Consortium Blockchain a Right Step

Blockchain is a very disruptive technology and if industries do not keep in pace both in terms of its understanding and impact, experimentation and adaptation with changing ecosystem could potentially lead its enterprise leader's fear of missing out (fomo) psyche becoming a reality as it did for brick & mortar companies when they missed the opportunities with the advent of Internet in the early 90’s.

Today, to be on the safer side many enterprises are forming or joining the Consortium and testing their feet not to be left out. Global financial companies lead the way followed by Cross Sector and Life Sciences & health care enterprises.

The significance and ripple effect of Bitcoin Cryptocurrency tsunami which is based on Blockchain made Industry leaders to pay attention bit more closely to its underlying technologies. Blockchain technology is not new, but how the Distributed paradigm of hardware (nodes) including the Distributed Ledger Technology (DLT) has been leveraged coupled with removing the fear of security on identity and the need for an intermediary of controller’s oversight to validate the truth of the transactions.

Smart Contracts implementation on the blockchain with a semi-trust control on transactions validity with heighted identity security by different niche platforms like Ethereum Consotium, Hyperledger Fabric Consortium (from Linux foundation), R3’s Corda, Quorum, Chain Core made it much more enticing for the industry leaders. Not to be outdone, major Cloud vendors including IBM, Microsoft, AWS made these platforms available on their portals along with development toolsets to build and deploy enterprise based applications.

Consortium Blockchain features

1.       Platforms support Privacy and Confidentiality for all the participants in the network

·         It is built on trust where participants know that all of their transactions can be traced

·         All network participants identities are backed with cryptographic certificates that are tied to its Organizations, network components and end users or client applications

·         Blockchain supports all business exchange of assets of tangible (Cars, Whole foods) to intangible ones like Futures, Intellectual properties etc

·         Only known participants can participate in the transactions thus it is private and permissioned system

2.       Distributed Ledger records transactions are built in a decentralized and collaborative way

·         Transactions Assets are defined using a collection of key value pairs (JSON) with digital signatures of every endorsing peer node with values that can be encrypted

·         Ledger is a sequenced, tamper-resistant record of all state transactions chained together in blockchain with one ledger per channel and making it immutable

·         Each participant will have their own replicated copy of the ledger besides being shared with its participants

·         There is a single place of Origin for all transactions in the blockchain to provide provenance for the transactions

3.       The ledger functions and control are implement using Smart Contracts to automate and execute mutually agreed upon by the participants

·         Privacy is key for B2B model and this is implemented using Smart Contracts and Channels

·         Smart contracts are written in chaincode which enforces the business logic in defining assets and transactional logic

·         Channel’s ledger contains a configuration block defining policies, ACL and other pertinent information

·         Major programming languages like C++, GO, Java, JavaScript are used to program the chaincode

4.       A process called Consensus is used to commit the transactions only on approval by the appropriate participants

·         Consensus allows for transactions to be synchronization across network thru this process with shared data ledgers as well shared programs that update them

·         Transactions are written in the order in which they occur in this consensus process to avoid any malicious entries

·         Transactions are committed only when the block’s transactions have met the explicit policy criteria checks and balances dictated by the members and endorsed, validated and versioned checked

·         Consensus mechanism utilizes different technology messaging brokers like SOLO, Kafka, Simplified Byzantine Fault Tolerance (SBFT)

Use Cases

There are many uses that are identified in various industries including Capital Markets, Financial Services, Healthcare, Government Legal/Regulatory, Insurance, Supply Chain Logistics, Anti Counterfeiting, Travel and these are in various stages of implementation, development, design and PoC’s. Here are some:

Healthcare: 

1. Large Pharmaceutical companies are using Consortium blockchain platform for their clinical trials to overcome its higher cost and meet Government regulations. Clinical trials involves data collection and its management in timely fashion from patients, physician offices, recruiters and research centers spread around vast geographical areas.
2. Medical Insurance claims is a 3 trillion dollar US healthcare market but still utilizes 40 year old EDI paying value-added services in validating the transactions along with a significant percentage of clerical staff processing the paper input to service long tail of small scale providers.

Supply Chain Logistics:

This use case is an ultimate for Blockchain implementation. There are two key dimensions that are required in any Supply Chain from its creation to end-delivery. 

• End-to-End traceability with ability to trace back to its Origins which potentially increases with complexity of the product in varying degrees 
• Identifying passage and impact of laws and regulations influencing the product’s journey

The complexity can further compounded when supply chain has to trace assembly of these products into SKD’s and into final product. Imagine If I extend the thought process to trace including installation issues, repairs, upgrades, warranties etc. 

Capital Markets:

Currently 26 member Japanese financial institutions have successfully implemented Internationally OTC (Over –the- Counter) derivatives using blockchain to apply master agreement without a need to renegotiate with counterparty thus improving transparency and simplifying data management.

Recently Credit Suisse and ING completed the first live securities lending transactions valued EUR 25 million using R3’s Corda Blockchain platform.

