Data: The World’s Most Precious Commodity

In the 21st Century, data is the raw material upon which all value-added transactions depend.  Manufacturing, finance, transportation, energy and countless other industries all heavily rely on data to innovate, compete and indeed survive.  This is nowhere more true than in healthcare.  The $60 billion healthcare data market is growing at over 11% per year. ¹  

The largest consumer of data will be AI, if it is not already.  Indeed, AI is fast running out of training data. ² This puts a premium on private sources of relevant and high-quality data.  As with all raw material, clear proof of data ownership is critical.  

Who Owns That Data?

Failure to establish data ownership invites litigation, and the inability to successfully monetize or otherwise use it.  For example, in December 2023 the New York Times sued OpenAI and Microsoft for copyright infringement, seeking billions of dollars in damages. ³

This month, Thomson Reuters won a landmark AI copyright infringement case.  The federal court held that the defendant used content from Thomson Reuters to develop a competing AI-driven legal research tool.  The judge ruled that the defendant’s actions did not qualify as "fair use" under U.S. copyright law.  This landmark decision underscores the legal protections surrounding the use of copyrighted materials in AI training and development.

This Is Yet One More Challenge For “Big Data” And Healthcare AI Models

AI in medicine is already here, and will only become more pervasive.  However, the data on which AI healthcare models train is typically of poor quality.  Problems include incompleteness, inability to audit original sources, no or irrelevant clinical context, data “cleaning” and other unknown manipulations, irreconcilable data conflicts, no correlated outcomes measures, and stale or undated information.  

Most of today’s $60 bn. data market represents the exchange and repackaging of such “big data”. ⁴ AI error rates and “hallucinations” are thus not only inevitable in most AI healthcare solutions, they are dangerous in specific applications such as clinical decision-making. ⁵  

But now there is a deeper problem – who owns the various bits and pieces of data making up a “big data” dataset?  EMR companies, medical society registries, hospital systems, researchers, payers, AI start-ups are among the many entities who may have contributed and will claim ownership.  The weaknesses of “big data” structures, coupled with competing ownership claims, will make it an increasingly unattractive choice for healthcare data consumers, including AI models.    

The Circles Solution

RegenMed’s Circle datasets are generated and maintained in a closed system which maintains their coherence, transparency, and auditability.  They are high-quality – both statistically and clinically significant – with clear ownership and monetization rights vested in the dataset creators.

Real world data is likely to become one of the most critical categories of all healthcare data.  It will be key to supporting value-based medicine, lower costs, faster lab-to-bedside clinical translation, and health equity.  RegenMed is well positioned to capture a significant portion of this market.

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