Huma is a comprehensive British healthcare platform offering virtual care and decentralized clinical trials through seamless data integration.

Project Description

Huma is a leading healthcare platform from the UK that provides an innovative virtual care and decentralized clinical trial experience. It consolidates health data from hospital databases, wearables, and mobile devices, transmitting crucial information in real-time to healthcare professionals. The platform supports a wide range of healthcare services, including digital-first care, patient support, virtual trials, and remote monitoring solutions. Its robust functionalities enable healthcare systems to deliver efficient and effective care, facilitating better patient outcomes. The platform supports healthcare professionals and patients alike by providing a seamless experience that encourages proactive care management and enhances research efficacy through innovative technological approaches.

Scope of Work

The initial scope of Huma centered around the development of a modular software as a medical device (SaMD) platform designed for comprehensive patient monitoring. The primary challenge was to create a real-time, efficient data collection system from compatible devices capable of physiological and non-physiological monitoring. Key client goals included ensuring the system's performance, reliability, and accuracy, ultimately creating a seamless platform for healthcare professionals to monitor patients effectively. This involved integrating sophisticated technologies and maintaining high standards for software testing to ensure that all regulatory and performance benchmarks were satisfactorily met.

Our Solution

To address the complex needs posed by Huma, a multi-faceted backend environment was implemented, utilizing Python and its Flask framework to handle extensive data collection and processing. The architecture supported real-time patient data display on web and mobile interfaces, coupled with advanced data analytics for monitoring and prognostication. Implementing this system involved integrating key technologies such as MongoDB Atlas for robust database solutions and Twilio for communication functionalities. Additionally, comprehensive use of cloud services like AWS and Google Cloud ensured scalable resource management. The solution also included employing JavaScript frameworks like Angular and JS libraries for frontend enhancements, ensuring comprehensive clinical decision-making and patient self-management support.

Key Features

• Data Collection: Collects both physiological and non-physiological data from various devices through web and mobile applications, ensuring accurate and real-time information gathering.

• Clinical Monitoring: Facilitates intermittent or spot-check monitoring by clinicians, enabling effective patient oversight and rapid response to changes in patient condition.

• Customized Care Plans: Offers customizable modules and functionalities for personalized care plans, enhancing patient engagement and care outcomes.

• Clinical Information Display: Presents patient data on clinician and patient interfaces, with features for trend visualization, goal setting, and communication, enriching the clinical workflow.

• Disease Management: Enables data-driven disease monitoring, decision-making support, and encourages patient self-management, improving clinical efficiency.

• Data Analytics: Provides analytical tools for risk assessment, diagnosis, and disease monitoring, offering insights that support clinical prognostication and intervention strategies.