Connected Device Platform
Allowing clinicians to remotely manage home dialysis patients
Project description
As Principal UX/UI Designer at Mozarc Medical, I led the end-to-end design of a new platform that enables clinicians to remotely monitor and manage patients undergoing at-home dialysis. The platform was designed to support two upcoming home-use dialysis machines: one for peritoneal dialysis and one for hemodialysis.
Our challenge was to make these devices viable in home settings by ensuring clinicians could efficiently access, interpret, and act on large volumes of treatment data.
Background
Clinician's time is a valuable resource and patient safety for home treatments is critical. Clinicians need a way to:
Monitor real-time and historical treatment data from patients’ home devices
Identify issues early and reduce time spent reviewing each treatment
Remotely update prescriptions and settings
Do all of this in a secure, compliant environment that scales across patient types and devices
Initial Research
Competitive Analysis
We began by completing a competitive analysis to benchmark features already on the marketplace. In addition to direct competitors in the health-tech space, I looked at market leading SAAS products that focused on making data useful for their users and that helped manage connected devices.
Field Interview Analysis
Our marketing team conducted field interviews with clinicians to understand daily routines and decision-making patterns. We then analyzed these interviews to create an initial journey map to identify where a connected data platform could improve efficiency and satisfaction in their day-to-day workflows. We used these potential areas of improvement to identify
Clinician journey map for treatment monitoring and support phases, ideal state with new features highlighted in green.
(click to expand)
Unmoderated Testing
With our features and initial requirements we then performed unmoderated information architecture testing and survey interviews to ensure our navigational model matched user mental models and to fill in any remaining questions.
Design Process
Wireframes
With our required features and information architecture established, I began by creating wireframes of each workflow for initial feedback from early stakeholder reviews and to enable quick changes.
During our background research we found that clinicians very rarely used medical data portals on mobile devices and predominantly accessed them via desktop. Although our final design needed to be responsive, I adopted a desktop-first approach.
Wireframes of EMR Integration feature, shown combining design system elements and wireframes.
Internal Expert Review
Mozarc employed a team of expert clinicians consisting of former dialysis nurses. My strategy for leveraging this team's expertise was to involve them early and often, especially when in the wireframing phase.
This strategy paid off in a reduction in later use errors as well as the discovery of required or novel features, all without having to pay for recruitment or lab time.
AI Prototyping
Our design required complex forms and inputs that did not always easily translate to standard Figma prototypes. During the project, Figma released their Make AI prototyping features and I quickly jumped into learning how to create prototypes with it. I used these prototypes primarily with internal experts to allow me to quickly create working versions of new features.
Initial prototype for changing patient treatment and access type created in Figma Make for internal feedback.
High-fidelity Design
I then built my high fidelity design of the initial wireframes in Figma. I took inspiration from leading SAAS web applications to create a modern UI style that applied to our tested wireframes and IA.
Design System Development
I expanded the existing design system for Mozarc’s Simpli Peritoneal Dialysis cycler, which I had previously contributed to, adapting it from an Android tablet interface to a responsive web platform while maintaining visual and functional cohesion across products.
I established a clear text hierarchy, built a comprehensive color library and Figma design tokens as well as buttons and inputs, and developed a responsive layout system with an interactive component library to support prototyping.
Example scaling from buttons to components and into responsive, interactive prototype molecules for a therapy configuration form.
Example Lab Setup for Combined Device / Portal Study
Prototyping and Continuous User Testing
I built several fully interactive prototypes of our platform using Figma. Over the course of a year and half, we held six usability studies while iteratively building on the feedback and adding in new features.
Our final design met all core requirements, resolved usability issues uncovered in testing, and integrated new features from internal and external experts, resulting in a more efficient, user-friendly, and consistent platform.
Core Workflow
I designed the platform to streamline clinicians’ most frequent task, signing off on treatment data for billing, with the goal of saving time and reducing friction.
Each individual treatment report for a patient is available within a table of all of their treatments and can be expanded to view specific details without leaving the page. Key data points such as treatment errors or patient vital recordings that were outside of their goal range are highlighted for quick assessment.
Decision Support
Using insights from clinical experts and customer research, we designed treatment reports that surface common issues faster and reduced the time spent digging through data.
Plotting daily pressure readings against their goal range helps clinicians easily identify trends that require intervention.
Regulated Features
Additional safety and error prevention methods were added for features expected to be regulated by the FDA as medical device features.
Patient Prioritization
Our dashboard design's goal was provide clinicians with an at-a-glance view to prioritize at-risk patients and to easily see outstanding work requirements.
Enterprise Features
Our design needed to support workflows for some of the largest dialysis providers in the world. With large patient and staff lists, we needed our solution to make onboarding and management simple and in line with their existing practices.
My design allows for client admin users to intuitively pull from external data sources such as EMRs and then easily manage permissions and assignments for their staff accounts.
Admin Dashboard Content
Clinic administrator accounts can access dashboards to quickly review clinic staff, patient assignments, and permission levels.
Staff Management
Clinic administrators are able to access staff pages to view productivity insights, account information, and manage patient assignments.
Integration With CLient Data Systems
Importing individual patients is easy with EMR integration. Key information is brought into the system and admins add in platform-specific data.
The final design delivered measurable improvements across usability, efficiency, and clinician confidence. Six rounds of testing helped eliminate critical errors, while new data visualizations gave clinicians earlier insight into patient treatment issues. Streamlined workflows reduced the time needed for routine tasks, and early user feedback confirmed a strong preference for our design over competitors.
Minimized Testing Costs with AI and Internal Resources
The new internal review process allowed us to leverage early expert feedback to avoid lab and recruiting costs. AI prototyping tools reduced the time from concept to design iteration. As these tools continue to evolve, I'm really excited to keep learning how to use them to accelerate my design process.
Reduced Errors
Through six rounds of remote and in-lab usability studies, we reduced critical usability errors, surpassing our internal usability thresholds for medical device functions.
Our final round of testing showed that our design had:
Eliminated 100% of critical errors in key medical device functions
Maintained below 90% use errors throughout all other functions
Created Novel Decision
Support Methods
Developed multiple new data visualizations that help clinicians identify issues with patients treatments more easily and earlier than current techniques. Several of these designs are in the process of being submitted for patents.
Positive User Feedback
Achieved early desirability signals with over 80% of testing participants stating they favored our product over competitors.
Increased Efficiency
Delivered features that save clinician's time when compared with competitors or current practices. When comparing our initial designs, specifically for EMR functions, our final prototype showed an average reduction in time on task of 55%.
In post-testing questionnaires we found that our participants' most commonly sited reason for favoring our product was that they believed it would save them time.
Developer Friendly ♡
I worked with Mozarc's globally distributed developers to structure final Figma files for developer handoff.
The Mozarc Connectivity Platform is now in the final phase of integration with our upcoming home dialysis devices and is expected to enter validation studies soon.
