STUFF
Biometric Health Assessment
Company: Advanced Health Intelligence (AHI)
Complexity: 9.28/10
Fun factor: 9.008/10
Project details
- Platform: iOS, Android
- Design system management: Supernova.io
- Product type: B2B SaaS, SDK, White label app
- Design system: Material 3, UCDL
- Design tool: Figma
What is it?
A clinical-like health assessment consisting of multiple stages that is designed to assist clinicians and upstream providers with combined risk analysis of chronic diseases.
Assessment stages
- Cardiovascular Health: A 30 second face scan that measures heart rate, blood pressure, heart attack, stroke.
- Health at Rest: Lying down for 2 minutes and then conducting a 30 second finger scan to measure resting heart rate.
- Body Analysis: A 3-5 minute body scan to measure body circumference, body fat, obesity, central obesity.
- Fitness Evaluation: A 3-5 minute physical step test and then a 30 second finger scan to measure maximum heart rate, and heart rate recovery.
What do you need?
- Face & Body Scan: Desk, chair, table.
- Health at Rest: A bed or couch.
- Fitness Evaluation: Some stairs or a riser step.
How long does it take?
- First-time: 30 minutes, split over a couple of days.
- Ongoing: About 15 minutes.
Use cases
- Health insurance underwriting, dispensary of pharmaceutical drugs (e.g. statins, semaglutide), telehealth, population risk, corporate wellness.
What did I do?
- Initial MVD (Minimum Viable Demo), and MVP (Minimum Viable Product)
- My responsibility varied over time, but I was responsible for the entire app.
- This included research, stakeholder mapping, persona mapping, user journeys, user testing, prototypes, developer handoff, the scans (each stage), scan guides, results, product docs, marketing assets, and video guides/promos.
Major challenges
- Product: High drop off due to usability oversight, notification & message fatigue, regulation and app store guidelines, customisation and theming, no localisation.
- Product complexity: High complexity and barriers to change due to emerging technology innovation cycles. i.e. Working with data science and training models, then testing is expensive.
- Organisational: Design & features by leadership (top down hierarchy), misaligned reward systems, managerial self-interest, team silos, misaligned commercial messaging.