Distributed Ledgers, the next step in Patient Generated Health Data (PGHD) including Environmental data

Soon we will be able to access thousands of datapoint into our lives, many will reflect our environment and health.  The HHS Idea Labs held a Entrepreneur-in-Residence webinar on December 13, 2016, for recruiting an software architect to assist the National Institute for Occupational Safety and Health (NIOSH) in collecting employment data as it pertains to a persons health.  They wish to share/store the collected data in the EHR.  Onerous at best, because most EHR today do not have API for uploading data and HL7 standards do not currently provide for discreet PGHD data. Why,  environmental data or other types of data that affect or is collected by the patient isn't considered clinical.  I am not saying this is a bad thing, for in data design, it is best to segregate data, especially large data sets.

The webinar panel mentioned FHIR, the REST API from HL7.  Currently FHIR datagrams are based on HL7 V2 which is not designed for PGHD (Patient Generated Health Data).  We are trying to use old technology and clinical standards for collecting and storing PGHD and IoT data .  If we are bound to the aging EHR design and HL7 clinical protocols, it will be impossible to develop a solution that will support the ever growing data lake, which is being collected.

We need a system that can collect, store and analysis IoT data or data from anywhere and anything that come in contact with the patient.  A distributed, secure solution, one which provides transparency and is patient controlled.  The solution is available now, the distributed Ledger, the database that support Blockchain.  Distributed ledgers store transaction data and distributed database like Cassandra store the payload.  This solution already provides a standard for sharing, securing and providing transparency for transactions such as data events.

This solution would allow EHRs, the client, to access the patient's data anywhere and anytime, using the credentials provided by the patient. All systems that affect or interact with a patient health could have permission to write into the ledger. An Example; NIOSH in 2004 published a toxicity Alert about employees that worked with popcorn flavoring. If workplace sensors data was supplied to the employees EHR, a doctor or an analytic platform could detect or predict issues such as obliterative bronchiolitis within patients.  NIOSH recently published another paper on a simular issue in coffee processing facility.  Consider the cost saving that could be realized if we could detect environmental issues in patients before the become health issues.

I am proposing using distributed ledgers as a secure reference and storage of patient IoT data.  EHR's would not have to change their structure. Vendors could consider a ledger as a third party solution with an exposed API for easy integration.   Analytics platforms could analysis data in background, searching for correlation within the data.

This solution could also be used to share patient data in a secure manner, solving the interoperability issue.  EHRs, with the patient's permission could share credentials, which would allow other systems or doctors to access that data. Since distributive ledger solutions are based on transparency, transactions would be saved as a chain-of-custody paradigm, providing non-reputable single point-of-truth.

Cloud based distributed ledgers can provide a ubiquitous shared database solution that will not impact a EHR or organization's health systems by adding new types of data or interfaces.  It will allow for a forward path of growth in health and science without compromising organizations security or patients privacy.