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Basic implementation of an incentive layer used to allow practitioners to send incentives to patients.

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lindanimfeka25/IncentivesMVP

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Build Status

Public health incentives and health data analytics platform.

Screenshot of the ribbon MVP

Features

  • Ratings : Patients can rate practitioners and penalize them or reward them based on their interaction. This allows governments to find problem zones and allow for better service delivery.

  • Incentives : Ribbon pays patients to complete health tasks. This incentivizes good behavior as well as helps local economies earn enough to feed their families.

  • Analytics : Healthcare data is taken with a patients permission. That data is then analysed and sold to pharmaceutical companies to help them better understand the African market. From the funds received it will be put back into the system as incentives.

  • Decentralized : Ribbon uses smart contracts and IPFS technology to decentralized the information storage to allow for better security and no upfront infrastructure costs.

  • Crowdfunding : All healthcare programs can be crowdfunded or privately funded.

Getting Started with Ribbon

Prerequisites

You're going to need:

  • Linux, Windows or macOS

  • AWS Amplify

Getting Set Up

  1. Clone IncentivesPOC to your hard drive with git clone https://github.com/RibbonBlockchain/IncentivesPOC.git

  2. cd IncentivesPOC

  3. Initialize and start the IncentivesPOC to run locally:

# Run this to run the app locally

npm install

npm run serve

You can now see the POC at http://localhost:8080. Whoa! That was fast!

Our Partners

You can view more on our website.

Questions? Need Help? Found a bug?

If you've got questions about setup, deploying, special feature implementation in your fork, or just want to chat with the core team, please feel free to chat to us on our Slack!

Found a bug with the app? Go ahead and submit an issue. And, of course, feel free to submit pull requests with bug fixes or changes to the dev branch.

Contributors

Thanks to the following people who have submitted major pull requests:

Special Thanks

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