The Gender Data Health Gap: Solving Women's Healthcare Challenges with Advanced Technology

The gender data gap is the difference in the scope of knowledge about health between men and women that results in the reduced quality of treatments for women and delayed diagnostics.

In this article, we discuss the main challenges in different fields of women's health, the reasoning for healthcare gender bias, and how tech innovations that affect women's health can help bridge gender bias in healthcare.

The main challenges in different fields of women's health

Sex-based differences between men and women affect all branches of healthcare because sex matters on a cellular level. Yet, due to historical prejudice and lack of sufficient research, there is a gender health data gap in the way women are diagnosed and treated. Here is an overview of the main conditions that are affected by this:

Cardiovascular diseases

Cardiovascular diseases are a leading cause of death globally for women, and yet, they are a huge part of the gender health data gap. Women are twice as likely to die of coronary heart disease compared to men (Source ).

There are several gender-specific issues at stake when it comes to cardiovascular health:

• Women often experience atypical symptoms like fatigue, nausea, and back pain during a heart attack.
• Medical research has historically focused on male participants when studying heart disease. As a result, the symptoms of a heart attack were identified based on how men typically experience them (e.g., chest pain, arm pain, shortness of breath). Even today, women experiencing heart attacks are 50% more likely than men to receive an incorrect initial diagnosis, as described in the book by Caroline Criado Perez, Invisible Women: Exposing Data Bias in a World Designed for Men. This often leads to incorrect and untimely treatment.

• Most clinical trials and treatment protocols on heart conditions were conducted decades ago and are based on male physiology. The Harvard Physicians' Health Study, conducted in 1982 on 22,000 male participants, established aspirin as a preventive treatment for heart attacks. However, because the study excluded women, researchers lacked data to confirm aspirin's safety and effectiveness for them. This gap led to hesitancy in prescribing aspirin to women.

Autoimmune diseases

Autoimmune diseases are highly prevalent in women. In fact, 78% of the cases occur in female populations partially due to the influence of the X chromosome and sex hormones.

• Examples include lupus, rheumatoid arthritis, multiple sclerosis, and Hashimoto's thyroiditis, all of which disproportionately affect women.
• Despite the prevalence, autoimmune diseases are often misdiagnosed or attributed to stress due to vague and overlapping symptoms like fatigue and pain.
• This occurs due to a lack of understanding of hormonal or genetic triggers for these diseases. It takes an average of five years for women to receive a diagnosis of an autoimmune condition.
• To date, there are limited studies on why autoimmune conditions disproportionately affect women.
• There are also limited options for treatment that focus on managing symptoms rather than addressing the root causes of these conditions.
• This partially occurs due to a lack of expertise that allows the identification of autoimmune diseases based on symptoms and the dismissal of certain symptoms as generic. Autoimmune diseases are very complex and call for specific research.

Pain management and chronic pain disorders

• Conditions that fall under this umbrella include fibromyalgia, migraines, and chronic pelvic pain.
• One of the main issues with these conditions is that women's pain is often dismissed or undertreated due to gender bias in the health systems related to the perception of pain. An analysis of 77 studies from high-income countries found a persistent ideology that women are "used to internal pain," and pain without external causes was perceived as a "natural characteristic" of women's bodies (Source ). As a result, women experiencing pain are often labeled as hysterical, emotional, or fabricating their symptoms.
• Migraines, which affect women three times more often than men due to hormonal fluctuations linked to estrogen, are often underestimated in severity. Women with migraines frequently experience longer and more debilitating attacks, yet the condition is frequently dismissed or inadequately treated. Yet, this debilitating condition impacts productivity and quality of life.
• Historically dismissed as psychosomatic, pain-related conditions now have limited understanding and treatment options.

Reproductive health

• Conditions that fall under this umbrella include polycystic ovary syndrome (PCOS), infertility, endometriosis, uterine fibroids, and menopause.
• There is insufficient research on hormonal disorders like PCOS and menopause management. PCOS, for example, is a very common condition that affects about 8-13 % of women worldwide, yet 70% of cases remain undiagnosed.
• Awareness and management of menopause are also limited despite the fact that women live about one-third of their lives in menopause.
• Endometriosis takes an average of 7-10 years to diagnose. It is also subjected to symptom dismissal, again, due to gender bias in healthcare related to the attitude towards pain.
• The problem is that the focus on reproduction often overshadows other health aspects, and the standards of female care are associated with catering to reproductive function. However, understudied reproductive conditions affect different aspects of women's health, even beyond reproductive age. Even with fertility, treatments are often not available due to high prices, and causes of female infertility are underresearched.

Alzheimer's Disease

Women account for two-thirds of Alzheimer's patients.

