How ADLT™ and the Blockchain are Changing the Patient Data Landscape

Date January 22, 2019

Giving Control Back to the Patient!

From its earliest days of identifying Use Cases applicable for the Blockchain, Clinical Trials and Patient Data have always been mentioned as one of the initial areas for decentralized ledger technology. The need for patient and clinical information is so vital to the clinical supply chain yet the process remains ‘broken’ as patients are unable to receive the proper treatment and information that is available, and researchers are unable to receive adequate information in regard to patients and investigators. By today’s standards of technology, one would think that this is a very simple fix with something as simple as a web-based portal or dashboard that all sponsors, patients, and participants can log into for updates and information; however, it’s just not that simple.

When we look at the challenges of the clinical supply chain as a whole, accurate and reliable patient data can truly resolve many of the issues that are consistently forcing trials and studies to take longer periods of time; cost companies and investors more money; and limits the opportunities for patient treatment at any given time. Here are the top 4 Patient Data Challenges iSolve is trying to resolve with ADLT™:

  • The Ability to Securely Manage Patient Data
  • The Ability to Share Data Amongst Trusted Participants
  • The Ability to Access Data for Research, Recruitment, and Knowledge
  • The Ability to Incentivize Patients to Share their Medical Data

There are several factors that need to be in place to have a successful solution. The Blockchain must have a set of governance rules that are consistently executed to ensure security, transparency, and trust are being maintained by participants. These rules will be executed via Smart Contract and will establish a source of truth for the data being managed by the Blockchain. ADLT™ leverages a governance model that is ‘Patient Centric’ and supports democratized patient data. This model places the patient in control of their information by allowing the patient to see where their information is being viewed and utilized. And because ADLT™ enforces permissioned data, trusted participants can query and view de-identified patient data and make ‘Patient Data Requests’ to leverage the information for research and studies.

ADLT™ relies upon governance rules to act as a medium between participants that do not normally share, view or exchange data. These rules provide interoperability between participants and contributors and allows the network to expand beyond the normal reach of any individual participant or contributor. This exchange of information can also be leveraged as an additional incentive to patients seeking information about existing or upcoming clinical trials and treatments.

By establishing the core functionality, the Use Cases and benefits from ADLT™ as a Patient Health Data Exchange, are endless as the scope goes way beyond these initial areas. Imagine an Amazon for patient data or a LinkedIn for patient data whereby patient data is a transferable asset that can be leveraged as a single source of truth in a secure and trusted platform that can benefit all participants of the clinical supply chain from Sponsor to Patient. But it must have a starting point. With ADLT™, we are moving towards a single disease state whereby patients, researchers, providers and pharmaceutical companies can be reached and incentivized to participate. Having a successful deployment, our model can scale to support additional disease states.

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