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

  1. Cardiovascular Health: A 30 second face scan that measures heart rate, blood pressure, heart attack, stroke.
  2. Health at Rest: Lying down for 2 minutes and then conducting a 30 second finger scan to measure resting heart rate.
  3. Body Analysis: A 3-5 minute body scan to measure body circumference, body fat, obesity, central obesity.
  4. 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.