Ferrovial Services has been awarded a contract to manage the emergency transport service in the Autonomous Community of Madrid. The contract is valued at €77.3MM, with a
four-year duration, and may be extended for a further two years.
As part of the
Emergency Medical Service of Madrid (SUMMA 112), the company will
transport patients to the emergency services of the hospitals in the network of hospitals of the Autonomous Community of Madrid or those with which it has reached an agreement to provide medical services. Likewise, it will be responsible for transporting patients from the emergency services to their homes.
Over 90 state-of-the-art ambulances
This service will use a total of
106 state-of-the-art ambulances that have been specially designed for the permanent -96 activity permanently and 10 for reserve activities. All of these ambulances will feature a
communication system to transmit the data associated with the location and tracking of each vehicle to the SUMMA 112
Coordinating Centre in real time, as well as the operating status of each unit and the reception and monitoring of transfer requests and the completion of these services. In addition, they will feature all necessary medical supplies.
Ferrovial Services will manage the contract from a
base centre and 18 support bases distributed throughout the Autonomous Community of Madrid. To do so, it will have a
management team made up of over 500 people.
Ferrovial's role in Madrid's Healthcare Transport system
Ferrovial started to offer these services for SUMMA 112 through its subsidiary in
2010, with a
four-year contract that was extended until 2016. Some of the improvements that Ferrovial provided during this period included the implementation of a
notification assignment software, which selects the closest free vehicle or the vehicle that will be free as soon as possible. Such an innovative solution has improved the service and significantly
reduced the response times.
During the execution of the new contract, the company also developed a new program based on the massive treatment and analysis of data to monitor the status of the service, mean assistance times per type and zone and mean distances per type of notification and vehicle, among others.