Conclusion:
A methodical study, evaluation of a disruptive and revolutionary paradigm such as Blockchain Technologies to its current landscape of ecosystem has more promises than failures.

FHIR a Strategic Initiative for Healthcare Providers to build Clinical Data Repositories

Today’s Hospitals are collecting vast  amounts of data from their day to day operations on Patients like Clinical Observations, Conditions, Encounters, Medication, Pharmacy, Imaging including vital signs using sensors to support both Operational and Research requirements. They are also looking at ways and means to map their internal data with external data which conform to some standards for ease of mapping and contextualize the data.

However the major problem they face is in their inability to combine the data from multitude of silos created by different applications for any meaningful and well-rounded analysis either for research perspective or to support any policy decision making or provide better and cost effective analysis to improve Patient care.

Many major hospitals have built healthcare data storage repositories in their native format with metadata tags to identify the context of the data what they call Data lakes which can be queried and extracted based on questions they wish to answer.

The success and utilization of these Data lakes depends upon how lighter they have been designed and built in comparison to dark data silos and to minimize its inherent drawback limitations to address questions such as; how the data was brought in; how and where it can be found; how to explore; and what and how it needs to be transformed to be of use. This task of identifying, preparing, combining several data sets from different hierarchical depths is equally challenging for a NON-IT-STAFF members like Researcher and Business users if not equally easy for the IT folks without Health Domain knowledge.

What and How FHIR (FAST Healthcare Interoperability Resource) an Open Industry Standard from HL7 comes handy to elevate such and many other bottlenecks?

HL7 a Non Profit Organization accredited in building Healthcare Standards, introduced FHIR (pronounced as “FIRE”) www.hl7.org/fhir/ . 

Healthcare providers have been using various HL7 Open Standards for Exchange of Information in the past since 1987 like HL7 V1, V2, V3, CDA, CCDA. FHIR Framework standards were written to address various pitfalls of their earlier specifications and standards and also keeping in view advances in IT technologies that can be leveraged for its effective implementation.

FHIR is the new Open standard getting lot of traction in the Healthcare Industry that has defined more than 180 Granular and Normalized Entities with attributes with defined formats. These “Containerized” entities are called Resources and in NoSQL World called Collections and its rows as Documents. FHIR also provides RESTful API protocols for exchanging of information between legacy healthcare systems and for integrating with different application systems. 

The common data format standard used in FHIR are XML and JSON. The concept 80/20 rule is applied when Industry identified these distinct resources in the current draft of HL7 Version 3.x from value proposition to mean 80% of the Clinical data needs can be accomplished using 20% of the Resources identified by the Industry.

These FHIR Resources are grouped under various heads such as Individuals (Patient, Practitioner, Person, Group), Diagnostic (Observation, Specimen, ImagingStudy), Medications (Medication, Immunzation, MedicationRequest),  Care Provision (CarePlan, ReferralRequest, RiskAssessment), Management (Encounter, EpisodeOfCare), Workflow(Appointment, Schedule, Task) for Clinical data sets and many more to support Financial Domain Coverages like Billing, Payment and various Specialized Health Research domains.

FHIR Specifications and Standards are exhaustive and detailed and provides standards how Profiles and Extensions for Elements and Data Types can be extended for attributes in Resources and to combine Resources for different Use Cases.

The most conspicuous benefits of FHIR is the ability to  build a conformed standardized yet unified view of common data sets/documents that are interoperable and shared with precise definitions both internally and with external systems and vendors.

The other benefits includes its support for Clinical Terminologies and Ontologies for SNOWMED, ICD9/10, LOINC and other Open Standards thus avoiding to design a separate Terminology Services with Codes for Lab noting’s, Diagnostics, Medications, Imaging and others.

Lastly, the most important one for me, FHIR Resources can also be presented in an RDF format (Linked Data) specification by serializing property information using Turtle format or as JSON-LD and presenting data in RDF (Resource Description Framework) data model to support Graph DB. A RDF Graph DB(SPARQL)  can help and enhances Healthcare provider’s ability to identify complex patterns of relationship in real or near real time that could save lives and decrease costs to Patients.

FHIR Implementation

FHIR can be implemented in a phased manner depending upon how many different domain repositories and areas of interest that Healthcare provider intends to build and leverage insights. HL7 also provides HAPI pronounced “happy” a JAVA based health care package library to enable adding FHIR messaging to your applications in building different FHIR Resources.

NoSQL Database

Todays, Key Value store are the norm for its flexibility in building a schemaless and horizontally scalable databases that supports object oriented paradigm. To this add performance compared to RDBMS as you scale up data volumes into billions of rows or terabytes/petabytes data and also to meet high demand throughput with low latency traffic there is no next best alternative to NoSQL.So In my opinion, a NoSQL data store is a perfect match for FHIR.

Conclusion: Containerizing data using FHIR Standards as Resource Types (Collections/Documents) from Data Lakes, HL7 Messaging into a NoSQL Database work as a self-contained, documented, standardized basic building blocks which can be readily utilized by both Research and Business Users to meet their Operational and Research needs with ease.