Introduction
During the height of the COVID-19 pandemic, Suwasariya, the national emergency ambulance service in Sri Lanka, faced significant difficulties. The increased number of COVID-19 patients put immense pressure on their call centers and made it challenging to deploy ambulances efficiently. To address these issues swiftly, Suwasariya joined forces with Emojot, an AI-driven, emotion-centric, intelligent experience management platform, to introduce innovative solutions. Emojot’s Emotion SensorsTM played a crucial role in tackling two key issues: overcrowded call centers and ensuring ambulance staff were well-prepared. The outcome was an improvement in patient transfers and enhanced readiness of ambulance staff throughout the pandemic.
Challenge 1: Congested Call Centers
During the pandemic’s peak, Suwasariya’s call centers experienced a surge in call volumes, resulting in delays and potentially life-threatening situations.
Solution: Emojot’s Emotion SensorTM for Ambulance Dispatch
Emojot deployed an Emotion SensorTM equipped with skip-logic and decision-tree modeling capabilities to streamline the process. When a call was received, the agent filled out the Emotion SensorTM with the patient’s symptom information. The sensor then automatically recommended whether an ambulance dispatch was necessary. This not only reduced the stress on the main call center but also ensured that ambulances were used efficiently, focusing on absolute necessity cases.
Results
– Reduced call center congestion and improved response times.
– Efficient use of ambulance resources for critical cases.
– Enhanced patient outcomes by prioritizing urgent cases.
Challenge 2: Ambulance Staff Preparedness
The ambulance staff faced challenges in determining the severity of patients’ conditions, leading to multiple trips back to the base station for full personal protective equipment (PPE).
Solution: Emojot’s Emotion SensorTM for PPE Requirement
A second Emotion SensorTM was implemented to determine the PPE kit requirement for ambulance staff. If the primary sensor recommended an ambulance dispatch, agents called the patient back to gather more information on symptoms for the second sensor. This sensor, with skip-logic and decision-tree modeling capabilities, automatically recommended whether the ambulance should be dispatched with full PPE or standard PPE.
Results
– Reduced Travel Time: Ambulance staff no longer needed multiple trips to gather PPE, reducing time spent on commuting.
– Efficient PPE Utilization: PPE resources were used effectively, ensuring availability for all cases.
Conclusion
By leveraging Emojot’s skip-logic and decision-tree modeling capabilities, the National Emergency Ambulance Service, ‘Suwasariya’ successfully addressed the challenges posed by the COVID-19 pandemic. The implementation of two Emotion SensorsTM transformed Suwasariya’s response during the COVID-19 pandemic. They helped alleviate call center congestion, improved ambulance deployment efficiency, and enhanced staff readiness. This collaboration highlights the critical role of technology in healthcare crisis management, demonstrating how innovation can empower emergency services to respond effectively to unprecedented challenges and save lives during public health emergencies.
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