Optimising Patient Care with AI
Customer location: The US 
Dedicated team behind the project
Lead Back-end Engineer
Senior Back-end Engineer
Full-stack Engineer
Lead Project Manager
The client
Our client is a healthcare technology startup dedicated to modernizing health data retrieval. Their mission is to revolutionize the way patient data is accessed and utilized, empowering providers to deliver higher quality care. Their innovative solution offers an alternative to traditional fax-based systems, aiming to streamline processes and improve data accuracy.
The project’s key requirements
The client successfully raised a US$5 million seed funding round as reported by Founderlodge. This investment validates the company’s innovative approach to health data retrieval.
Our client’s innovative technology and dedication to improving healthcare were acknowledged by BestStartup.us, a leading platform for identifying promising startups. Read More
The challenge
With a need to accelerate their development process and transition their tech stack to Django, a high-level Python web framework, our client undertook a significant shift. This strategic move was important to enable faster and more efficient web application development.
The company wanted to upgrade their workflow by integrating AI into their system. This technological advancement was aiming to speed up the retrieval and analysis of these records, and also improve the overall operational workflow.
What tested our expertise most was the integration of Mixpanel into the application. The lack of existing documentation or community knowledge on this issue needed an empirical approach to problem-solving, focusing on the development of a strong solution for improved user statistics tracking.
What was done
Our team has been focused on improving the functionality and efficiency of the client’s application through several key projects. Each project presented its own set of technical challenges, requiring a deep understanding of both the application’s architecture and the specific needs of the industry.
Implemented features:
Core Refactoring
The team improved the main core business logic for better efficiency, restructured data transfer for reduced memory usage, and optimized the codebase for faster execution and improved memory utilization. Specifically, multiple data copies in each process were transitioned to a singular data object model.
PDF Links
A solution was developed that dynamically creates internal links in PDF documents, allowing users to navigate directly to specific pages.
Integration with mixpanel
Successfully integrated Mixpanel into the application, enabling to gather more comprehensive user statistics.
Migration to Django
This involved setting up the Django environment, transferring existing functionalities and data to the new platform, and testing to ensure operational continuity.
Application of AI amplifiers
AI technologies were carefully selected and integrated into the system. This step required configuring the AI tools to specifically handle the automation of health data processing.
FHIR Spike (research phase)
During the research phase of the FHIR Spike Story, we developed a proof of concept for a FHIR data warehouse and data pipeline. This is the initial step towards integrating FHIR standards.
Project management approach
LEAN Development
Emphasized efficiency and waste reduction throughout the project lifecycle.
Weekly Iterations
Enabled regular reviews and adjustments with a dynamic, cycle-based approach.
Iteration Planning
Focused on setting clear objectives and coordinating tasks in weekly sessions.
Engineer-Driven Task Selection
Fostered self-management by allowing engineers to choose tasks autonomously.
Cross-Functional Team
Leveraged diverse skill sets for enhanced problem-solving and innovation.
Complexity Estimations and a Tracker
Utilized for precise task difficulty assessment and progress tracking.
Results:
Mixpanel integration now provides daily user statistics that help uncover opportunities for app improvement. This integration allows for a deeper understanding of user behavior, aiding in the refinement of features and overall user experience
Achieved cleaner and faster code execution.
Utilized a single data object across processes instead of multiple copies to reduce memory usage
FHIR data standardization
Developed a promising proof of concept for a FHIR data warehouse and data pipeline. Actively testing the integration of new medical data standards into the business model
PDF usability improvement
Enhanced document usability, making PDFs generated by the company more effective for end-users
Award recognition
The company has been recognized and included in BestStartup.us’s prestigious list of the best medical companies and startups
$5M raised
The client raised a $5 million seed funding round
Tech stack
What the team has to say
Andrew
Full Stack Engineer
“ Working on the healthcare project as a senior developer has been rewarding. It’s not only about enhancing my technical skills, it has also allowed me to directly contribute to improving patient care and healthcare outcomes. Being a part of this change is something I’m proud of. I value the variety of challenges that come with this area, as they stimulate both personal and professional growth. “
Oleksandr
Full Stack Engineer
“ Working with the product, I am confident that I am making the world more modern and better! I constantly feel that I am investing in the future.
I can really see how the field of med tech is evolving, and we are at the best time and place for this transformation. In this project, not only technical skills are valuable, but also management, planning, and visionary.
Here, you feel valued as an individual with your own point of view and vision. All conditions for this growth are provided, starting from basic technical tasks to participating in discussions about the next steps of product development.“
Other сases
Team size: 4 developers
Team size: 6 developers
Team size: 2 developers
Team size: 6 developers
Team size: 3 developers
Team size: 10 developers