Health Clinics case study

How a clinic reduced missed calls and cleaned up intake handoffs.

Peak booking windows were creating missed calls, rushed intake, and recall gaps. This case study shows how reception support, request routing, and recall workflows helped the front desk keep work moving.

Clinic reception staff coordinating patient appointments

The starting point

The clinic received calls, website enquiries, intake forms, appointment changes, recalls, and repeated admin questions across the day. Staff were capable, but peak booking windows created missed calls and rushed handovers.

The team needed support that answered common admin questions, captured useful context, and routed sensitive requests to staff without creating privacy or clinical risk.

What we did across the engagement

After the starting point was clear, we moved through four practical steps: mapping the challenge, defining where AI could safely help, putting the workflow in place, and setting the handoffs and review points that kept judgement with the team.

Map

We mapped the operating challenge

Peak booking windows were creating missed calls, rushed intake, and recall follow-up that depended on staff memory.

Define

We defined AI's role and boundaries

Common admin questions, appointment requests, intake details, and recall reminders could be supported safely, while symptoms, emergencies, and clinical judgement needed staff handoff.

Set up

We put the workflow in place

We redesigned how calls, intake details, and recall follow-up moved through the front desk, with clear handoff rules for anything sensitive.

Control

We kept control with the team

Before the workflow was treated as live, we set the ownership, handoff rules, and review points for sensitive requests. Routine work could move faster, while judgement stayed with the team.

The results

The change showed up in the day-to-day work: fewer things slipping through, cleaner handoffs, and clearer ownership for the team.

  • Fewer missed enquiries during peak reception load
  • Cleaner appointment context and recall ownership
  • Clearer ownership of what AI can and cannot answer

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