Mobile application for cancer patients: 35% increase in responsiveness
Quantum Flairs has optimized a mobile app for cancer patients, enhancing data collection, personalized support, and scalability to improve outcomes and facilitate workflows.
Customer
Our client is a healthcare software development company committed to creating solutions for oncology patients from the point of diagnosis onward. Their key product is a mobile app to support oncology patients throughout their treatment process. This app collects detailed information about the patient’s condition, generates comprehensive reports, and improves communication between patients and their healthcare providers.
Detailed information about the client cannot be disclosed under the provisions of the NDA.
Industry
Region
Client since
Healthcare
EU
2023
Challenge
Addressing critical issues in data management and app performance
The primary challenges our client faced were concentrated in four key areas:
Data collection and analysis: Although the current app version had data collection capabilities, it needed to be more comprehensive to provide a full picture of patient health. Thus, our team was tasked with developing features to efficiently collect and analyze data from patient inputs, providing physicians with a comprehensive view of disease and helping in treatment decisions.
Process automation: They also needed to implement CI/CD processes to accelerate application development and maintain consistent quality assurance.
Functionality expansion: The client wanted to make the app more personalized to improve patient engagement and facilitate clinical workflows. So they decided to add new features, such as personalized push notifications and advanced analytics, to increase the app’s utility.
Scalability preparation: With the growth in user base and partnerships, the existing app infrastructure was not equipped to handle the increased load. There was a risk of performance issues and system downtimes, which could negatively impact user experience and trust. Quantum Flairs was entrusted with preparing the app for user growth and the expansion of the partner network.
Solution
Enhancing data insights, personalization, and scalability
In close collaboration with the client, Quantum Flairs specialists implemented a comprehensive solution to address the client’s challenges and enhance the mobile application for oncology patients. Our experts focused on improving data collection and analysis, automating processes, expanding functionality, and ensuring scalability.






The Quantum Flairs team developed and integrated Python scripts to automate data extraction from various sources. These scripts handle both structured data from in-app forms (such as medical history and treatment logs) and semi-structured data from wearables using device-specific APIs and FHIR data formats. This comprehensive data collection enables the app to gather valuable insights from patient interactions, which are then used to inform healthcare providers.
Additionally, we built an analytics dashboard using React, featuring graphs, charts, and summary tables to visualize patient data. The dashboard leverages charting libraries like D3.js and Chart.js to create customizable visualizations tailored to specific data types and clinical use cases. This provides healthcare professionals with a clear and intuitive interface to access and interpret patient data, thereby enhancing the decision-making process and improving patient care.
Furthermore, we applied ML and statistical analysis techniques to identify patterns, predict risks, and personalize treatment recommendations.
Data collection and analysis
Preparation for scaling
To support our client’s planned expansion and the addition of new partners, we worked closely with them to implement several key enhancements for future growth.
Performance optimization: To ensure the application remains fast and stable under increased user load, the Innowise team conducted rigorous load testing and optimized both the codebase and infrastructure.
Microservices architecture: We transitioned the application to a microservices architecture, enabling individual components to be scaled independently based on demand. Our experts refactored existing components into smaller, independent services, and created new services to handle specific functionalities. We primarily used REST APIs for communication between services, with message queues employed for asynchronous communication when needed.
Implemented functionalities
To further upgrade the application’s capabilities and user experience, our team has implemented several key updates:
Personalized push notifications: We integrated Firebase Cloud Messaging to deliver personalized reminders for medication intake, doctor appointments, questionnaire completion, and tailored recommendations based on individual patient data.
Advanced analytics: We added new metrics and reports, such as treatment efficacy assessments and complication risk predictions. These enhancements enable doctors to analyze patient data more deeply and identify individual disease characteristics.
Interface improvement: We’ve conducted A/B testing on various interface versions and refined the app’s usability.
Technologies
Front-end
React, React Native
Back-end
Front-end
Python, AWS Lambda, DynamoDB, Neo4j, Firebase Cloud Messaging; API Gateway
Git, GitHub
Front-end
GitHub Actions, Terraform, AWS CDK, Docker
Process
We adopted Scrum to manage our development process, breaking workflow into bi-weekly sprints and keeping a steady pace with deployments every four sprints. With a CI/CD pipeline for automated testing and deployment, our team was able to push updates within the tight project timeline without sacrificing quality.
To keep everyone on the same page, we set a collaborative team environment with Slack for real-time communication and Jira for detailed task tracking. Additionally, our project manager made sure the client stayed in the loop with weekly updates via Skype.




Results
The Quantum Flairs team significantly improved the client’s app’s quality, efficiency, and performance. Enhanced data collection and analysis increased the accuracy of medical decisions while implementing CI/CD cut down the time needed for new feature development. Performance optimization efforts resulted in a 35% increase in app responsiveness and a 40% reduction in system downtimes. Additionally, personalized features and advanced analytics boosted user satisfaction. We also ensured the application’s scalability, minimizing the risk of future failures.
Higher accuracy, reduced development time, and improved UX
40%
reduction in system downtimes
35%
increase in app responsiveness
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