eBay for Patient Data

Enormous amounts of patient data creates big business opportunities. In fact, some day, patient sick care might be a loss leader. Instead, the revenue model will be patients owning data and using a platform to sell it for a price. Patients will become digital health entrepreneurs.

Selling your sick care data is called an “edge opportunity”.

We are headed in that direction.

1. Blockchain technology could make it easier for patients to own their data and share it , or sell it, with anyone they choose
2. Third party data science companies will churn submissions and deliver information and actionable intelligence as a service
3. The FDA will change how it regulates software as a device, data as a service and intelligence as a service
4. Online platforms will broker the two sided market between the buyers and patient sellers of data
5. ICOs will cater to data sellers in exchange for cryptocurrencies
6. Public databases that are open to data and biomedical scientists will be open for research, much like present genomics data bases run by public agencies like the NIH and NCI
7. Data entrepreneurs will translate publically available databases to commercial products
8. Data selling and the resulting revenue will be a new employee benefit for those working for self insured corporations, unions or other entities. Patient reported outcomes will one of the data sources along with the internet of medical things.
9. Value based care intermediaries will create a new revenue model
10. The sick care data value chain will evolve and get more complicated. It will start with patient owned data and eventually be bought and sold though a series of value added steps by intermediaries. Here is what it looks like:

• Discover: In today’s digitized world, there are many sources of data that help solve business problems that are both internal and external to organizations. Data sources need to be located and evaluated for cost, coverage, and quality.
• Ingest: The ingest pipeline is fundamental to enabling the reliable operation of entire data platforms. There are diverse file formats and network connections to consider, as well as considerations around frequency and volume.
• Process: Many applications are well served by processing data immediately following the ingest stage, to transform the data into a format that facilitates its reuse or to take immediate action based on incoming events.
• Persist: Cost-effective distributed storage offers many options for persisting data. The choice of format or database technology is often influenced by the nature of other stages in the value chain, especially analysis.
• Integrate: Much of the value in big data can be found from combining a variety of data sources to find new insights. Integration is a nontrivial but valuable step in which this combination process occurs.
• Analyze: The star of the big data show—analysis—depends critically on every other step in the value chain—the so-called data janitorial work that makes up 80 percent of data science. New insights and actions are derived from data, enabled by an ever-growing and nuanced choice of tools and platforms.
• Expose: The results of analytics and data that are exposed to the organization in a way that makes them useful for value creation represents the final step in deriving value from data.

11. We will need to address the societal and ethical implications. Who rules AI? There are three basic challenges: data protection requirements, minimizing biases and transparency.

12. Silicon Valley startup Open Health Network, which develops AI-based applications for healthcare organizations like UCSF, Sanofi and Cornell University has launched a new product meant to use blockchain technology to allow patients to manage and monetize their medical data. If successful patients will be able to sell their assets on the PDX. a NASDAQ for patient data.

Of course, there will be a dark side to all of this. Every time shoppers return purchases to Best Buy Co. , they are tracked by a company which has the power to override the store’s touted policy and refuse to refund their money.

That is because the electronics giant is one of several chains that have hired a service called The Retail Equation to score customers’ shopping behavior and impose limits on the amount of merchandise they can return.

Will patients be refused services for “abusing” the system, or doctors refused payment because they take care of them? Aetna already tried that, but had to back off after the backlash.

Airlines might charge you based on your online shopping history. Will the same thing happen to your sick care insurance premiums?

Nearly one in five employees in the healthcare field said they’re willing to sell confidential data like login credentials to unauthorized parties, a new survey from Accenture claims. Nearly one quarter of the survey’s respondents said they know someone in their organization who has sold their credentials or access to an unauthorized outsider.

A bid and asked sick care data revenue model is inevitable.What would you charge for your data ? What’s in your iPhone?

Image Credit: Pixabay

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Arlen Meyers, MD, MBA is the President and CEO of the Society of Physician Entrepreneurs at www.sopenet.org and co-editor of Digital Health Entrepreneurship