A multispeciality hospital in Bangalore: Transforming Patient Support with AI

Client: Dr. Aisha Noor, Head of Patient Services,

Challenge:A multispeciality Clinic faced challenges managing high volumes of patient inquiries related to appointments, treatment options, and billing. Patients often experienced long wait times, resulting in dissatisfaction and complaints. With a majority of inquiries being repetitive in nature, the clinic’s support staff frequently found themselves overwhelmed, impacting their productivity and leading to reduced patient satisfaction. The clinic needed a way to efficiently manage routine inquiries while improving response times.

The reliance on traditional support channels like phone calls was costly and inefficient, as patients expected timely and convenient assistance. With healthcare being a sensitive industry where response time is crucial, hospital sought a scalable solution that could manage routine inquiries and streamline patient interactions without increasing operational costs.

Solution: Aisa-X introduced a healthcare-focused AI assistant , designed to handle scheduling, FAQs, and routine inquiries. Operating around the clock, the AI assistant met the needs of 60% of patients who preferred real-time, AI-driven responses, enabling the support team to focus on in-clinic patient needs.

Implementation Phases

Deploy Aisa-X for Patient Support

Launch Aisa-X as a 24/7 support assistant for managing patient inquiries and appointments.

Train on Healthcare Protocols

Equip Aisa-X with healthcare FAQs, billing policies, and appointment scheduling details.

Integration with Scheduling System

Connect Aisa-X to the hospital’s scheduling platform to manage appointment bookings and rescheduling.

Connect with EHR System

Integrate Aisa-X with the electronic health records (EHR) system for accurate patient information access.

Patient Query Escalation Setup

Define criteria to route critical or complex patient cases to healthcare staff.

Patient Feedback Collection

Establish a feedback loop to refine Aisa-X’s responses and continuously improve patient experience.

Results: With Aisa-X,the hospital saw a 50% reduction in escalation rates, while patient satisfaction increased by 33%. Support tickets dropped by 25%, and handling times improved by 60%. The clinic now views Aisa-X as an indispensable part of patient care, with an 85% commitment to future AI investments.

  • 📉 Escalations: 50% reduction
  • 🌟 Patient Satisfaction: 33% boost
  • 🎫 Support Tickets: 25% decrease
  • ⏱ Efficiency: 60% faster handling times

Venkateshkumar S

ABOUT AUTHOR

Venkateshkumar S

Full-stack Developer

“Started his professional career from an AI Startup, Venkatesh has vast experience in Artificial Intelligence and Full Stack Development. He loves to explore the innovation ecosystem and present technological advancements in simple words to his readers. Venkatesh is based in Madurai.”

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