A US healthcare client cut average patient response time by 47% with a 40-seat inbound programme
Average response time
−47%
Measured across all inbound patient contacts against the pre-programme baseline
Programme size
40 seats
Dedicated patient-support agents working only this client’s programme
Coverage
US business hours
Delivered from Ahmedabad night shifts, in-hours for the patient
Data handling
HIPAA-aware
Access-controlled floor, restricted USB and printing, role-based permissions
The challenge
- Patient contact volume had outgrown the in-house team, and the queue was the first thing to suffer — callers waited, then called again, which inflated volume further.
- Coverage stopped when the US office closed, so anything arriving late in the day waited until the next morning before anyone looked at it.
- Every candidate solution ran into the same constraint: patient data meant the handling standard could not be relaxed to buy capacity.
- Onshore hiring at the volume required was neither fast enough nor affordable against reimbursement per patient.
The programme
- Sized a 40-seat dedicated patient-support team against measured contact volume by hour, then built the roster before agreeing the service level rather than after.
- Staffed the programme entirely on Ahmedabad night shifts so US patients reach a named agent during their own business hours, not an after-hours service.
- Ran the programme in an access-controlled zone with clean-desk enforcement, restricted USB and printing, VPN-only system access and role-based permissions, under a signed data processing agreement.
- Trained agents on US healthcare terminology and the explicit boundaries of what a support agent may and may not say, with certification on mock interactions before any live patient contact.
- Put an independent QA analyst on the programme, scoring recorded calls weekly against the client’s own rubric, reporting outside the delivery line.
The outcome
Average response time across all inbound patient contacts fell by 47% against the pre-programme baseline. The mechanism was not heroics — it was capacity present at the hours contacts actually arrive, which removed the overnight backlog that had been generating repeat calls each morning.
The secondary effect mattered more to the client than the headline figure. Because the queue stopped compounding, total contact volume fell as repeat callers stopped chasing unanswered enquiries, and the in-house team was freed to handle the clinical escalations that genuinely needed them.
The programme has since become the client’s primary patient-support channel. Capacity is reviewed quarterly against volume, and the same night-shift roster has absorbed two seasonal peaks without adding permanent headcount.
