Blockchain Applications and Use Cases in Health Information Technology

We argue that a public program such as the U.S. Medicaid program with $553 Billion in total program costs and over $25 Billion spent on health information technology and administration last fiscal year could benefit from the use of blockchain based distributed ledger and smart contracts.
2 years ago

Authors: David Randall, Pradeep Goel and Ramzi Abujamra

 

Journal of Health & Medical Informatics

 

Publisher: OMICS International
 
Abstract
 
Blockchain technology and the associated crypto currencies have the ability to transform industries including healthcare. We suggest the decentralized and programmable nature of the blockchain applications can be used to change health information technology to gain greater efficiency in public and private health care systems. Current public health information technology systems such as eligibility, enrolment and electronic health records have documented issues with interoperability and are slow to adapt to changing program and technology demands. We suggest that blockchain can potentially solve these issues. We argue that a public program such as the U.S. Medicaid program with $553 Billion in total program costs and over $25 Billion spent on health information technology and administration last fiscal year could benefit from the use of blockchain based distributed ledger and smart contracts. We finally argue that a decentralized benefits administration system can provide greater efficiency to enrolment, eligibility, claims payment and adjudication processes thus driving efficiency and reducing systemic fraud.
 
Copyright: © 2017 Randall D, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
 

Illustration Photo: IBM scientist Rahel Strässle holds a prototype device called the cognitive hypervisor. Sophisticated wearable sensors can capture rich body-related information such as bio-signals and emotional states. The ability to collect, blend and understand on-body data in real-time promises significant changes to healthcare and related fields. Combining wearable information with data from environmental, and social sources enables to create a sophisticated contextual patient model for early identifying and predicting health-related issues. (credits: IBM Research / Flickr Creative Commons Attribution-NoDerivs 2.0 Generic (CC BY-ND 2.0))

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