MedTech + Big Data

A medtech product focused on data and care coordination

Product Design, Interaction Design, Prototyping

Content

INTRODUCTION

Dynamic Hackathon Atmosphere

I represented the Polish branch of our company at a global innovation hackathon in Malmö, Sweden — the kind of event where sleep is optional, coffee is mandatory, and creativity is measured in caffeine levels.

The challenge came from Care.us, a leading European telecare provider (fictional name, inspired by a real client). Their goal: to optimize call center scheduling for emergency response operators — ensuring that every alert from an elderly client receives a human response within 30 seconds, 24/7.

I joined a cross-functional team of five:

1x UX/UI Designer (me)
1x Frontend Developer
1x Backend Engineer (Big Data)
1x Backend Full Stack Developer
1x Senior Architect

THE CHALLENGE

Problem: Empathy and pressure

Call centers like Care.us handle thousands of emergency calls from elderly clients every day. Operators face immense emotional and mental pressure — responding calmly and kindly to people in distress, often at night, and often repeatedly.

Goal: The company wanted a system that could

Automatically generate shift schedules for operators.
Ensure a response time under 30 seconds, even during peak hours.
Take into account human needs (breaks, fatigue, focus drops).
Predict when stress or exhaustion might affect response quality.
Balance team composition (e.g., a senior always paired with a junior).

It had to combine empathy and efficiency — a rare mix in scheduling software.

IDEATION & CONCEPT

Rapid Discovery

Our first goal was understanding what drives fatigue and performance in emergency call centers. The Big Data engineer analyzed historical incident patterns, while I mapped user journeys and pain points from the operator’s perspective.

We found patterns such as:

Call frequency spikes between 02:00–08:00 — operators are tired, but the phones won’t stop.
Rainy weather and national holidays caused 20–30% more calls.
Senior clients tended to call more often in the evenings or during local events (like concerts or storms).

Stakeholder Interview Sessions

From these insights, we designed a concept where the system learns over time:

When operators need a break (before they know it themselves).
Which teams handle stress best together.
How to adapt shift rotation dynamically based on real-world conditions.

THE SOLUTION

We created the concept of “Care.us Shift Intelligence” — a modular dashboard powered by AI-driven data modeling.

The system could:

Auto-generate balanced shifts, considering operator skills, rest time, and fatigue levels.
Predict overload zones and suggest micro-breaks in advance.
Monitor real-time coverage and alert if a team’s strength dropped below safe thresholds.
Visualize empathy load — a soft metric estimating emotional fatigue after tough calls.

The design emphasized clarity and resilience: high contrast, minimal color palette, and information hierarchy designed for high-stress environments.

OUTCOME

After 48 intense hours and countless espressos, we pitched our concept to the international jury. The client loved the human-centered data approach and how it balanced numbers with empathy.

A few weeks later, we developed a two-week estimation for a real-world MVP. The client appreciated the idea but decided to postpone implementation due to complexity and cost. Still, it was an incredible exercise in rapid ideation, teamwork, and design under pressure.

Highlights:

Built and pitched in < 48 hours.
Finalist project recognized for innovation in AI-assisted workforce planning.
Strong cross-functional collaboration: design, data, and architecture.

TAKEAWAYS

Empathy in design goes beyond users — it includes those who serve them.
Data can predict stress, but it takes design to make it visible and actionable.
You can achieve a lot in 48 hours — if you have good people, a good challenge, and way too much caffeine.

Visana

How I work

Contact

Dribbble — @maciejantkowiak
LinkedIn — maciejantkowiak
Email — antkowiakmaciej@gmail.com