Healthcare Management Platform for Avalon AI

Avalon.AI is the US data analytics company providing the best outcomes for payors, providers, and medical device and pharma companies. Their innovative AI model combines value-based data analytics with clinical treatment and protocols to provide best-in-class healthcare. Avalon.AI’s proprietary technology is delivered via advanced dashboards and data sets that enable users to make more informed decisions – from the micro level of individual prescriptions up to doctors, hospitals, and entire healthcare systems – all to create better patient outcomes.

In response to the lack of sustainable individual healthcare solutions, Avalon.AI took on the mission to develop a comprehensive digital platform to streamline the management and evaluation of patient medical data. The project was divided into two stages.

Stage 1: providing patients with the ability to manage their doctor’s appointments, receive test results, review prescriptions, and manage personal information updates and medical history.

Stage 2: creating a robust administrative solution for hospitals, insurance providers, and HR departments, equipping them with the tools to oversee a variety of tasks related to managing individual healthcare procedures.

While Avalon.AI had a clear vision and profound understanding of the healthcare sector, the complexity of its goals demanded a partner with demonstrable technical expertise.

Boasting a robust portfolio of successful digital transformation projects within the healthcare sector, and previous successful collaboration on the Opioid Prescription Intelligent Analytics and Hospitals Administration Platform projects, Svitla Systems was chosen as the technology partner to evolve Avalon.AI's initial concept into an advanced solution.

The timeline was tight due to commitments the client made to the stakeholders and required Svitla to launch the MVP within 2 months.

Our task aimed to streamline and optimize the process of managing patients' information, which was initially obtained from various unconnected sources and often in unstructured formats. This task involved receiving, structuring, and categorizing this information to render it meaningful and actionable.

By leveraging Robotic Process Automation (RPA), we handled the vast amount of unstructured patient data, organizing it into an easy-to-analyze format. Once structured, the data was stored in PostgreSQL, a robust open-source relational database that provided the flexibility and security needed to manage and safeguard sensitive patient data.

Next, we embarked on creating intuitive and insightful dashboards using Amazon QuickSight for data visualization. QuickSight's powerful features helped us transform complex data into easily understandable visuals, providing a user-friendly way to comprehend patient trends and patterns.

Finally, the Svitla Team developed the platform, using TypeScript and Node.js on the backend to facilitate effective server-side operations. We chose the Nest.js framework for its efficiency and compatibility with TypeScript and Node.js. The front-end part was built using React.js. Known for its flexibility and efficiency, this approach allowed us to create a highly responsive and interactive user interface.

The entire solution was built on AWS, taking advantage of its reliable and scalable infrastructure. Services such as Amazon EKS (Elastic Kubernetes Service), CloudWatch, CodeBuild, and CodeDeploy were instrumental in ensuring high availability, monitoring performance, building and testing code, and automating software deployments respectively.

By synthesizing these advanced technologies, we created a sustainable solution that streamlines the management of patient data, enhances data visibility, and offers a user-friendly interface.

Currently, the team is focused on the second part of the system, crafting an administrative solution for hospitals, insurance agencies, and HR departments. The aim is to provide them with the capability to review operations associated with supervising personalized healthcare processes.