Cera Care: Falls Risk
Designing an AI-powered feature that helps care teams identify people at increased risk of falling up to seven days in advance, enabling earlier intervention and more proactive care.
Intro
Falls are one of the biggest causes of injury and hospital admission for older adults receiving care at home. While Cera collected large amounts of care data every day, teams were only able to react after an incident had already happened.
Working closely with Product Managers, clinicians, engineers and the Data Science team, I helped design a new Falls Risk feature that translated complex AI predictions into clear, actionable information for branch teams. The goal wasn't to replace clinical judgement, but to help carers recognise changing risk earlier and take preventative action before a fall occurred.
Role: Product Designer
Duration: 3-6 months
Platform: Android App and Web Portal
Team: Product Manager, Data Project Co-ordinator, 6x Engineers and QA
Stakeholders: Operations and The Data Team
The Problem
Care teams relied on experience and individual observations to identify people who might be at risk of falling. Although carers recorded valuable information during every visit, there was no easy way to recognise subtle trends across weeks of care.
As a result:
Falls were often identified only after an incident had occurred.
Branch teams had limited visibility of changing risk across large caseloads.
Valuable care data wasn't being used to support preventative interventions.
Opportunities to reduce hospital admissions and improve outcomes were being missed.
The challenge was to transform complex clinical and behavioural data into something carers could understand and trust during their everyday workflow.
Understanding the Problem
Rather than beginning with an AI solution, we started by understanding how branch teams currently assessed risk and where existing processes fell short.
Through workshops with Product, clinicians and the Data Science team, we explored the information already being collected during visits, including care plans, medication records and daily observations. Research showed that small changes across multiple data points could indicate someone becoming increasingly vulnerable, even when those changes weren't immediately obvious to carers.
This led to the development of an AI model capable of predicting an increased risk of falling up to seven days in advance.
My role was designing the experience around those predictions, ensuring the information felt understandable, trustworthy and actionable for non-technical users.
Make it stand out.
It all begins with an idea. Maybe you want to launch a business. Maybe you want to turn a hobby into something more. Or maybe you have a creative project to share with the world. Whatever it is, the way you tell your story online can make all the difference.
Make it stand out
It all begins with an idea. Maybe you want to launch a business. Maybe you want to turn a hobby into something more. Or maybe you have a creative project to share with the world. Whatever it is, the way you tell your story online can make all the difference.
Make it stand out.
It all begins with an idea. Maybe you want to launch a business. Maybe you want to turn a hobby into something more. Or maybe you have a creative project to share with the world. Whatever it is, the way you tell your story online can make all the difference.