Streamlining of CATS Ambulance Management

COVID-19 led to India's emergency response systems going into overdrive to cope with enormous new demands brought about by the pandemic. Centralised Accident and Trauma Services (CATS) is an autonomous body of the Government of NCT of Delhi providing round-the-clock free Ambulance Service to the victims of accident and trauma since 1991.

When COVID-19 cases began to rise in the densely populated city-state of Delhi in May 2020, it put a huge stress on the already stretched CATS ambulance system. Ambulance response times (call to the patient) and handover times (call to hospital) skyrocketed due to the surge in demand for emergency services. The pressures on Delhi’s emergency response system highlighted the need for a new and sustainable solution.

The Dialogue and Development Commission (DDC) of Delhi worked closely with the Department of Health & Family Welfare (DoH&FW) and SaveLIFE Foundation (SLF) with the aim to streamline and optimise the functioning of CATS, and to integrate private ambulances/cabs into a system to meet the increasing demand for ambulances from suspect and confirmed Covid-19 patients. SLF’s traditional expertise in emergency medical response, data analytics and first-responder training directly intersected with the needs imposed by the pandemic.

Prior to the intervention, patient call and ambulance dispatch data were being captured but were not being effectively utilised. Only 136 ambulances were operating in Delhi in May 2020, which was far short of the requirement during the pandemic. Further, there was no deciding factor for the efficient deployment of ambulances per district, and the deployment was done solely on the basis of population statistics.

Due to these gaps, once COVID-19 hit, the government was finding it challenging to efficiently use the available data to adapt its deployment strategies, and it needed to be swiftly addressed in order to full fill Delhi Government’s commitment to increase the responsiveness and capacity of its ambulance service. Further, ambulance call operators did not have prior training on how to handle COVID-related calls, it was difficult to implement safety protocols to be able to ensure that ambulances do not carry COVID and non-COVID patients in the same shift.

Due to the surge in emergency calls, ambulance response times (time taken for an ambulance to reach the patient after the call) peaked as high as 14 hours, and handover times (time taken for the ambulance to take the patient to the hospital) grew to 20 hours in some cases. The onset of COVID-19 and surge in demand for emergency care strained the existing processes, and infrastructure, and highlighted the need for a new solution that would provide urgent relief to Delhi’s population while building capacity for the State to handle abnormal health events in the future.

A rigorous analysis of the model revealed the following key gaps:

• Call volume and response time were not taken into account while deploying ambulances
• Traffic and other such restricting factors that impact response time was not taken into account
• Lack of visibility on the performance of the ambulances. The performance of ambulances was one of the indicators for evaluating the magnitude of the pandemic.

The intervention solved three key problems: enabled smart interpretation of data, optimised ambulance deployments to achieve faster response times, and increased system capacity. Additionally, there was a need for visibility of the performance of the ambulances on a daily, weekly and monthly basis.

A rigorous performance management system was put in place and several strategies to improve turnaround time of ambulances were implemented.

Three original interventions emerged from this effort:

• Created a smart deployment technology hat analysed the total patient call volumes and ambulance response times to optimise ambulance deployment plans;
• Build a reporting tool that gathered data from ambulance providers to produce daily and weekly monitoring reports against defined metrics;
• Aggregated and integrated additional ambulances into the State’s emergency services.

SLF helped increase the number of ambulances, systematically review daily operations, and build technological solutions to optimise ambulance allocation across Delhi. The required smart technologies were swiftly developed and operated which optimised Delhi's ambulance deployments, and integrated additional emergency vehicles into the system. 68,000 data points on call volumes, ambulance response times, and data from ambulance providers were analysed every day to understand response patterns.

The call volume and response time data were analysed over a period of 7 days. The pattern from the current week then provided insights into the deployment strategy that needed to be followed in the subsequent week.
To ensure that each district has a minimum number of ambulances, a threshold limit of 30 ambulances was set as the minimum. Further, to increase the government’s supply of emergency resources, additional ambulances were aggregated and integrated into the system.

The technology used real-time analytics, and predictive algorithms to:

• Enable the government to redeploy ambulances in a timely manner
• Identify and correct problems as and when they occur
• Measure performance in real-time
• Preemptively assign ambulances.

The intervention was an integrated emergency medical response monitoring and optimisation system that adapted to the changing needs of Delhi.

This low-cost innovation to aggregate all ambulance services on a single platform, brought parity in the data being collected, used algorithms to generate real-time patterns, and visualised those patterns to enable decision-makers to take immediate action. Greater adoption of this solution is expected to have improved levels of transparency, accountability and efficiency in emergency response systems across and outside of India that was previously inconceivable.

These interventions led to a landmark improvement in ambulance response and handover times, with the following outcomes:

• Average ambulance response time to patients improved by 64% — dropped from 55 minutes (pre-Covid) to under 20 minutes (during the fourth Covid wave in Delhi in May 2021)
• Average handover times to hospitals improved by 40% — lowered from 268 minutes to 160 minutes.Ambulances on the ground increased by over 270%

The interventions successfully met the rapidly escalating demands of COVID-19 and delivered emergency medical care for both COVID and non-COVID patients. With every minute counting in the delivery of emergency medical care, these outcomes saved a substantial number of lives. These successful efforts helped keep Delhi’s COVID-19 fatality rate below 2.4% and recovery rate above 86%.