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Case study mode
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Active+ came to us with a problem that sounds simple but gets complicated fast: how do you streamline patient referrals whilst ensuring every person gets exactly the care they need?
01 The Challenge
Active+ was drowning in manual referral processes. Their team was spending hours on administrative tasks that could be automated, but healthcare isn't like booking a hotel room. Every referral involves complex decision-making about patient needs, provider availability, and care pathways.
The existing system was entirely manual, creating bottlenecks that delayed patient care and frustrated both staff and patients waiting for appointments.
02 How We Approached It
We mapped the entire referral journey to understand where human judgment was essential and where automation could genuinely help. The key insight was that automation shouldn't replace clinical decision-making, it should eliminate the administrative friction around it.
We built a system that learns from successful referral patterns whilst preserving the ability for clinicians to override recommendations when patient needs require it.
03 What Made It Special
Rather than creating another automation tool, we built something that gets smarter with use. The platform learns from referral outcomes and clinician feedback to improve its suggestions over time. The real breakthrough was designing automation that enhanced clinical judgment rather than replacing it.
04 The Reality
We delivered a referral system that dramatically reduced administrative overhead whilst maintaining high-quality patient care decisions.
The platform now handles routine referral logistics automatically, freeing up clinical staff to focus on complex cases that need human expertise.
Significant reduction in manual processing through intelligent automation of routine referrals
Faster patient access to care with streamlined booking and scheduling workflows
Enhanced decision support for clinical staff making complex referral decisions
[Client]
Active+
[sector]
Healthcare
