What can we learn from women’s health data?

Analysing real-world health data could help overcome the bias towards men in traditional medical research, says Sensyne Health's Dr Lucy Mackillop.

Collecting and analysing anonymised patient data has the potential to generate valuable insights that can catalyse research, lead to improved patient care, and power the development of new treatments.

Being able to analyse large data sets can provide a better understanding of how some patients will respond to a treatment or predict who may develop a disease based on data collected during clinical care.

Medical research has often focused on men, meaning that the insights gained have not always been reflective of how women would react to a treatment or disease. Women are likely to have different symptoms to men for the same illness and do not necessarily have the same reactions to certain drugs or respond to the same doses as a male counterpart.

Therefore, it is important to increase the collection and analysis of women’s health data so better insights can be gained for supporting their care.

The impact of underrepresenting women

Research from the Allen Institute for Artificial Intelligence found that over the past 25 years, although women have made up nearly half (49%) of participants across drug trials, for many types of disease the proportion of female participants did not match the gender breakdown of real-world patients. In trials for cardiovascular, HIV, kidney disease and digestive diseases, women have especially been underrepresented.

The effect of failing to include women proportionately in clinical trials may have consequences for the quality of medical care women receive, with therapies, doses and risk assessment tools being tailored to the male population. The use of real-world medical data from women may change this – and more broadly, ensure that representative samples of data are used for the disease or issue.

What we can learn during pregnancy

As well as collecting more representative samples of data from women for conditions like cardiovascular disease, accurate data collected during pregnancy could offer a valuable information.

This is because typically, ‘real-world’ medical data is collected from patients who are ill. However, pregnancy is a unique time when large quantities of data are collected in otherwise ‘healthy’ women.

Pregnancy can also act as a cardiometabolic stress test for women and reveal underlying susceptibilities to conditions such as diabetes or hypertension.

Therefore, by analysing the data collected during a woman’s pregnancy, clinicians can view a window into future health risks and understand who is most at risk. This helps develop better preventative strategies and also prioritises care.

Last year it was estimated that 20% of pregnant women in the UK were affected by gestational diabetes, while each year, up to 15% of pregnancies are affected by hypertension. Developing therapeutic strategies and individual care pathways may allow for prevention or delay in these diseases, both for the mother and her offspring.

Improving health of future generations

Research has found that the environment in which a baby grows has a significant impact on its health throughout its life. This means that being able to improve the way we care for pregnant women through collecting and analysing data can also significantly influence the health of their offspring.

While collecting data from patients is important in development of new treatments, clinical research, and patient care, there must be a greater focus on ensuring that women are well represented in trials.

For pregnant women in particular, the information that their medical records can offer must be recognised, and databases that can be used to support the improvement of care and outcomes has the potential to provide important insights.

About the author

Dr Lucy Mackillop is a consultant obstetric physician at Oxford University Hospitals NHS Foundation Trust; honorary senior clinical lecturer, Nuffield Department of Women’s and Reproductive Health, University of Oxford; and chief medical officer at Sensyne Health.