Case Study - Healthcare

Voice AI Improves Health Care Systems Operational Efficiency

Healthcare systems often face significant inefficiencies in patient administration. Many healthcare providers rely on phone-based appointment systems, increasing labor costs and lower patient satisfaction.


The lack of 24/7 scheduling options forces patients to call at inconvenient times, resulting in missed opportunities for appointment booking. Appoint systems can also fail to match patients with the correct provider, leading to poor resource utilization.


Technology limitations fail to integrate with patient records, causing delays by requiring manual access. Patients may also find difficulty navigating legacy systems.

Table of Contents

Case Summary

Healthcare systems face numerous challenges in providing quality patient care and maintaining an efficient operational system. This case focused on a group of 10 regional hospitals with over a dozen affiliated clinics.


Their goals were to improve patient satisfaction through better response rates, improve the delivery of useful and timely information, and streamline administrative operations.


The financial goals were to reduce operational costs by at least 50%.

Core Client Issues

Patients were increasingly frustrated with the challenge of creating appointments. The process of scheduling was slow and error-prone as it required human intervention. There were no after-hours scheduling options, which created additional phone bottlenecks on Mondays.


Growth in the practice created a need for additional administrative staff to handle inbound calls for appointment scheduling and other patient questions.

Administrative Overhead

Limited Availability (8-5 only)

Increased Staff Costs

Appointment scheduling is time-consuming and error-prone for patients and staff. Growth creates the need for more staff.

No off-hour scheduling such as evenings, nights, or weekends. Creates overload on Mondays.

As demand increases, additional staff are needed, higher training and retention costs.

Poor Patient Follow-ups

Long Call Waiting

Increased Staff Time

There was a general lack of proactive patient follow-ups about medications, post-visit check-ins, and treatment plans resulting in a lack of trust and confidence

Patients experience extended time on hold waiting for appointment scheduling to other inquiries leading to frustration.

The staff has to devote more time to phone and administrative activities, instead of health-care specific tasks.

New Solution Description

Proactive Patient Follow-ups

Elimination of IVR Systems

Enhanced Call Routing

Voice AI agents now handle scheduling changes, follow-ups, and cancellations, reducing staff time and potential errors.

Replaced outdated IVR systems with natural language systems, increasing patient satisfaction.

AI Voice agents reduced call wait times and handled call routing without requiring additional staff to handle increased call volume.

Handling Patient Inquiries

Automated Appointment Scheduling

24/7 Multingual Support

AI voice agents now handle FAQ inquiries, post-treatment reminders, and medication follow-ups, increasing patient satisfaction.

Manual scheduling activities were reduced by 75%, appointment adherence increased by 30%

AI Voice agents communicate in six languages reducing communication barriers leading to greater patient satisfaction.

Results Discussion

  • New Appointment Scheduling: AI agents now handled appointment management 24/7, which reduced manual labor by 75%. Patients were in greater compliance with appointment changes by more than 30%, resulting in fewer no-shows.
  • Multilingual Support: AI agents supported six languages, enhancing accessibility and patient satisfaction.
  • Proactive Follow-ups: Automated reminders for appointments and treatment plans boosted patient engagement.
  • Enhanced Call Routing: Streamlined call management decreased response times by 60%.
  • Operational costs were reduced by 55%
  • Overall operational efficiency improved by 75%
  • Patient appointment adherence increased by 30%
  • Patient satisfaction increased by 35%

Implementation Process

  • Phase 1: Situation Assessment
    Reviewed and analyzed scheduling inefficiencies and call management issues.
  • Phase 2: AI System Development
    Constructed system components, including facility information, FAQs, routing paths, and associated AI prompts.
  • Phase 3: System Deployment:
  • Phase 4: Optimization
    Fine-tuned AI for optimal handling of patient inquiries, responses, and follow-up tasks.

Demonstration

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