Health data is booming, but clarity on what it means is lacking
Investor Aryeh Ganz argues that wearables, glucose monitors and blood tests generate large amounts of data, yet no standardized processes explain what the results mean. He says the value of data depends on whether it leads to better decisions and improved health.
Aryeh Ganz, managing partner at health investor Cornucopian Capital, writes in an opinion piece that measuring human biology is becoming more accessible, but interpreting the results is lagging behind. Cornucopian Capital invests in companies developing novel foods, therapeutic platforms and technologies that measure the body in real time. The article was published by AgFunderNews, a site covering agriculture and food technology, and reflects the author's own views.
Data without explanation
Wearables, continuous glucose monitors, more accessible blood tests, genetic information and advanced diagnostics give ordinary people information that once required a clinical setting. Ganz sees this as an important step from episodic treatment toward preventative, personalized care. However, there is still no consistent, standardized way to tell consumers what their biomarker readings actually mean.
This is already affecting healthcare. In a Doximity survey of roughly 200 physicians earlier this year, two-thirds said patients brought results from direct-to-consumer health tests to appointments. Fewer than 10% said their institution or professional organization had well-defined guidelines for handling those results. Some patients had turned to Google or ChatGPT to interpret them.
Precision is not the same as meaning
The author points to continuous glucose monitors, which people without diabetes increasingly use for wellness. As The BMJ reported, glucose fluctuates with food, exercise, stress, sleep and hormones. A device can measure these swings precisely, but it cannot say which ones matter.
Detection also does not automatically mean better outcomes. In an NHS trial in the United Kingdom involving more than 142,000 adults, researchers tested Grail's Galleri blood test, which looks for cancer-related signals in cell-free DNA. Adding the test did not statistically reduce the primary endpoint of combined Stage III and IV cancers, though later screening rounds showed encouraging reductions in Stage IV disease.
The investment angle
Ganz concludes that health data should be judged by what happens after it is collected: whether it produces a useful recommendation, whether someone acts on it, and whether a repeat measurement shows improvement. In his view, the next opportunity lies in systems that connect fragmented information, identify what matters and help patients and clinicians decide what to do. He says AI will play a role in that layer if it improves decisions rather than just producing more sophisticated dashboards.
