Bridge to Care

Inspiration

The Lake Macquarie and Newcastle Suicide Prevention Network (LMNSPN) supports people in some of the most vulnerable moments of their lives - but too many people who need help don't know where to start. Women in the region were being underserved, referral pathways were inconsistent across partner organisations, and disconnected manual processes meant opportunities for early intervention were being missed. We were inspired by the chance to reduce that friction and help people reach the right support faster, at the moment they need it most.

What it does

Bridge to Care is a compassionate digital entry point that connects people in need with the right mental health resources in under two minutes. A user arrives at the landing page and answers a short, trauma-informed check-in - who they're seeking help for, how urgently they need support, and a little context in their own words. Based on their responses, Bridge to Care matches them to relevant local resources from LMNSPN's network, with clear pathways for people in crisis, those needing support soon, carers worried about a loved one, and people who just want to learn more.

But the product is only half the story. To reach people who may never search for help on their own, we designed a physical outreach strategy using QR codes placed on collateral across the Lake Macquarie and Newcastle area. We explored placements specifically chosen for moments when people have time to pause and reflect - bus stop ads, disposable cup sleeves at local cafes, and cards in venue toilet stalls. We also designed fridge magnets so the link stays visible at home. The goal is to meet people where they are, not wait for them to find us.

How we built it

We used AI throughout the project - to help shape compassionate check-in language, generate and refine content, and accelerate development of the prototype. The app itself is a React web application, built with GitHub Copilot assistance and deployed to an Azure Web App, with continuous deployment via GitHub Actions so the team could push updates throughout the day. We used AI to help us move fast without sacrificing the care required when designing for people in distress.

Challenges we ran into

The primary external resource directory we wanted to integrate with - find-local-care.base44.app - uses on-screen filters rather than shareable links, making it impossible to send someone directly to the right resources without extra steps. We also had to balance collecting enough context to give useful recommendations while keeping the experience minimal and privacy-conscious. Crafting check-in language that is warm and non-judgmental, while also being clear to someone who may be in genuine distress, required real care and iteration. On the outreach side, the challenge was identifying placements that were not just visible, but reached people in a moment of genuine openness - not rushing past a poster, but sitting with a coffee or a quiet moment alone.

Accomplishments that we're proud of

We shipped a working, deployed end-to-end prototype in two days. The check-in flow meets people where they are - no jargon, no login, no unnecessary steps. We mapped out three real user journeys (urgent need, support needed soon, concerned about someone else) and validated that each path leads somewhere useful. We're also proud of the outreach strategy: the QR code placements aren't an afterthought - they're designed around human behaviour and the specific ways people in this community move through their day.

What we learned

Building for mental health contexts demands a level of empathy that goes beyond good design - every word on screen matters. We learned that the biggest barrier to good outcomes often isn't technology; it's that people don't know help exists, or don't feel like it's meant for them. A digital tool is only as effective as its reach. We also learned that AI is a genuinely useful collaborator when the work requires both speed and sensitivity - it helped us iterate on language and content in ways that would have taken much longer without it.

What's next for Bridge to Care

Outreach rollout: Partner with local venues, cafes, and transport providers to place QR code collateral - cup sleeves, toilet stall cards, bus stop placements, and fridge magnets distributed through community services
Resource integration: Work with the find-local-care.base44.app team to support shareable filter links, enabling the check-in to send people directly to the right results
Analytics: Add privacy-safe tracking so LMNSPN can see which pathways people take and which resources are most useful
Partner referral flows: Build a simple tool for partner organisations to refer clients directly into the check-in journey
Accessibility: Full accessibility review and testing across mobile devices
Multi-language support: Expand to reach CALD communities and those for whom English is a second language
Crisis escalation: Ensure people who indicate urgent need are shown crisis contact options at every step, not just at the end