News
The technology exists: Why are women still waiting?
By Jane Lewis, chief operating officer, chief financial officer and women’s health lead, ABHI
For years, the conversation around women’s health has rightly focused on recognition.
Recognition that women wait longer for diagnosis. Recognition that symptoms are too often dismissed or normalised. Recognition that healthcare systems have historically been designed around male biology, leaving gaps in research, evidence and care.
That recognition matters. But awareness alone will not improve outcomes.
The challenge facing women’s health today is no longer simply identifying the problem. It is acting on the solutions already available.
At ABHI’s Women’s Health Summit earlier this year, leaders from across healthcare, government, academia and industry came together to discuss the future of women’s health.
One message emerged repeatedly throughout the day: we do not have an innovation problem.
Across medical devices, diagnostics, digital health and genomics, there are already technologies capable of transforming outcomes for women.
From self-sampling approaches for cervical screening and non-invasive diagnostics to AI-enabled tools and advanced imaging, innovation is happening. The question is whether healthcare systems can adopt it quickly enough.
Too often, promising technologies become trapped in pilot programmes, fragmented procurement processes or lengthy implementation pathways. Evidence generation, commissioning and adoption are frequently treated as separate challenges rather than part of a single journey.
The consequence is that innovations capable of improving quality of life and reducing pressure on health services take years to reach the women who could benefit from them.
This matters because women’s health extends far beyond reproductive health.
Historically, many discussions have centred on fertility, pregnancy and gynaecological conditions. These remain critically important, but they represent only part of the picture.
Women experience cardiovascular disease differently to men. They are disproportionately affected by autoimmune conditions. They face distinct health challenges throughout their lives, from adolescence to healthy ageing.
Jane Lewis
Yet healthcare systems often continue to approach these issues in isolation.
A woman does not experience her health in separate compartments. Pregnancy, cardiovascular risk, menopause, mental health and musculoskeletal conditions are interconnected.
Healthcare systems need to reflect that reality through more integrated, life-course approaches to care.
There has never been a better opportunity to do so.
Across the NHS, the shift towards prevention, community-based care and digital transformation aligns closely with the needs of women’s health.
Women’s Health Hubs are already demonstrating the benefits of bringing services together around the needs of women rather than organisational boundaries. Digital technologies are helping to identify risk earlier and support more personalised care.
Innovation can help deliver all three of the NHS’s major transformation ambitions: moving from treatment to prevention, from hospital to community, and from analogue to digital care.
But innovation alone is not enough.
Closing the women’s health gap also requires us to address longstanding gaps in research and evidence.
Women remain underrepresented in many areas of clinical research, and sex-disaggregated analysis is not always applied consistently. The result is that clinical pathways and treatment decisions are often based on evidence that does not fully reflect female physiology.
Better data, stronger research participation and greater focus on female-specific and female-predominant conditions will be essential.
There is also a compelling economic case for action.
Women’s health is often framed as an equality issue, and equality remains central. But poor health affects workforce participation, productivity and economic growth.
Improving outcomes for women benefits not only patients, but employers, healthcare systems and wider society.
Yet despite this, women’s health innovation continues to attract only a fraction of the investment directed towards other areas of healthcare.
That is beginning to change.
Across the UK and internationally, momentum is building. Governments, investors, researchers and innovators increasingly recognise that women’s health is both a societal necessity and an economic opportunity.
The conversation has moved on significantly in recent years. Topics that were once overlooked are now firmly on the policy agenda.
The next challenge is ensuring that awareness translates into action.
The technologies exist. The evidence is growing. The policy direction is increasingly clear.
ABHI is increasingly taking this agenda beyond national boundaries. Through our engagement with international industry associations, policymakers and healthcare leaders, we are working to ensure that women’s health is recognised as both a health and economic priority.
We are helping to shape discussions on innovation, regulation, investment and adoption, while sharing lessons from the UK with partners around the world.
Whether addressing the gender health gap, improving access to diagnostics or accelerating the uptake of new technologies, international collaboration will be essential.
