calculators on MDCalc, 84 include a sex or gender variable; of those, 98.8% use binary categories and about a quarter of the ones with retrievable references conflate sex and gender. No US vendor, health system, or published pilot currently surfaces sex-specific guidance as an embedded decision-support function. This is open ground, and it is the most concrete place a new effort could contribute.
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A standing cross-specialty synthesis. Specialty societies do this well within their own conditions, and the AHA does it best. What nobody publishes is a single, continuously maintained view across every condition, which means a clinician who wants to know the current state of sex-based evidence outside their own specialty has no one place to look.
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Adoption tracking. For troponin thresholds, for the 2022 endometriosis guideline change, and for SCAD recognition, the guidance changed and nobody has measured what happened next. Tracking adoption is a modest, achievable piece of infrastructure, and it is what turns a guideline update into a known result.
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A US home for the models that already work. Three of the strongest sex-differences resources in the world, Janusmed, OncoSexome, and the SAGER guidelines, were built outside the US. Each is an invitation rather than a shortfall: the approach is proven, and the opportunity is to bring it here in partnership with the groups that built it.
How the Compendium fits.
This is the gap the Compendium was built for. A by-condition catalog at primary-literature depth, with named trials and registries, effect sizes, and evidence-quality flags, refreshed monthly and reviewed section by section by a PhD or clinician, is a direct answer to the two things missing above: a standing cross-specialty synthesis, and a way to see when something has changed. It shortens the last stretch of the path by giving the finding somewhere current to live, where a clinician, a guideline writer, or a CME developer can find it without waiting for their own specialty to get to it.
where the gap starts
The number everyone cites is 17 years, and the honest version is more useful. Balas and Boren (2000, Yearbook of Medical Informatics) tracked nine preventive and cardiac procedures and calculated 15.6 years from landmark trial to 50% utilization, split into 6.3 years to reach reviews, papers, and textbooks and a further 9.3 years to reach practice. Morris, Wooding, and Grant (2011, Journal of the Royal Society of Medicine) reviewed 23 studies and found publication-to-guideline lags ranging from 0 to 49 years, and their paper was an argument against treating 17 as a single reliable figure, since the studies were rarely measuring the same thing. Hanney et al. (2015) traced seven complete pathways from discovery to implementation and found 18 to 54 years. The useful read is not one number but the spread: how fast evidence travels depends almost entirely on what carries it.
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Source: Balas & Boren 2000; Morris et al. 2011; Hanney et al. 2015.
why this is a gap
Sex-based findings have a longer road to travel, because the three things that normally carry evidence to the bedside each have less to work with. The evidence itself is often not disaggregated: across 574 NIH-funded publications from 2017 to 2024, 61% included both sexes and 83% of those reported sample size by sex, but only 44% ran an actual sex-based analysis (Communications Medicine, 2026). The tools clinicians use at the point of decision mostly have nowhere to put the finding: of 821 clinical calculators on MDCalc, 84 include a sex or gender variable at all (Biology of Sex Differences, 2026). And no US body publishes a standing, cross-specialty synthesis of sex-based differences the way specialty societies do for their own conditions. Each individual finding has to be carried across by whoever happens to care about it.
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Sources: Communications Medicine 2026; Biology of Sex Differences 2026.