Closing the Data Gaps in Women’s Health (McKinsey)

Now more than ever, data is at the center of engagement and decision making. Healthcare and life sciences are no exception: data is central to discussions about public health and is core to enabling continued scientific advancement. The accelerated digitalization of healthcare during the pandemic has only expanded the amount of health-related data available—and cemented the key role that it plays in care delivery, disease prediction and diagnosis, biopharma and medtech innovation, and patient outcomes.

Despite the exponential growth in data generated across the healthcare ecosystem, notable gaps remain. One such area is women’s health, in which gaps span the entire data value chain—from defining women’s health (pre–data generation) to diagnosing (data generation) to tracking at the national level (data collection) to translating data into insights at the global level through epidemiological studies (data analysis). These data disparities ultimately influence health outcomes for women globally by creating blind spots in the insights that drive research design, investment decisions, and pipeline priorities. Certain subsets of women, such as those of different backgrounds, sexual orientations, and gender identities, are more vulnerable to the gaps and negative effects of these blind spots. Furthermore, insufficient availability and analysis of women-specific health data undermine advancements in disease-state understanding and limit asset discovery opportunities across medical conditions with meaningful unmet need.

Closing the gap in women’s health data is essential to ensuring that women receive the care and treatments they need to maintain good health. This requires a concerted effort from healthcare providers, researchers, policymakers, and the public to address the underlying causes of this gap and work towards more inclusive and equitable healthcare practices. This article by McKinsey highlights these disparities and explores options to remedy them.