The Numerical Bias: Gender Divide in Healthcare

Globally, while women are known to live longer than men, they tend to have higher instances of chronic morbidity, respiratory disorders and mental health issues. Yet, women are less likely to report illness, utilize healthcare services and spend on healthcare. There has been growing attention towards gender inequality in healthcare. From diagnosis of illness, prescription of drugs, post-natal care to inclusion in clinical trials and development of healthcare technology, women experience unequal medical attention in every setting. While understanding each of these component remains equally important, the aim of this article is to decipher inequity at the baseline i.e. gender-biased numbers in the medical space.

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“……Numbers enlighten, empower, elevate. Numbers can help us make sense of modern India. Numbers can help us anticipate the future. But numbers do not exist in a rarefied space”

- Rukmini S

Representativeness of Clinical Trials: The issue of inequity in numbers starts at the root of medical research. Clinical trials are integral in determining what symptoms, which drug and what technology can help understand and deal with an illness. However, these trials are dominated largely by male participants and less so by female participants. This makes the trials less representative of the entire population and leaves doctors with reduced understanding of female’s health. ?In her book “Invisible Women”, Caroline Perez comprehensively documents the inequities in gender representation in research trials. She observes that the gaps are most concerning in studies on mental health, cardiovascular diseases and cancer. For example, despite the fact that women are 70% more likely to suffer from depression than men, females are severely underrepresented in clinical trials on psychiatric disorders. Only 42% of participants in mental disorder drug studies are females. Even the animal studies on brain disorders are five times more likely to be dominated by male animals. Such biased representation in studies leaves doctors misinformed and half of global population at adverse risk of being misdiagnosed.

Biased Drug Trials: Beliefs on women being unfit subjects due to factors such as menstruation, pregnancy and oral contraceptives often leads to their exclusion from early phases of drug studies. Pertaining to these reasons, women are more likely to be included in phase three of drug trials and less likely in phase one and phase two. Trials for generic drugs are almost exclusively dominated by young adult males. Due to lack of inclusivity, post-trial numbers remain biased and puts women at dangerous risk of side effects. For instance, in 2013 the FDA recognised that the active ingredient in the prescription drug Ambien left women severely groggy with no such notable consequence for men. Recognising that women need to be included throughout the lifecycle of drug development process remains extremely essential for imparting correct advice and improving the understanding of female health.

Lack of Gender-Disaggregated Data: Another notable issue in numbers arises from lack of recorded and segregated data by heterogeneous classes in the hospital systems. With technological advancement in artificial intelligence and the advent of big data, it has become easier to capture a patient’s information and analyse their history. Despite this, only 35% of the reported data in hospital systems is segregated by gender. This prevents the ability of institutions to conduct meta-analysis and identify the sex-dependent effects. Such information is necessary to identify not only the biological differences between men and women but also, the socioeconomic characteristics which potentially contribute to inequities in the health space.

Final Remarks: Governmental policies and initiatives by international organisations need to keep pushing for equality in research trials and improve data representativeness. Progress in equitable medical research can ?happen by inclusion of more women in research teams and at leadership positions. Higher authority and decision-making power will enable them to align the objectives of research with a female’s perspective, thus making it more inclusive. Further exploration of social factors such as time constraints for women due to care-giving and financial dependence on male members can help policy makers build capacity and design interventions that increase female’s participation in research trials.

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Written by

Shubhangi Agrawal, RA at IIM Ahmedabad