Leveraging technology for better women’s healthcare outcomes

The global digital health market is expected to be valued at $660 million by 2025, which will advance technology for both the patient and healthcare professionals (HCPs). And with advancements come improved patient outcomes.

When specifically looking at women’s care, there are a few areas benefitting from technology, such as remote patient monitoring. By 2024, more than 75% of US medical practices are projected to implement remote patient monitoring (RPM) technology. Additionally, generative artificial intelligence (AI) and the use of patient data are playing a major role in creating new opportunities and improving outcomes.

The integration of telemedicine with RPM devices and AI has immense promise in optimising women’s health outcomes. This information can also allow pharmaceutical companies access to data to meet the specific needs of women.

Effectively leveraging RPM

Prior to the pandemic, RPM might have been considered a trend, but nowadays it is considered imperative in our healthcare landscape. Technically, RPM is described as using technology, such as wearable devices integrated with mobile apps or platforms, to remotely collect and transmit health data from patients to healthcare providers through a HIPAA-compliant digital dashboard. In modern healthcare, RPM is transforming the patient journey by improving access to care, reducing costs, improving patient outcomes, and enhancing patient engagement.

Flexible enough to meet the demands of a variety of patients and clinical teams, RPM has been “associated with a reduction in both ER visits and hospital readmissions, as well as accelerated improvements in quality of life,” according to information from the National Library of Medicine.

With thoughtful and accurate implementation, RPM can be used to improve healthcare quality, access, and patient satisfaction – especially when it comes to caring for women. From fertility and cycle tracking apps to obstetrical care, digital healthcare organisations are “at the cutting edge of a growing market focused on women’s health […with] the potential to reach almost $10 billion by 2024.” Also, according to the American College of Obstetricians and Gynecologists (ACOG), “Medicaid agencies and private payers should urge their participating healthcare practitioners to utilise remote patient monitoring.” The ACOG further states that evidence shows RPM results in decreased “high-risk monitoring visits, while maintaining maternal and foetal outcomes.”

Doctors are more easily able to access real-time analytics, such as a patient’s heartrate or blood pressure, through RPM. These findings are crucial for optimising care for women who are managing chronic conditions. Whether during pregnancy, postpartum, perimenopause or menopause, remote monitoring provides a more efficient and seamless way for important data to be collected by a patient’s care team, without the need for an in-office appointment.

RPM is also popular with older adults, as it permits physicians to monitor patients in their homes. Doctors can use patient portals, which are online applications that let patients interact with their physicians 24/7, to gather information and help their patients. The portals can also share vital signs with physicians, using digital machines so that the treatment plan can be altered accordingly, all without paying a visit to a physical office.

Connecting pharmaceutical companies with high-intent women’s health data

Patient data is more integral than ever to understanding diseases. The pandemic cemented the critical role that quality data plays in diagnosis, care delivery, disease prevention, and medtech/life sciences innovation. As noted in a perspective from the National Institute of Health, one of the key lessons the healthcare industry learned in the US during and after the pandemic was that digital health’s ability to help address the pandemic was dependent on a coherent and accessible data infrastructure.

Despite the advancement of data utilisation, significant strides remain to be seen in women’s health, and there has been a harmful level of female under-representation in health datasets. According to the National Library of Medicine, about 34% of studies across healthcare conditions analyse data by sex. The data disparities, such as the lack of discernment of sex differences across health conditions and incorrect labels of basic women’s anatomy, are creating pronounced gaps in women’s healthcare progress.

Despite the proliferation of wearable technology and femtech companies created to help understand and manage women’s health, the unprecedented amount of whole data sets are drastically underutilised. Furthermore, insufficient collection and analysis of women’s health data leads to stalled research, hindered investment decisions, and eroded improvements in disease-state understanding.

According to the US Department of Labor, women account for 80% of consumer purchasing decisions in the healthcare industry. In order to close the data gap in the women’s health data value chain, a key first step would be reframing the industry-wide definition of women’s health to encompass all health conditions — not solely those related to reproductive health — and emphasising the connection between sex and treatment of diseases. Next, it’s essential for clinicians, researchers, and other healthcare personnel to implement enhanced techniques and infrastructures to collect and analyse more comprehensive sets of sex-disaggregated data. Increased education on sex-specific biology and training on inferred biases is also needed. Lastly, life sciences entrepreneurs and investors can pursue opportunities to finance new projects that focus on improving women’s health data.

Why generative AI is just the beginning

Technology including generative AI can go a long way in improving the collection of correct women’s health data. The use of AI has proven its vast potential to assist providers in countless aspects of patient care and administrative processes, especially in oncology and radiology. For example, in 2020, a team of researchers from Google Health, universities, and medical centres throughout the United States and United Kingdom tested how AI reads X-ray images to detect breast cancer. They built an algorithm and instructed the AI by using X-ray images from nearly 29,000 women with known cancer diagnoses. As a result, the AI model read images better than radiologists, reducing the number of false negatives by 9.4% and lowering false positives by 5.7% on US scans. This is especially significant, given that the National Cancer Institute found “screening mammograms miss about 20% of breast cancers that are present at the time of screening.”

AI also has the potential to empower women with personalised health information, as is the case with Wild.ai, a recently launched app which uses AI-driven data sets from active women to assess their vitals and performance to improve exercise, recovery, and nutritional recommendations. Wild.ai is one of the first tools to include numerous variables that affect health and performance (including age, ethnicity, and various life stages including perimenopause and menopause), addressing the gap in women’s sports science.

The time is now

Effectively using telehealth with other technology such as RPM and AI has enormous potential to transform the way women’s healthcare is delivered and improve access, convenience, and personalised care. While challenges such as gender and research bias, discrimination, and under-diagnosis of common diseases exist, improving technological advancements can address these barriers, opening new avenues for remote women’s care. This will ultimately lead to healthier women and happier families.