There are some gender-specific issues in the way the conditions manifest, such as:

• Women experience faster cognitive decline than men.
• Women often show more pronounced verbal memory impairments early in the disease, even when brain scans indicate similar levels of damage as in men.
• The research healthcare gender gap here is the lack of focus on why the disease disproportionately affects women. The biological and hormonal factors contributing to this disparity are not well understood. Possible links to estrogen, longevity, and genetic risk factors (like APOE ε4) require further study.

Cancer

• Conditions that affect women specifically include breast cancer, ovarian cancer, cervical cancer, and other cancers of the reproductive system. Surprisingly, other cancers like lung cancer, the leading cause of cancer in women, also manifest in gender-specific ways that are under-researched.
• Meanwhile, research and early detection focus on breast cancer. In contrast, ovarian and cervical cancers are often diagnosed late, especially in postmenopausal women, as there is an attitude of dismissing gynecological health past childbearing years.
• Lung cancer in women is rising, especially among non-smokers, and may be linked to estrogen.

Drug responses

• Women metabolize medications differently, yet drug dosages are often based on male physiology due to the past lack of women in clinical trials.
• A higher risk of adverse reactions in women is due to underrepresentation in drug trials, a key component of the gender health data gap.
• Some of the examples of drugs affected by this are Ambien, statins, and chemotherapy drugs. In particular, Ambien (zolpidem) was found to remain in women’s systems longer than in men, causing next-day drowsiness and impaired driving. The FDA had to revise its dosage guidelines for women only after the drug was widely prescribed, and women experienced issues when driving their cars.

Osteoporosis and bone health

• Women are four times more likely than men to develop osteoporosis.
• Hormonal changes post-menopause lead to rapid bone density loss.
• The issue is that there is a lack of focus on early prevention and tailored treatment for women. For women, maintaining adequate muscle mass through weight training helps prevent osteoporosis. Yet, exercise is an overlooked factor that physicians do not directly recommend, and there is a mistaken focus on body mass index to determine health, without considering muscle mass and bone density.

Sexual and pelvic health

• Non-fertility sexual health issues in women include pelvic floor disorders, sexual dysfunction, vaginismus, and dyspareunia (pain during intercourse).
• Taboo and stigma around discussing sexual health often delay diagnosis and treatment. There is also a lack of knowledge about what sexual health looks like for women due to a lack of sexual education in society and among medical professionals themselves.
• Poorly fitted or outdated medical devices are also a part of this problem. Pelvic mesh, or transvaginal mesh, is a medical device used to treat pelvic organ prolapse (POP) and stress urinary incontinence (SUI) by supporting weakened pelvic tissues. However, many women have experienced severe complications, including chronic pain, infections, and mesh erosion through the vaginal wall. Due to safety concerns and high failure rates, the FDA banned transvaginal mesh for POP in 2019.
• All in all, there is an insufficient focus on non-reproductive sexual health issues.

Infectious diseases

• Conditions include HIV, HPV, and vaccine side effects (e.g., flu, COVID-19).
• Women are biologically more susceptible to certain infections like HIV.
• Women also experience stronger immune responses to vaccines, leading to more severe side effects.
• There is a limited study of sex-based differences in immune response and vaccine development that create a gender data gap.

Understanding the health data gender gap

Based on everything we have discussed so far, it can be concluded that the healthcare gender gap is a result of the following:

• Historical exclusion of women from clinical trials
• Underfunding of female-specific conditions, such as autoimmune diseases and reproductive health.
• Lack of sex-based analysis in medical research, resulting in treatments and diagnostics based on male physiology.
• Dismissal and misdiagnosis of women’s symptoms by doctors
• Limited understanding of hormonal and genetic differences between sexes
• Insufficient focus on non-reproductive aspects of women’s health
• Biases in healthcare education and practice reinforcing outdated assumptions about women’s pain
• Poor accessibility to healthcare and medical innovations

Solving these issues calls for a holistic approach that includes education, funding, and also investing in femtech.

These include:

• Centering female issues in the education of medical professionals
• Investing in the research of conditions that primarily affect women
• Improving the legislative stance on addressing the healthcare data gap. Some examples include the FDA Guidance on Sex-Specific Differences (2014) and the NIH Revitalization Act (1993).

Femtech solutions are an excellent strategy to bridge the data gender gaps. Here are just some of the exciting things they can do:

• AI-powered healthcare data analytics to identify sex-specific healthcare IT trends .
• Wearable devices tracking menstrual cycles, hormonal fluctuations, and pregnancy health.
• Digital platforms for clinical trial recruitment ensure better female representation.
• AI-driven tools for early detection of endometriosis, PCOS, and menopause-related conditions.
• Smart breast health monitors for non-invasive cancer screening.
• Personalized treatment plans using predictive analytics for autoimmune and cardiovascular diseases.
• Telemedicine services tailored for women's health (e.g., fertility, menopause, chronic pain).
• Mobile health apps offering evidence-based guidance for sexual and reproductive health.
• AI-driven clinical decision support systems that account for sex-based differences in drug metabolism.
• Real-world data collection to improve medication dosages and reduce adverse reactions in women.
• Digital symptom trackers help women advocate for proper diagnosis and treatment.
• Introducing AI-powered decision support systems in clinics for faster and more accurate diagnosis.
• Expanding women-specific health programs in hospitals for integrated, holistic care.

