How The Medical Gender Data Gap Harms Women
Prepared by Sara Rizal
23 September 2026
Recently, it was announced that polycystic ovary syndrome (PCOS) was officially renamed polyendocrine metabolic ovarian syndrome (PMOS), to reflect the medical condition more accurately: not just an issue of the ovaries, but a complex, multi-system disorder of hormones, metabolism, and endocrine function affecting one in eight women globally[1]. The condition was first identified in 1935, yet it was only in 2012 that the National Institutes of Health (NIH) formally acknowledged the inaccuracy of its name, and it took another 14 years for the condition to be rebranded[1]. This long process is not a show of caution, but a reflection of how medical conditions affecting women are not seen as a priority. Historically, health conditions affecting women have received less funding and fewer diagnostic tools, thus subjecting women to years of pain before receiving the appropriate care.
This long process is also how my friends, and most, if not all, women, would characterise receiving their diagnosis. It would take years for them to confirm an endometriosis diagnosis, and even then, some report feeling dismissed, confused, and dissatisfied with their care. Women’s physical pain is far more likely to be dismissed as ‘emotional’. The outcome of this is that women are twice as likely to be prescribed the wrong medication. For instance, studies have shown that while men who reported pain tended to receive pain medication, women were given sedatives or antidepressants[3]. This medical routine is also exacerbated by the fact that women routinely wait longer than men to receive treatment. A US analysis of 92,000 emergency-room visits between 1997 and 2004 found that women had longer waiting times than men[3]. The reality is that female bodies are not given the same level of medical attention as male bodies.
Essentially, one of the main reasons for this delayed diagnosis is that the way data is collected and interpreted by gender is subject to fundamental biases, generating a gender health gap that impacts all levels of health research[2]. The medical gender data gap can be characterised as missing or incomplete evidence for diseases that disproportionately impact women, and the existing evidence is interpreted in light of men’s symptoms as the default[2]. By not addressing the medical gender data gap, we will continue to delay diagnosis, limit medical knowledge about women’s health, and weaken healthcare policies.
Limitations of treating men as the default patient
The male-default bias in medical knowledge has resulted in women’s symptoms being misdiagnosed, diagnosed late, or worse, completely dismissed. Male-default bias in medicine is the assumption that the male body is the standard model for human physiology, while women's bodies are presented as “abnormal”. This male-biased perception informs how medicine is taught and studied. For example, the integration of sex- and gender-based medicine in US med schools remained ‘minimal’, with gender data gaps identified in the approach to treating disease and drug use[3]. By seeing the male body as the default patient, women are less likely to be included in medical trials, thus preventing the collection of invaluable data that can more accurately contribute to women’s medical literature[3].
Without sex-disaggregated data, women are subjected to receiving inaccurate diagnoses, resulting in inaccurate prescriptions or delayed treatment. For example, women experience twice as many adverse drug reactions as men for over 86 different medications approved by the United States’ Federal Drug Administration (FDA)[2]. Yet most drugs are approved based on clinical trials that are either conducted solely on men or include women in later trials[2]. The consequence of mainly relying on findings from male subjects is that women may experience over-medication, adverse reactions, or susceptibility to dosage inaccuracies. In the context of diabetes amongst Malaysians, evidence reveals that women are less likely to receive the recommended care, as certain medications have different side effects in men and women[4]. However, clinical guidelines rarely recommend sex-specific treatments[4]. By systemically treating men as the default patient, coupled with the lack of representation of women in clinical research, the medical gender data gap continues to widen, thus affecting our ability to give women sound medical advice and treatment.
Women’s health is under-researched and reduced to reproductive health
In addition, the lack of gender-disaggregated data leaves many conditions under women’s health severely understudied. Currently, the scope of women’s health is reduced to maternal and reproductive health. Meanwhile, other health conditions have not been effectively studied in terms of the gender differences between men and women. For example, in the context of heart diseases, chest discomfort is the most common symptom during a heart attack for both men and women[5]. However, women are more likely to experience other symptoms such as nausea, fatigue, and breathlessness[5]. These symptoms are often mistaken for less serious conditions such as anxiety or indigestion[6]. This dismissal of women’s symptoms also explains why women were less likely to receive an electrocardiogram (a standard test to check for a heart attack) and less likely to be hospitalised[5]. Such symptoms are often labelled “atypical” when a more appropriate term, according to some cardiologists, would be “understudied”[5]. Clearly, gender-based research around women’s health, such as cardiovascular diseases, is not given the proper time and resources to be investigated. The lack of gender-sensitive medical information is leaving gaps in diagnosis among women, leading to poor health outcomes and potentially costing their lives.
Poor data leads to poor healthcare policy
Moreover, neglecting the medical gender data gap can lead to poor healthcare policies. By not acknowledging the male-default biases in medical research, this can impact population-level summary indicators, which are often used to develop and monitor progress in health, set targets, and develop strategies in national health plans[2]. Such biases can also impact emerging fields such as digital health, precision medicine, and the use of artificial intelligence, as these technologies do not account for gender bias detection[2]. Fundamentally, the lack of gender- and sex-disaggregated data will obscure differences in disease prevalence and treatment outcomes. Hence, we must do more to reduce the medical gender data gap.
This starts with increasing the representation of women in clinical research and ensuring that data collection and reporting include the intersection of gender and sex at local and national levels. There must also be greater integration of gender perspectives in healthcare planning and resource allocation. Malaysian Government policy documents such as the Health White Paper and the National Women’s Policy demonstrate a clear commitment to women’s health, including gender data systems, attention to equity, and the inclusion of women-specific indicators[7]. However, the policy framework lacks a fully integrated approach that connects prevention, early diagnosis, treatment, and long-term care across the life course[7]. Malaysia has built strong foundations in maternal and reproductive health. The next step is to build on those foundations and adapt policy frameworks to reflect the full spectrum of women’s health across the life course.
PMOS is a case study on what happens when we do not address this medical gender data gap. We must invest in sex-disaggregated data, gender-responsive research, and healthcare policies that recognise women as patients whose experiences deserve equal medical visibility. We must advocate for a medical system that no longer makes women feel misunderstood, mistreated, or misdiagnosed. References
Alvarado, G. and Bird, C (2026) “What The PCOS-PMOS Rebrand Tells Us About The State of Women’s Health Research”, MSmagazine
Di Lego, V. (2023) “Uncovering The Gender Health Data Gap”, National Library of Medicine
Perez, C.C. (2019) “Invisible Women: Exposing Data Bias In A World Designed For Men”, Vintage
Dr Ming, M.F., Dr Hairi, N., and Dr Kim Sui, W. (2011) “Choose to Challenge Gender Inequality in Health”, MalaysiaKini
Corliss, J. and Bhatt, D. (2022), “The heart disease gender gap”, Harvard Health Publishing
(2025) “Understanding Gender Differences in Heart Diseases”, Health Digest
Dr. Kamarulzaman, A. (2026) “Beyond Maternal Health: Rethinking Women’s Health Policy”, Code Blue
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