Built on 1.3 billion structured data points shared by over 3 million people living with 1,250 chronic conditions, OpenStuff transforms lived patient health experiences into real-time, actionable insights.
More than half of U.S. adults report turning to social media for health information, yet over one-third encounter high levels of misinformation.
Large language models now risk amplifying this problem further, generating highly persuasive but false health content.
In a landscape where patients seek immediate, relatable, and trustworthy answers, the gap between traditional medical sources and the open web has never been greater.
OpenStuff bridges that gap by providing an AI-powered health search that is grounded entirely in real-world patient experiences. Structured, transparent, and continuously updated, OpenStuff ensures insights come directly from people living with chronic conditions — not viral noise.
For the first time, anyone, not just researchers, can explore health questions powered by the voices of people who live with these medical conditions every day. OpenStuff is a unique tool for patients seeking clarity, doctors looking for actionable insights, and researchers eager to accelerate discovery.
Unlike existing medical search engines built on static literature, OpenStuff is powered by large-scale, crowdsourced data that grows, updates, and enriches itself continuously.
This new data category, RWx (Real-World Experiences), captures the lived, structured experiences of millions of people managing chronic conditions.
It complements traditional RWD (Real-World Data) and RWE (Real-World Evidence) by grounding insights in ongoing, patient-reported input rather than retrospective or clinician-entered records.
Every new patient’s voice strengthens the dataset, keeping it fresh and representative. Beyond self-reported experiences, OpenStuff is expanding to integrate wearables, EMR data, geospatial layers, and longitudinal studies, creating a living and evolving resource.
By building the data from day one in a structured, normalized, and consistent form, OpenStuff AI goes beyond simply providing answers about experiences.
It transforms natural language questions into real-time data queries and extends powerful research capabilities to everyone: patients, doctors, and researchers alike.
The platform draws on more than 3 million patient voices and 1.3 billion data points across 1,250 chronic conditions, closing the biggest data gap in chronic care knowledge.
By turning simple natural language questions into sets of real-time data queries, OpenStuff opens the door to research that was previously impossible, instantly, accessibly, and at scale.
“OpenStuff would not exist without the millions of people who generously shared their experiences,” said Yael Elish, founder of StuffThatWorks.
“They are the heart of this platform. By combining their voices with AI, we are making knowledge that was never accessible before available to everyone: patients, doctors, and researchers alike.”
“Having early access to the StuffThatWorks platform has been transformative,” said Donna Hanson, vice president, strategy and optimisation at Advanced Clinical.
“For the first time, we can explore the patient journey — their experiences, burdens, and unmet needs — at a scale and depth previously unattainable.
“The platform puts rich, actionable data directly at our fingertips, enabling us to optimize clinical trial protocols in real time and in alignment with patient expectations.
“The ability to assess standardized patient data in real time is truly game-changing. The platform also allows us to engage patient communities for protocol refinement or to test recruitment and engagement materials, adding a new dimension of agility and precision to trial design.
“While the industry has long aimed to make trials more patient-centric, StuffThatWorks accelerates that ambition by turning weeks or months of patient feedback into insights available in days or even minutes. It’s a meaningful step forward in making clinical research more responsive and patient-focused.”
