Metapy: Transforming Data Management for Healthcare and Engineering
UX/UI Design, Product Design, Inclusive design, Dashboard design, Prototyping, and Interaction Design.
Overview
In the MetaPy project, I led a cross-functional team as the Lead Product Designer, overseeing the design of a data management platform tailored for healthcare and engineering users. I directed another designer to build a cohesive design system with reusable components, collaborated with data scientists to integrate real-time biosignal analytics, and guided clinician Aimee Barker’s input to ensure the interface met practical, clinical needs. This collaborative approach resulted in an intuitive, scalable platform that supports effective data-driven decision-making across diverse professional environments.
In depth case study below.
Research
The research process was comprehensive and user-centered. Working with clinician Aimee Barker and other stakeholders, I conducted in-depth user interviews to understand specific data management needs in healthcare and engineering settings. Competitive analysis was conducted on current tools to identify strengths, limitations, and user pain points, and workflow mapping helped optimize accessibility and flow across diverse user roles.
Goals
The project aimed to enhance user experience, simplify data management, enable real-time insights, and integrate cloud accessibility. Our primary objective was to deliver an interface that centralizes complex data, creating a user-friendly, actionable platform for quick, informed decisions.
Pain points
Users reported frustration with complex navigation, excessive data with limited organization, and rigid workflows that did not adapt well to varied user needs. This feedback directly informed our design priorities.
Ideation
Through a collaborative ideation process, we conceptualised solutions focused on a streamlined, minimalistic dashboard, customisable user profiles for role-specific needs, and advanced real-time signal processing for bio-signal data.
(selected wireframes)
Design
As Lead Product Designer, I directed a collaborative team effort to achieve a cohesive and scalable design for MetaPy. Working closely with another designer, I set briefs and provided guidance to develop a consistent design system with reusable components, ensuring a seamless user experience across all features.
To incorporate real-time analytics, I collaborated with data scientists to integrate complex signal processing capabilities, making biosignals like EEG and EMG accessible and actionable for healthcare and engineering professionals. Additionally, I worked with clinician Aimee Barker, guiding her feedback on medical features to ensure practical, intuitive functionality for clinical users.
Key features include a streamlined dashboard, customisable user profiles, session management tools, and a calming visual design for long-term usability. This cross-functional approach ensured a robust platform that adapts to users’ specific workflows, promoting efficiency and data-driven decision-making.
(selected screens)
Conclusion
MetaPy effectively meets the data management needs of healthcare and engineering professionals by providing an efficient, adaptable, and centralized interface. With insights from Aimee Barker and other stakeholders, the design supports better patient outcomes and streamlined workflows, enhancing decision-making and productivity for engineers and clinicians alike.