Healthcare organizations rely on appointment scheduling systems to connect patients with doctors, physicians, and medical services. These institutions often operate across multiple locations, employ many therapists, and communicate with patients through healthcare call centers.

It makes sense to utilize healthcare call centers, which handle appointment bookings through calls, chats, website forms, and emails, to facilitate the scheduling process and make it easier for patients to get medical services as soon as possible. The primary objective of healthcare call centers is to provide high access, thereby enhancing the patient experience and the organization’s revenue.

The types of healthcare systems that match most of all are:

• Polyclinics/hospitals offer various therapies and medical specialties.
• Subspecialty clinics with multiple locations.
• Nationwide or statewide clinics.

The challenge: appointment unavailability in the healthcare call center

Every clinic aims to accomplish two tasks simultaneously: provide access to medical services to as many patients as possible and maintain economic efficiency.

Achieving these goals requires an in-depth analysis of several areas:

• a thorough understanding of the current demand for medical services,
• a comprehensive analysis of the availability, scheduling, geographic location, and costs of medical services.

This ensures that the medical offerings can meet the demand effectively.

Currently, 60% of demand comes to clinics through the healthcare call center via incoming calls, chats, and web forms. Further patient services, such as appointment scheduling, rescheduling, and paperwork, are also handled through these channels.

However, collecting and structuring data from different communication channels takes a lot of work and is expensive if done manually. As a result, clinics often need better-quality data that is very difficult to analyze.

We know how challenging it is for clinics to balance demand and service availability.

On average, 10% of demand is regularly lost due to the inability to book a medical service in time (doctors’ unavailability and other causes). This has a compound effect: it not only leads to a direct loss of profit but also worsens the patient experience. In the end, the healthcare system loses even more.

The Solution: implementing QA Automation & Gen AI Speech Analytics in the healthcare call centers

The Ender Turing Gen AI software analyzes patient communication across all channels: calls, chats, emails, and web forms. This enables us to analyze all patient requests comprehensively.

This is how the process is built:

Automated Call Categorization

The Ender Turing system categorizes all patient requests in the healthcare call center. Some common categories include:

• Appointment scheduling;
• Appointment rescheduling;
• Cancellations;
• Payments;
• Paperwork;
• Price inquiries or special offers requests;
• Service information requests.

Monitoring and Evaluation of 100% of Conversations

The Ender Turing platform monitors and analyzes all calls, chats, emails, and forms, conducting in-depth analyses of revenue-related inquiries or enhancing patient experience. For this, we are using the platform’s automated QA module.

This analysis helps us understand the reasons:

• Why appointments weren’t scheduled.
• What led to a poor patient experience.
• Why do patients call for issues that should have been resolved through self-service?

Here is the list of the most common reasons for appointment unavailability:

• A specific doctor is overbooked.
• Insufficient availability of doctors in a particular specialty, leading to overall specialty overload, where demand exceeds supply.
• Scheduling needs to be corrected: doctors’ available times don’t meet the demand.
• Misalignment by location: geographic demand doesn’t match schedules.
• The clinic does not provide a service that is in high demand.
• Schedules for future periods are opened too late. For example, they open them a week in advance, but they should be opened 2-3 weeks ahead.
• When schedulers discuss prices during the call, they can’t handle objections or effectively sell the service, causing potential patients to disappear.

Deep analytics of demand in real-time

Thanks to continuous monitoring, Ender Turing shows demand for medical services down to the minute detail. Throughout the speech analytics functionality, the system provides insights like the number of patients requesting specific services daily, appointment requests for particular doctors or locations, and requests for price reductions or special offers.

• Clinic operations management optimizes patient access and minimizes wait times across therapies and locations. By receiving these analytics from the healthcare call center, operations management can connect the dots and better align medical staff with current demand, adjusting the number of doctors as needed.
• Scheduling Team Leads receive a practical tool for streamlining the scheduling process and improving efficiency.
• Collaboration enhancement between administrative staff, doctors, and other healthcare professionals involved in scheduling.
• Revenue growth: clinics see a 9% boost in bookings and preventive healthcare services sales growth.

THE RESULTS

Additional contribution to operational excellence in various clinic departments:

• Digital Transformation Department. A clinic gets insights for improving patient self-service. For example, patients often call to complain they have not received their documents, which should come automatically. Analytics shows what bags have to be fixed.

• Marketing Department. The system provides data for analysis of marketing campaign results. Ender Turing monitors calls and chats post-campaign launch, pinpointing necessary keywords and providing detailed stats.

• Patient Experience Department. The system analyzes the efficiency of all communication channels: chats, calls, emails, and website forms. The clinic sees which channels are most successful, where sags occur, and which should be shut down.

• Medical Department. The doctors receive automatic call wrap-ups, and patient information is quickly distributed within processes.

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