The challenge now is not recognising the need for change, but delivering it.
Women have waited long enough for acknowledgement of the problem. They should not have to wait any longer for the benefits of the solutions that already exist.
ABHI is the UK’s leading industry association for HealthTech. Its members, ranging from multinationals to small and medium-sized enterprises (SMEs), develop and supply technologies spanning everything from syringes and wound dressings to surgical robots, diagnostics, and digitally enabled healthcare solutions. ABHI’s 400 member companies represent approximately 80% of the UK HealthTech sector by value.
Australia’s drug advisory committee has recommended wider funding of triptorelin for women with breast cancer or endometriosis.
The recommendation comes after AstraZeneca announced plans to remove Zoladex from the market, risking leaving more than 7,500 women with breast cancer without an alternative treatment.
Both medicines block the release of oestrogen and testosterone and can be used as part of treatment, or for fertility preservation, in some forms of cancer.
The Pharmaceutical Benefits Advisory Committee met urgently in July and recommended making triptorelin unrestricted under the Pharmaceutical Benefits Scheme (PBS), which would mean it was funded for all uses.
The drug has been listed on the PBS for prostate cancer since 2006.
Triptorelin and Zoladex can also be used to treat endometriosis and to block puberty for either precocious puberty or gender-affirming care.
Vicki Durston, director of policy and advocacy at Breast Cancer Network Australia, described the recommendation as “a significant step forward” and said access to the medicine could mean the difference between life and death for some patients.
She said some women had already chosen to have their ovaries removed because of uncertainty over Zoladex supplies.
Marilla Druitt, Victorian state chair of the Royal Australian and New Zealand College of Obstetricians and Gynaecologists, said it remained unclear whether triptorelin would work exactly the same way as Zoladex, but the recommendation was likely to be positive for patients with endometriosis and pelvic pain.
She said: “I’m glad we’ve got an alternative.”
“That’s fantastic, and it remains to be seen whether or not it will be as good, but pain is so complex, pain is a really hard thing to study because it’s got so many contributors.”
Druitt said further research would be needed after the medicine was introduced.
If accepted by the federal government, the recommendation would also allow PBS funding of triptorelin for puberty suppression in precocious puberty and gender-affirming care.
This would make gender-affirming care federally funded through the PBS for the first time and would remove a financial barrier for transgender children in Queensland and the Northern Territory.
Stuart Aitken, medical director of Gender Health Australia, said the recommendation had sparked “absolute joy” among his patients.
He said: “It takes away a huge barrier to accessing evidence-based care.”
“It means that the ban has a very limited effect.”
By Women’s HealthX
As healthcare organisations navigate tightening compliance mandates, evolving reimbursement frameworks, and shifting health economics, the single most critical asset for leadership is operational visibility into what their industry counterparts are executing right now.
Ahead of the Women’s HealthX marketplace in Boston this December, a cross-functional steering committee of health plans, hospital networks, biopharma innovators, and enterprise employers has launched the definitive 2026 U.S. Health Infrastructure Survey.
The objective of this brief, multi-state index is to bypass abstract market fluff and map out exactly how the country’s elite healthcare stakeholders are practically structuring their 2027 budgets, clinical protocols, and technology procurement guidelines.
Some of the questions we are asking:
- Health Plans & Payers “What is the biggest operational barrier to expanding women’s health coverage?”
- Health Systems & Providers “What is the biggest women’s health priority for health systems over the next 24 months?”
- Pharma & Life Sciences “What is the biggest commercial hurdle facing women’s health innovation?”
- Employers & Benefits Leaders “Which women’s health challenge creates the greatest workforce impact?”
By contributing just 60 seconds of your operational insight to the index, you will ensure your specific sector’s parameters are accurately represented.
In return for your participation, you will secure a priority, pre-ordered copy of the completed 30-page intelligence report when the final data drops this September!
See where your direct peer groups are drawing their line in the sand for the upcoming fiscal year.
