Gray’s users include some of the largest hospitals in Canada, recognized globally as leaders in healthcare innovation and care delivery.
The Centre hospitalier de l'Université de Montréal (CHUM), a supra-regional hospital, is one of the largest providers in Canada and sees nearly 500,000 patients a year. The cancer center has 45 infusion chairs and 8 radiation treatment machines.
Like many cancer centers, the CHUM is facing major challenges: amidst a labor shortage, treatments are becoming more complex, patient volumes are increasing. Coordinating and scheduling care trajectories has become a labor-intensive, highly manual process, burdening staff that is already overworked. The center operates at capacity offering no margins for the increasing volumes.
Due to the fragmentation of care, leaders cannot efficiently monitor the performance of their department and operate in reactive mode, rather than in a proactive mode.
GrayOS is deployed across the radiation oncology and the medical oncology departments in order to optimize, automate, and orchestrate the operations . The platform is used by scheduling clerks, head nurses, and oncology directors to perform both operational tasks (like patient scheduling) and strategic tasks (planing resources). The tool was able to unlock additional capacity despite the center already operating at high resource utilization rates. Scheduling patients, which used to require several days of work from the most senior clerks, can now be done in a few clicks and does not require a full time role. Nurse workload balance is optimized resulting in an overall increase in staff satisfaction across booking clerks, therapists, nurses and administrators. Finally, department managers stopped operating “in the dark”, and can now better plan their resources and monitor the care pathways.
Reduction in administrative burden
of additional capacity unlocked per day
saved each year
Potential to avoid 1000 days of patient delay per year
Clinical knowledge safeguarded :
mitigation of staffing disruptions
Improved staff satisfaction
Reduced time required to train new staff by 50%