Hospital del Mar in Barcelona has completed a year‑long pilot exploring whether quantum‑aligned optimisation techniques can improve one of healthcare’s most complex operational challenges: surgical scheduling. The project, conducted with Barcelona‑based quantum computing company Qilimanjaro under the CDTI‑funded Q‑CARE initiative, has produced early results suggesting significant efficiency gains.
Founded in 1905, Hospital del Mar is a 471‑bed tertiary hospital and major biomedical research centre. Its surgical block includes 11 operating rooms and a 15‑bed post‑anaesthesia recovery unit shared across all specialties. According to hospital officials, the complexity of coordinating procedure durations, cleaning times, recovery capacity and clinical requirements makes manual scheduling increasingly difficult.
“Within the Q‑CARE project, our collaboration with Qilimanjaro has enabled us to explore advanced optimisation techniques aligned with quantum computing and quantum‑inspired approaches, applied to operating room scheduling under real clinical and operational constraints,” said Rafa Luque, Nursing Coordinator of the Surgical Process and Sterilisation at Hospital del Mar.
Classical Optimisation Shows Early Gains
Before quantum methods can be applied, the team first built a classical stochastic optimisation model using real procedure data across 24 surgery types. The model schedules an entire week at once, coordinating patient assignment, room allocation and start times while keeping the recovery unit within capacity.
The optimised schedule reached 331 surgeries per week, compared with 267 under the hospital’s current process—an increase of 27% without adding rooms, staff or equipment. Sensitivity analysis showed that the true bottleneck was recovery bed coordination, something difficult to detect through manual planning.
Luque said the preliminary results “indicate potential improvements of close to 30% in planning capacity compared with traditional approaches, and provide us with a much richer quantitative basis to analyse and evolve our resource‑management methodology, although still within an exploratory setting.”
Preparing for Quantum Scaling
While classical optimisation works at the hospital’s current scale, Qilimanjaro notes that larger patient populations, additional operating rooms and tighter clinical constraints will eventually push classical methods to their limits.
“Projects like this are essential to understanding where quantum technologies can create real value in optimisation tasks,” said Jordi Riu, Algorithm Portfolio Product Owner at Qilimanjaro Quantum Tech. “Since the scale and timing of this impact are still uncertain, we believe it is crucial to start early and collaborate closely with domain experts. This allows us to develop robust algorithms that can provide practical benefits today, while progressively incorporating quantum‑accelerated methods as the hardware matures.”
The hospital now has a validated optimisation framework, structured data and a clear map of operational constraints—elements that position it to adopt quantum solvers once hardware reaches sufficient scale and reliability.
Next Steps
Both partners are exploring how to integrate the optimisation model into day‑to‑day clinical operations using live patient data. Quantum solvers will be introduced gradually as they become viable for larger, more complex scheduling instances.
The Q‑CARE project is subsidised by Spain’s Centre for the Development of Industrial Technology and Innovation (CDTI) through the Science and Innovation Missions programme, part of the 2024–2027 State Plan for Scientific, Technical and Innovation Research and aligned with the national Recovery, Transformation and Resilience Plan. It falls under Mission 6: Digital Health, which supports research into digital tools that improve healthcare efficiency and accelerate medical innovation.
