Wednesday, November 1, 2017

From Vendor-Centric to Patient-Centric Data Stores

There is growing consensus that patients should be owners and stewards of their personal health and healthcare data. They should also have the right to control access to chosen healthcare professionals, institutions, and researchers. Current information systems in the healthcare system do not facilitate this point of view, as data is for the most part stored in the siloed systems of the places where patients obtain care.

If we accept the view that patients own their data and can control access to it, how do we facilitate the transition from provider-centric to patient-centric data storage? Such an ecosystem will require new models for data storage and its access. Existing business models for clinical systems will need to adapt to this new approach, although new business opportunities will emerge for companies and others that can succeed in this new environment.

My own view is that every patient should have a cloud-based data store to which they (or a designated surrogate for minors or those unable to give consent for access) allow access to designated healthcare providers or others. A new business model will emerge for companies that facilitate connection of authorized systems to a patient’s data. Even existing electronic health record (EHR) vendors could participate, especially as many of them are building large data centers and cloud-based solutions (although will require changes in their current business models away from their keeping the data in their silos).

The market for this approach will necessarily have some regulation, most likely from the government. Those participating will need to adhere to a common set of standards. Systems will also need to maintain the integrity of data deposited by clinicians. Patients should be allowed to annotate data, and even challenge it, but not modify it (unless the clinician amends it).

This has implications for EHR systems of the future. The current large monolithic systems will need to give way to those that access data in a standardized way. The new EHR “system” may not look much different from current systems (although hopefully will), but instead of accessing data from within its own stores, it will instead pull and push back data from the patient’s designated store.

A recent Perspective in JAMA lays out three necessary components for this vision to succeed [1]. The first is standard data elements. Among the approaches likely to achieve this are initiative such as SMART on FHIR [2] and the Clinical Information Modeling Initiative (CIMI) [3, 4].

The JAMA piece posits a second required component, a standard data receipt for each clinical encounter, with push of the encounter into the patient’s data store. Methods such as blockchain may facilitate the integrity needed to maintain the sanctity of the clinician's input.

Finally, the third is a contract (I may have preferred calling it a compact) that sets the rules for access and control for such a system.

One question the JAMA piece did not was address was, who pays? This is never an easy question in healthcare, since patients do not pay directly for many things. Instead, their insurance pays. So a conversation will be necessary to determine how such a system is financed.

As with many aspects of informatics, the technology to implement all of this currently exists, and the real challenges are how to create the market and the regulations for this major transition in how patient data is stored and accessed. As with all developments in informatics, there will be “unintended consequences” along the way that will need thoughtful discussion among all stakeholders in this endeavor.

References

1. Mikk, KA, Sleeper, HA, et al. (2017). The pathway to patient data ownership and better health. Journal of the American Medical Association. 318: 1433-1434.
2. Mandel, JC, Kreda, DA, et al. (2016). SMART on FHIR: a standards-based, interoperable apps platform for electronic health records. Journal of the American Medical Informatics Association. 23: 899-908.
3. Oniki, TA, Zhuo, N, et al. (2016). Clinical element models in the SHARPn consortium. Journal of the American Medical Informatics Association. 23: 248-256.
4. Moreno-Conde, A, Moner, D, et al. (2015). Clinical information modeling processes for semantic interoperability of electronic health records: systematic review and inductive analysis. Journal of the American Medical Informatics Association. 22: 925-934.

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