- Public and private partnerships: Big Pharma learns to play nice
- Patient-powered research networks: a home advantage
- Startups: Molding open data into a viable business model
- Outlook and key takeaways
- About Cindy Waxer
- About Gigaom Research
Ever since President Barack Obama signed the Open Data Executive Order in May 2013, government agencies have been releasing treasure troves of once-buried information. The Department of Health and Human Services alone has made available more than 1,000 live data sets on HealthData.gov over the past three years.
This free exchange of data between the federal government and the public, often referred to as “open data,” has given rise to an innovation economy as more and more businesses turn bits and bytes of public data into fresh revenue streams. From SEC filings to weather patterns, multimillion-dollar corporations and startups alike are using open data to generate revenue and develop new products and services.
Although known for keeping its proprietary research findings closely under wraps, the health care industry is quickly embracing the economic value of open data. Companies are beginning to recognize the market value of shared information and how to monetize such data, and health care players are making open data as much a part of their business models as they are for slick marketing campaigns. But for an industry that still relies on fax machines to deliver release forms and test results, there are plenty of challenges ahead.
For one, there has yet to emerge a single, predominant paradigm for unleashing the economic value of open-health data. Currently there are three primary business models displaying real potential. These include:
- Public and private partnerships. Drug companies, non-profit organizations, and private corporations pool their resources for the sake of faster drug discovery and greater sample size. Examples include the Health Data Consortium, Yale University Open Data Access Project, and Accelerating Medicines Partnership.
- Patient-powered research networks. Patients contribute personal observations and test results to web-based platforms, including information that is then packaged and sold to third parties. Examples include PatientsLikeMe, MS Patient-Powered Research Network, and Patient-Centered Outcomes Research Institute.
- Startups. Newcomers apply proprietary algorithms to slice and dice government data for profit. Examples include Aidin, PracticeFusion, and Doximity.
While each of these companies differs from the next in terms of target audience, mandate, and financing, all face some common hurdles ahead including how to keep patient data secure, how to protect patient privacy, and how to tidy up reams of messy government data.
Thumbnail image courtesy of Steve Hamblin/Fuse/Thinkstock.