Emma Lagerstedt, Account Manager at HCC, outlines how data can help deliver on the vision set out by the Government’s forthcoming Women’s Health Strategy.
When the Government announced a Women’s Health Strategy in March 2021 (to mark International Women’s Day), it was responding to calls from professional and patient groups to take a comprehensive approach to women’s health. As a result of a longstanding de-prioritisation of women’s health issues, the UK does not just have a gender wealth gap, but also a health gap.
Despite life expectancy for women in the UK exceeding that of men, women spend a larger proportion of their life in poor health, and life expectancy for women is improving at a slower pace than it is for men. We know women are biologically more susceptible to a range of conditions including osteoarthritis, MS, lupus and Alzheimer’s, but often lack the research and data to understand why, or how to address this gap.
The announcement of the Strategy was a welcome sign that the Government is prioritising women’s health. However, to be successful, policymakers must collect and use sex-aggregated data in order to understand issues facing women’s health and drive improvements in patient outcomes.
The initial press release issued by the Government about the Strategy partially acknowledges this point. On data, the Government will focus on the “inclusion of women and women’s health in research and data collection […] and driving participation in clinical trials to support improvements in women’s health.” However, as currently written, there is lack of clarity on how this data will be used to deliver meaningful improvements to women’s health outcomes.
It is true that more needs to be done to include women in data collection and research. Despite making up half of the population, women are often underrepresented in medical research, in part due to the perception that women’s hormones and menstrual cycles “complicate” findings or “intervene” with treatment effects. This leads to a poor physiological understanding of illnesses in women which often fuels misdiagnosis of women affected by common conditions such as cardiovascular disease. To address this issue and avoid further entrenching unconscious biases in healthcare, we don’t just need more data, but better data.
For instance, there are different risk factors at play for developing heart disease in men and women. Whilst there is excellent research currently underway on how to use artificial intelligence (AI) to predict and treat heart attacks and other cardiovascular diseases, the data currently available has historically underrepresented women. This means a sex-blind, one-size-fits-all approach to prevention and treatment will likely remain biased against women.
What is instead needed is not just to include women in data collection efforts, but to disaggregate said data by sex and use it to develop tailored recommendations for optimising care for women. In the era of personalised medicine, the more disaggregated data we have about an individual, the better we are able to make treatment decisions based on individual characteristics.
A commitment to using sex-specific data in this way would enable systems to make the evidence-based decisions required to unleash the kind of improvements to women’s health that the Government wants to achieve through the Strategy. If Westminster wants a little help on the way, they need only look to Scotland, where the Scottish Government has committed in its recent Women’s Health Plan to using sex-disaggregated data to improve healthcare policy and delivery as well as clinical research.
