Why women's health data is still an afterthought in tech - and what needs to change

When I was 43 years old, I sat in a doctor's surgery trying to describe symptoms that had been disrupting my life for months: disrupted sleep, word-finding difficulty, unexplained mood shifts, and physical changes I could not make sense of. I was told I was probably too young to be experiencing what I suspected was perimenopause.

After what felt like countless hours in waiting rooms, dozens of appointments, persistence, and considerable personal research, I received a perimenopause diagnosis.

My experience is not unusual. It is so common that many women simply accept this as 'normal'. But when I started to examine why women are so consistently underserved at this stage of their health, I kept finding the same underlying problem: we do not have sufficient data about women's health, and the technology sector is replicating that gap rather than closing it.

A gap that starts in research

The women's health data problem has deep structural roots. Until the early 1990s, women were routinely excluded from clinical trials, often under the rationale of protecting potential pregnancies. The consequence was that drugs approved during that period, many of which remain in use today, were tested almost exclusively on male subjects. 

While there has been reform in this area, the data gap has still not been closed. Studies continue to show that women are underrepresented in clinical trials across multiple disease categories, including cardiovascular disease and psychiatric disorders. In one striking example, women with milder cardiovascular symptoms were found to be less likely to receive diagnostic tests or prescribed medicines than male patients presenting with comparable conditions. That's not because of different clinical needs, but because clinical research has historically not studied women's symptom profiles with the same rigour.

Menopause sits at a particularly stark end of this spectrum. Despite being a universal biological experience for half the world's population, 58% of medical textbooks worldwide contain no reference to it. In the UK, 52% of GPs report feeling inadequately trained to support patients going through it. The knowledge exists, but it has not been systematically collected or distributed in the same way as knowledge about male health conditions.

Technology is not automatically the solution

The growth of health technology in recent years has been repeatedly presented as the answer to gaps in traditional healthcare - a view with which I'm firmly in agreement.  AI, in particular, has a real capacity to identify patterns in health data that traditional medicine has missed. But that potential is contingent on the quality of the data it learns from. When AI systems are trained on datasets that are overwhelmingly male, they inherit those biases. A diagnostic tool built on skewed data will not serve female patients equally. The technology is only as equitable as the research behind it.

The World Economic Forum estimated in 2024 that closing investment gaps in women's healthcare could boost the global economy by $1 trillion annually by 2040. And yet femtech - the category of technology nominally dedicated to women's health - remains a relatively small slice of overall health tech investment. And even within it, focus has historically skewed towards fertility and reproductive health rather than the broader arc of women's health across their lifetimes.

Who is building the products?

There is compelling evidence that representation in research leadership affects outcomes. A 2025 analysis of clinical trials found that trials led by women principal investigators enrolled significantly more female participants than those led by men. The same principle applies to technology. The products that most accurately address women's health needs tend to be built by people who have direct experience of those needs - who have been told their symptoms were psychosomatic and who had to advocate for their own diagnoses.

International Women's Day, in this context, should be less about celebration and more about accountability. The health technology sector has a representation problem that goes beyond hiring metrics. It is a question of whose experiences are treated as the default, whose health data is collected and analysed with rigour, and whose conditions receive sustained research investment. Addressing that requires more women in decision-making roles, but it also requires a deliberate choice to treat women's health data as a priority rather than an afterthought.

What the technology sector needs to do differently

The path forward is not technically complicated. It requires enforcing diversity in clinical datasets. It requires funding for research into conditions that affect women specifically. And it requires investors to recognise that the underserved market is an opportunity, not a risk.

When I eventually received my diagnosis, I did not feel relieved - I felt angry. Angry that information that could have helped me sooner existed somewhere, but had not been made accessible. The data to serve women better exists or can be collected. What has been missing is the will to treat it as a priority.

The health technology sector has an opportunity to correct a decades-long imbalance. That means building with women's data, for women's needs, with women in the room where decisions are made. It's a simple ask, and it's what truly equitable healthcare requires