Dawn of Decentralized Model

It is not a doubt that Blockchain is one of the fascinating technologies of the 21st century. Some of its key features such as decentralization, consensus, immutability and trust-less make it an ideal distributed ledger that can be applied in different economic as well as social sectors to solve a variety of problems.

Despite its dominance in cryptocurrencies, its application in the healthcare sector has of recent years gained popularity of significant magnitude. This has been fueled further due to the recent introduction of Cura Network; comprising of patients and healthcare providers. It’s through this that has led to the dawn of a decentralized model which enhances privacy-preserving blockchain predictive modeling algorithms framework in healthcare data.


What is the decentralized model?

This could sound complicated, yet it’s a very simple concept that I am sure every person would love to understand. The decentralized model implies a distributed network of block records occurring from peer-to-peer without intermediaries. For instance Figure1 (b) below illustrates an architectural topology of the decentralized model. In this model, the verification of healthcare data records is achieved through proof of work.

An institution that adopts this model enjoys advantages such as no risk of data loss, open for the public to join freely as there is no restriction from a central server. This data can be exchanged directly without necessary tracing back records from other sources or institutions which could alter, lose or confuse the health data. This is the model CURA NETWORK has adopted and putting its best to mitigate the weakness of traditional central topology.


Figure1: A diagram showing both centralized and decentralized architectural topology

decentralized model


How does decentralized model work?

The model uses the artificial intelligence of an online machine learning blockchain algorithm. The machine can initiate peer-to-peer network that utilizes metadata in disseminating partial models, the hash of the model, and error of the model of required Meta information.  This model enables integration of privacy in the data being shared to a participating institution that agrees to adopt a similar model.  Some of the advantages that make a decentralized model be preferred as opposed to traditional models include:


  1. Build upon the existing health IT infrastructure.

Decentralized model uniquely blends with the existing IT infrastructure with health records such as Clinical Data Research Networks (CDRNs) and VA Informatics and Computing Infrastructure (VINCI) which forms the basis of blockchain backbone in decentralization; the infrastructure can efficiently retrieve from the existing patient data stored in the infrastructure whenever it’s required.

  1. Maintain modularity.

Unlike conventional client-server architecture, the decentralized model applies the peer-to-peer concept which enables a different site to remain modular and at the same time inter-operating with other sites. By adopting a decentralization model in keeping and storing healthcare data, this enables each institution to independently decide on the policies regarding the handling of patient data.  Also, blockchain puts the participant at liberty to freely join or quit the model; a feature that enhances modularity for parties using the decentralized model.

  1. Privacy and security protection in all aspects of interoperability.

Is privacy not everyone’s concern when it comes to patient-data sharing? Certainly, the answer is YES! Cura Network; The Global Decentralized Health System has been designed to facilitate the exchange of any healthcare data and able to achieve privacy-preserving interoperability.


DecentralizationIn summary, it is therefore very necessary for current healthcare institutions to adopt a decentralized model especially when it comes to data security issues regarding healthcare. Thus the dawn of decentralization is slowly revolutionizing the healthcare sector and upon full adoption be a solution to long-term challenges involving healthcare data that have existed for centuries.