Contribute 60 seconds and pre-order your national benchmark report
Women’s HealthX 2026 | From Rhetoric to Results
Encore Boston Harbor | December 3-4 2026
Bypass abstract market rhetoric to evaluate real-world health economics, regulatory compliance mandates, and care delivery systems.
Join the region’s foremost health plan medical directors, hospital COOs, biopharma innovators, and enterprise benefits buyers anchoring our 2026 tracks.
Sahar Abid is a Science Associate at Ema EQ, where she works on cultural sensitivity and bias in AI.
A woman asks an AI health assistant about postpartum depression.
She mentions that her in-laws are telling her to “push through” and skip medical help, even as her symptoms get harder to manage. She never says where she is from or names her background.
The assistant describes the condition and gives her a hotline number. It sounds correct, but it misses what she needs.
That gap is more common than the industry admits, and it points to a blind spot in how we test health AI for bias.
Most bias testing looks at what people explicitly say.
The typical way to check an AI for bias is to label a prompt with someone’s demographic details and see if the answer changes. That catches some problems but misses a bigger one.
Most people do not lead with their identity. They lead with their situation. The woman above told the assistant everything it needed to help her, just not in the form of a label.
Her real question was not only “what is postpartum depression?” It was “how do I get care when the people around me don’t want me to?
When family members hold sway over health decisions, and in many communities they do, advice that asks someone to overrule their family is not something they can act on.
The AI didn’t say anything factually wrong. It answered a different question than the one she was living.
We call this culturally implicit bias, meaning the AI misses the cultural context a situation implies rather than the context a person spells out.
When systems are trained to notice only the explicit cues, they fall back on a default answer built for the majority. For everyone else, the response can feel generic, off-target, or discouraging enough that they stop looking for help.
In health, that is not small. The people most likely to be missed are often the ones the system already underserves.
What we set out to test.
At Ema, we wanted to know how well AI picks up on cultural context that is implied but never stated. So we built our own way to test for it, across a range of communities and real situations like postpartum depression and fertility, using questions that carried cultural meaning without announcing it.
The patterns were consistent. Models often missed the meaning underneath the question. They dropped the specific details a person did share and smoothed them into something generic.
And even when they pointed toward real care, they tended to offer one option instead of choices that might actually fit a person’s life. Any one of those can be the difference between someone following the advice and walking away from care.
Why this matters for anyone building health AI.
Getting this right is the right thing to do, and it also works better.
When an answer reflects a person’s real context, people trust and act on the recommendations more, so they get the help and support they need.
Testing for it is harder than the shortcut most teams use. Swapping a name or a demographic label in and out is easy. Checking whether a model actually understands the human context around a question takes more care.
The shortcut teaches models to perform cultural competence instead of practicing it. No matter how much or how little someone chooses to share, they deserve an answer that is warm, complete, and usable.
A better question.
The bar for equitable health AI should be “does it serve someone who never told you who they are?” It is the harder test, but it determines whether real people get help.
The work of getting there is far from finished, and it is exactly what we are building toward at Ema.
Sources: Naidoo, V., & Chadha, K. K. (2025), Culturally responsive AI chatbots: from framework to field evidence, Computers in Human Behavior: Artificial Humans. Souligne, N., & Subbian, V. (2026), FairLogue: A toolkit for intersectional fairness analysis in clinical machine learning models.
Entrepreneur2 weeks agoApplications close August 18 for Women’s Health Innovation Summit 2026 Innovation Showcase
Menopause2 weeks agoThird of women unaware of perimenopause mental health impact
Entrepreneur2 weeks agoWomen’s Health Week Europe 2026 releases fully populated agenda ahead of October summit
Fertility5 days agoChelsea FC Women to launch first-of-its-kind player fertility fund
Menopause1 week agoMenopausal hormone therapy may lower dementia risk, study suggests
Hormonal health2 weeks agoWe are wrapping our children in plastic and calling it care
Diagnosis2 weeks agoChemicals in plastics may be linked to high blood pressure during pregnancy
News2 weeks agoWomen with endometriosis face 46% higher risk of type 2 diabetes – study