Michael Vardi On Why Women’s Healthcare Must Move Beyond Snapshot Diagnostics

Women’s healthcare has often been built on a model that captures isolated moments in time. A single blood test. A single hormone reading. A single clinic visit. According to Michael Vardi, Founder and CEO of Tempdrop, this approach fails to reflect the biological reality it aims to measure.

Source: Tempdrop“Women’s reproductive health is dynamic,” Vardi explains. “When we rely on a single data point, we are capturing only a moment. We are often missing the full physiological story.”

He calls this the ‘snapshot problem,’ a structural limitation that often continues to shape fertility diagnostics. Current clinical practice commonly uses point-in-time measures, including urinary luteinizing hormone tests to estimate ovulation and single mid-luteal phase progesterone measurements to confirm it. These approaches are established in standard care, but Vardi believes they capture isolated moments rather than the continuous hormonal dynamics of the menstrual cycle. 

In other areas of medicine, care has already moved toward continuous monitoring. Diabetes management increasingly uses real-time glucose data to track patterns and guide treatment, while cardiology relies more on ongoing monitoring tools to detect irregularities and improve long-term care. Vardi argues that reproductive healthcare is overdue for the same transition.

“The standard of care across medicine has shifted toward continuous remote monitoring,” he says. “Fertility diagnostics have yet to fully make that shift.”

The reason lies in the nature of hormonal activity. Hormones shift in coordinated phases across the menstrual cycle, shaping ovulation and the luteal phase. These changes are reflected in basal body temperature, which typically rises after ovulation due to progesterone and creates a clear biphasic pattern over time. 

“Tracking over time reveals patterns that a single test could miss,” Vardi explains. “It helps clinicians see how the system is functioning, not just whether a single threshold was met.”

He points to the limitations of standard timing protocols as a key example. The widely used ‘Day 21’ progesterone test is based on a standard 28-day cycle that, in his view, does not reflect the variability of most menstrual cycles. When ovulation occurs later, testing can occur too early, leading to results that may be misinterpreted in clinical practice. 

“If ovulation does not occur when expected, the interpretation of the test can be flawed,” Vardi says. “This is how subtle conditions often go undetected.”

According to him, these nuances matter. A single progesterone measurement can confirm ovulation when properly timed, but Vardi notes that it does not fully reflect the overall function of the luteal phase. Clinical guidance notes that luteal phase deficiency may be associated with infertility and recurrent pregnancy loss, although its diagnosis remains complex and debated in practice. 

“To detect these signals, we need longitudinal data,” Vardi notes. “We need to see the full cycle as it unfolds.”

He believes the emergence of wearable technology is beginning to close this gap. Advances in remote patient monitoring have enabled continuous collection of physiological data outside clinical settings. In reproductive health, this has led to wearable devices that measure basal body temperature overnight and capture longer-term temperature patterns associated with menstrual cycle changes. 

“Accuracy has always been the barrier,” Vardi says. “Clinicians have been right to question consumer devices that rely on peripheral temperature, which is highly sensitive to environmental factors.”

Recent research has begun to address this concern. A 2025 validation study partnered by Tempdrop analyzed nearly two hundred cycles using a continuous axillary temperature sensor. The findings demonstrated that the device could identify ovulation with comparable accuracy to established methods, while also confirming the hormonal patterns that follow.

“The data shows that continuous monitoring could reach professional standards,” Vardi explains. “It can help move reproductive tracking from estimation to measurement.”

According to him, the implications extend beyond technology. Continuous monitoring is changing how care is delivered. It gives clinicians access to longitudinal data collected outside the clinic, offering a more complete view of physiological patterns over time and reducing reliance on patient recall between visits. “Instead of working with incomplete information, clinicians can review months of structured data,” Vardi says. “They can evaluate how a cycle responds to treatment and adjust care with greater precision. Better data creates better conversations. It allows patients to advocate for themselves with confidence and clarity.”

He emphasizes that this has direct implications for diagnosis. Conditions such as Polyendocrine Metabolic Ovarian Syndrome (PMOS), endometriosis, luteal phase dysfunction, and unexplained infertility often involve variable and complex physiological patterns. Continuous monitoring can help identify longer-term trends that are not always visible in isolated clinical measurements.

“Many of these conditions develop over time,” Vardi says. “When you have continuous insight, it can help identify changes earlier and to intervene sooner.”

He also highlights the broader value of aggregated data. As more women engage with continuous monitoring, Vardi believes anonymized datasets could contribute to research, advancing the understanding of women’s health at scale.

The future of reproductive healthcare, in Vardi’s view, is rooted in this transition from reactive to proactive care. “Continuous monitoring empowers both clinicians and patients,” he says. “It could help transform the menstrual cycle into a measurable vital sign.”

Technology plays a central role in this shift, yet Vardi emphasizes that its purpose is to support, not complicate, the user experience. Wearable solutions are designed to integrate seamlessly into daily life, collecting data passively and allowing it to be shared with clinicians, partners, or support networks when needed.

“The goal is to reduce friction,” he explains. “Technology should work with the body, allowing the data to speak without adding pressure.”

He encourages women to begin tracking ovulation and understanding their individual patterns as a first step toward more informed healthcare. Knowledge, in his view, is often the foundation of better outcomes.

He believes women’s healthcare should evolve into a collaborative model built on continuous evidence, where patients and clinicians work together with shared insight.

As Vardi says, “The era of snapshot diagnostics is coming to an end. The future is continuous, connected, and grounded in real physiological data. If women understand their cycle, they can engage with their health in a completely different way.”

This article is for informational purposes only and does not substitute for professional medical advice. If you are seeking medical advice, diagnosis or treatment, please consult a medical professional or healthcare provider.