Health Monitoring and Risk Management: 6-Week PoC

WaveAccess2

Customer health monitoring and health risk management platform for healthcare and medical insurance: 6-week proof of concept

Having delivered complex AI projects in healthcare and medical insurance, WaveAccess offers developing a proof of concept for a custom-made health monitoring and health risk management solution that is hosted in Azure Cloud, making it easily scalable and requiring no physical infrastructure. It processes data using machine learning and provides up-to-date prediction of health issues in your patients.

If you would like the leverage data that your healthcare or medical insurance business has accumulated about your patients, we can make an Azure-based proof of concept on the data provided.

Value of health risk monitoring:

  • Peak cost prediction helps minimize potential losses
  • Using depersonalized data for security
  • Quick setup and intuitive UI
  • Quick client additions: to enable predictions, an EHR with monthly records is used
  • Expert data processing and external database integration due to Azure Cloud hosting.

Service Provided:

During our 6-week PoC, we will build an Azure Cloud-based prototype to prove whether a specific business challenge of your insurance or healthcare business can be solved using the accumulated patient data. We expect you to define one challenge and provide data. For example, you might want to optimize your patient treatment costs - let's check how Azure can help your data be instrumental with that!

Deliverables:

As a result, you will see how Microsoft Azure can be used for data storage and processing, whether your data is relevant for solving the problem, and get relevant business insights. If PoC proves efficient, we can proceed with a full-scale Azure-based project.

https://store-images.s-microsoft.com/image/apps.28480.749cc5ab-4d5e-4c81-9ea6-26def1933f37.9ab5f7d7-905f-40cd-b5f8-cdcb3f032a7b.c93d72d8-9a86-4d71-bf0d-d5dc92aa276c
https://store-images.s-microsoft.com/image/apps.28480.749cc5ab-4d5e-4c81-9ea6-26def1933f37.9ab5f7d7-905f-40cd-b5f8-cdcb3f032a7b.c93d72d8-9a86-4d71-bf0d-d5dc92aa276c