Technological Innovation in Healthcare

The project’s horizon was the construction of a robust and secure medical data analysis platform capable of providing key metrics and interactive visualizations.

About EPA

Imagen de EPA

The need for cloud solutions to drive continued business innovation

EPA Bienestar is an organization dedicated to improving the health and well-being of its users through comprehensive medical services and advanced technologies. Leveraging open-source digital developments and technological partnerships, they aim to transform how health and wellness are delivered.

By identifying and prioritizing individuals’ basic, physiological, and safety needs, EPA Bienestar helps users achieve their wellness goals. Their age-tailored approach creates personalized connections through a blend of human and artificial intelligence, constant technological innovation, empathy, and a learning methodology adapted to each scenario.

The Challenge

Facing the need to efficiently and securely analyze large volumes of medical data, EPA Bienestar sought to extract key metrics and visualize them comprehensibly to improve service quality and inform decision-making. To tackle this challenge, they partnered with DinoCloud, a Premier Partner of Amazon Web Services (AWS), aiming to create a robust, scalable platform that meets the organization’s growing needs.

Our Approach

Stages, technologies, and services implemented

DinoCloud conducted an initial diagnosis to highlight the necessity for advanced infrastructure in medical data analysis and the integration of new technological tools. The project’s goal was to build a secure medical data analysis platform capable of providing key metrics and interactive visualizations. Additionally, the potential of a platform known as Medplum was explored to complement the solution.

The project was divided into two main stages:

Stage 1: Building an Excellent Data Analysis Infrastructure

  1. Discovery and Definition of Metrics: Collaborated closely with EPA Bienestar through meetings and workshops to identify the key metrics to extract from data stored in Amazon HealthLake.
  2. Integration with Amazon Athena: Established a secure connection between Amazon HealthLake and Amazon Athena for efficient data access and analysis. Implemented strict authentication and authorization mechanisms to ensure only authorized personnel could access sensitive information.
  3. Data Conversion Process: Developed a robust process to convert data from NDJSON to JSON format required by Amazon Athena, ensuring data integrity and consistency. Included error handling mechanisms to prevent interruptions due to technical issues.
  4. Monitoring with Amazon CloudWatch: Implemented Amazon CloudWatch to monitor infrastructure performance, establish metrics, and set up alarms to proactively detect and resolve issues, ensuring smooth operation.
  5. Metrics Extraction and Visualization: Extracted defined metrics through specific queries in Athena and created custom metrics from the Observation resource data in Amazon HealthLake. Designed and implemented an interactive dashboard in Amazon QuickSight for clear and comprehensive visualization.

Stage 2: Deploying Medplum on AWS

  1. Exploration of Medplum: Conducted an exhaustive investigation of Medplum to evaluate its functionalities and potential integration with the developed infrastructure.
  2. Automation with AWS CDK: Created a repository using the AWS Cloud Development Kit (CDK) to automate the deployment of infrastructure on AWS, ensuring efficient and scalable operation.
  3. Infrastructure Deployment: Automatically provisioned essential resources such as Amazon EC2 (servers), Amazon S3 (storage), and Amazon RDS (databases). Continuously validated configurations to minimize human errors and ensure a solid and reliable infrastructure.
  4. Implementation and Testing of Medplum: Deployed the Medplum application on the new infrastructure, configuring it to connect with AWS services and the Amazon HealthLake solution. Conducted comprehensive testing to ensure correct operation and seamless integration.

At DinoCloud, we specialize in transforming a company’s current infrastructure into a modern, scalable, high-performance, and cost-effective system designed to meet business objectives. If you’re interested in optimizing your data management, enhancing analytics, and reducing costs, feel free to contact us here.

Services applied

Amazon EC2

Provided scalable computing resources for deploying and running applications efficiently.

Icono de AWS EKS Amazon S3

Offered secure and scalable storage for data and resources needed in the infrastructure.

Icono de AWS RDS with MySQL Amazon RDS

Managed relational databases to store and manage essential data efficiently.

Icono de Amazon HealthLake Amazon HealthLake

Provided a secure and scalable platform to store and analyze large volumes of medical data.

Icono de Amazon Athena Amazon Athena

Enabled efficient querying and analysis of data stored in Amazon HealthLake without complex ETL processes.

Icono de Amazon CloudWatch Amazon CloudWatch

Monitored infrastructure performance by setting up metrics and alarms to proactively detect and resolve issues.

Icono de Amazon QuickSight Amazon QuickSight

Designed and implemented an interactive dashboard to clearly and comprehensively visualize metrics and analysis results.

The Results

Through the partnership with DinoCloud, EPA Bienestar transformed its medical data analysis capabilities. By establishing a robust and secure infrastructure and exploring innovative technologies, they now possess a powerful tool that significantly enhances their ability to manage and analyze critical health information.

Some benefits:

We are #YourIdealCloudPartner

Focus on your core business while DinoCloud provides the
technology outcomes you need by leveraging its expertise in
the cloud.

Get in touch

(*) Required fields