Applying the Freemium Model to Patient-Facing Health Information Technology

Last week, I read Uwe Reinhardt’s final book, “Priced Out: The Economic and Ethical Costs of American Health Care.” Uwe compels the reader to consider the larger implications of historical and current decisions made by the government, employers and individuals to pay for healthcare in this country. When you include the challenges that surveillance-based business models bring to an online platform, the opportunities to do something innovative with health information technology that might move the entire industry forward seem vanishingly small. The transfer of Tumblr from Verizon to Automattic offers a view of what might be possible.

Veinot et al. suggest that information and technology companies could provide additional value across at least 10 different dimensions:

  • Collection and display of information
  • Customization of information
  • Education
  • Mediation of communication
  • Support or prevent workflows and activities
  • Framing and support of decisions
  • Social coordination
  • Optimization of resource allocation
  • Identification of patterns and anomalies
  • Prediction of outcomes

Many of these functions rely on users operating under the assumption that the platform does not monitor their activities with the intent to sell that activity to interested buyers. Even subscription-based business models augment their revenues with surveillance activities (e.g., New York Times). But the HIPAA Privacy Rule mandates a higher level of transparency around personal health information disclosures.

How does any of this link to Tumbler and Automattic? A freemium model for managing personal health information might address the challenges of working across Medicare, Medicare and commercial groups. The “base” model might include a way to request and store medical records across health system interactions. The lowest tier might also provide a method to display health summary information to interested parties in case of a medical emergency. A second tier could allow for 1) a claims-based record locator service to request medical records in real time, 2) automated communication with a primary care provider and family members and 3) facilitating behavior change. Higher tiers might enable interactions with other services (e.g., telemedicine, medical tourism). Users at any tier might have the option to share their personal health information with third-parties to have those entities pay for higher tier functionality.

The more egalitarian among us might expect a high level of anonymity within the base model, but given the money consumers spend for privacy in other Internet domains (e.g., Apple smartphones instead of Android ones, secure sockets layer [SSL] certificates, ProtonMail, Boxcryptor), this differentiator may need to be reserved for higher tiers to ensure a start-up’s financial viability. The platform could allow entities to connect to the user’s records with revokable consent. Some privacy-based functions might include: sharing personal health information and health behavior information under a pseudonym, using different aliases to connect with different healthcare entities, and parsing medical records to segregate different elements of a user’s medical record (e.g., data related to a sexually-transmitted disease, family history or drug use).

Who might build this freemium-based health information platform for consumers? Many existing members of the healthcare marketplace may not be considered trustworthy by consumers or their caregivers. Nundy et al. outlined three components for trust: competency, motive and transparency. (disclaimer: I’ve submitted a manuscript to a medical journal with Shantanu). Healthcare providers, payers and employers may all seek to exploit the information within such New entrants may struggle to secure enough capital to build a minimum viable product. An employer consortium, workers’ union or state government might see enough value in funding a start-up to help users manage their healthcare records over different care settings across different employers.

Each health information technology start-up has its own target audience and business model. The dynamics of the American healthcare system demand solutions that transverse different payers (within and across the Medicaid, Medicare and commercial domains). The freemium model may help innovators consider ways to deploy specific functions within a product roadmap that retains early adopters while encouraging the late majority to try the technology.