Here are some of the innovations in women's health that are already working towards closing the gender health gap:

• The FEMaLe Project (2020): A Europe-wide initiative to improve endometriosis diagnosis using AI-driven methods.
• The HEARTHEALTH Study: Focused on how heart disease affects women differently through wearable devices and telemedicine to collect real-time data.
• Medable: A decentralized clinical trial platform that recruits diverse participants, including women from various backgrounds.
• HERstory Trials (Astellas Pharma): These clinical trials specifically focus on female urology, particularly overactive bladder syndrome.
• Oratel Diagnostics is developing a saliva-based AI-powered test to detect endometriosis early.

Tech-driven strategies to bridge the health data gender gap

The gender health data gap is not just a medical issue; it's a critical business and innovation challenge. Insufficient data limits the effectiveness of AI applications in healthcare , and in femtech, this problem becomes even more pronounced.

Addressing the core problem: Data insufficiency in women's health

One of the primary challenges in femtech is the lack of comprehensive and inclusive datasets. Historically, male-centric data has been accumulated over decades, leaving women's health research underfunded and underrepresented. This imbalance affects:

• The accuracy of AI-driven diagnostics.
• The reliability of predictive healthcare models.
• The development of personalized treatments for women.

Overcoming data limitations with IoT and federated learning

IoT

The Internet of Things (IoT) enables real-time health data collection through connected devices such as wearables . In the context of women's health, IoT devices can track and analyze menstrual cycles, hormonal changes, digital innovations for maternal health , and more. By quickly generating large volumes of high-quality data, IoT in healthcare helps balance the historical gender gap in healthcare research.

Federated learning

Federated learning is a machine learning approach that trains AI models across multiple devices or servers without sharing raw data for privacy purposes. It addresses the challenge of data sharing in highly regulated industries like healthcare. Here's how it works:

• Small hospitals or clinics lack sufficient patient data individually, and local AI models cannot be trained on anonymized data. This creates a kind of decentralized collaboration.
• These models are then shared securely, not the raw patient data, ensuring compliance with privacy regulations like HIPAA.
• The aggregated models from multiple sources form a larger, more accurate, unified AI model. This model is periodically updated with contributions from all participants, creating a robust system that benefits every collaborator.

In femtech, federated learning allows organizations to:

• Combine data from wearable devices, clinics, and research centers.
• Create more accurate AI models for diagnostics and treatment recommendations.
• Maximize insights while protecting sensitive patient health information.
• Accelerate data collection by integrating diverse, real-time health data.
• Enhance data accuracy with models that better reflect women's health needs.

Advanced tech solutions for women's health

Bridging the gender health gap requires advanced tech and AI solutions—and to achieve this, you need an experienced tech partner for healthcare software development who understands healthcare innovation.

Binariks has demonstrated its expertise in applying advanced technologies to address key challenges in women's health. For instance, Binariks partnered with an innovative online clinic to enhance access to reproductive care through a custom telehealth platform. The client sought to minimize the need for in-person visits while ensuring high-quality, patient-centered fertility treatments.

Our team streamlined and automated key administrative processes—such as patient verification and test requisitions—reducing operational overhead and improving the patient experience. By integrating third-party tools, including DrChrono, Calendly, and Fertile AI, we created a centralized solution where patients and caregivers could seamlessly manage health data, lab orders, appointments, and treatment plans. Also, we ensured a secure, scalable system optimized for real-time data access.

The result was a more efficient, accessible, and patient-friendly platform for fertility care, helping the client expand its services while reducing stress and barriers for women in their fertility journey.

Closing the gender health data gap: A call to action

The gender health data gap has long contributed to misdiagnoses, delayed treatments, and a lack of research on conditions disproportionately affecting women. This disparity is a challenge for anyone involved in developing medical technologies, from researchers to software engineers and digital health innovators.

Advancements in women's health tech are helping bridge this gap through improved data collection, AI-driven diagnostics, and personalized treatment approaches. Federated learning ensures privacy while enabling more inclusive research, while IoT-powered devices provide continuous, real-world health insights tailored to female physiology. Digital health platforms further enhance accessibility, delivering targeted care solutions that address historically overlooked medical needs.

Closing this gap requires a concerted effort from healthcare providers, technology leaders, and policymakers. By integrating gender-aware data strategies into healthcare innovation, companies can build more effective, inclusive, and impactful solutions.

At Binariks, we specialize in developing cutting-edge health tech solutions prioritizing data accuracy, security, and usability. Contact us to ensure your next healthcare innovation contributes to a more equitable medical future.