Predict patient numbers for optimal care organization
By Gray Oncology Solutions | Published on March 11, 2022
Problem and objectives
Problem
- Medical oncology centres struggle to efficiently coordinate their physical and human resources (often in significant numbers)
- As a result, these centres are unable to operate at their full potential, which affects the effectiveness of cancer patient treatment
Objectives
- Optimize patient flows in medical oncology centres to better treat patients
- Reduce patient wait times before receiving treatment
- Reduce time spent by administrative staff organizing centre logistics
Proposed solution
Solution
Gray Oncology Solutions is a Québec company specialized in the organization of oncology care. The company has developed a management system for clinics and hospitals, known as GrayOS.
Principle
The GrayOS software optimizes the operation of medical oncology centres by predicting the number of patients to come and automatically scheduling appointments. It actually improves the flow of patients through the centres so that they can operation at their full potential.
Creation of a medical centre digital twin for managing equipment and personnel.
User experience
GrayOS has been set up in the medical oncology centre’s IT system to:
- Simulate patient flows at the centre
- Schedule appointments
- Link radiation therapy and chemotherapy appointments
- Manage unforeseen events (such as staff member on sick leave or equipment breakdown)
Role of AI
Algorithms that are used
- Linear regression;
- Clustering
- Classification
Deep learning for customizing patient treatment times based on their profile (under development)
Analyzed data
- Centre historical data
- New data added in real time by administrative staff
Impacts
Main outcomes
Experience and patient care:
- Increase in patient satisfaction
- Reduced patient wait times (estimated at 10%)
- A solution centered on the patient’s horizontal trajectory through the care pathway rather than a vertical silo-based approach focusing on one type of treatment (chemotherapy, radiotherapy, surgery or imaging)
Medical team wellbeing:
- Time saved in appointment management (almost total reduction from 30 min to 1 min of management)
- Clinical decision support (under development)
- Possibility for centres to operate even with reduced staff (estimated at 10% reduction)
Population health
Regular, optimized administration of oncology treatments
Health costs
Reduced operating costs (objective)
Generation and dissemination of new knowledge
Scientific papers in preparation
Economic development:
From 2 to 8 employees between 2020 and 2021
More precise numbers will be available in 2022 following the implementation of GrayOS at CHUM and CICL, and real world system tests
Challenges takled
Before getting concrete figures on the effectiveness of AI in medicine, it is necessary to test systems under real-world conditions. To communicate the results, such as a time saving of 30%, the company needs to have the client’s consent, which makes it difficult to make certain metrics public.
Conditions for success
Team mobilised
- 7 full-time employees
- 1 part-time employee
Areas of expertise:
- Health logistics
- Data science and machine learning
- Oncology, radiation therapy, chemotherapy
Collaborations
GrayOS is designed for medical oncology centres, including public and private clinics and hospitals. Gray Oncology Solutions is partnering with two cancer centres in Montréal where its solution is deployed on a large scale:
- CHUM;
- CICL.
These two centres give out more than 200K appointments per year in cancer care.
Gray Oncology Solutions collaborates with research centres for the technological development of its solution:
- Centre de recherche du CHUM;
- Polytechnique Montréal.
The company benefited from incubator and accelerator programs to help its growth:
- Creative Destruction Lab;
- District 3;
- Espace CDPQ;
- MtlInc.;
- NextAI;
- Startup Health.
Funding received
- Federal funding (2020): CAD$0.5M
- Investors (2021): CAD$1.25M
- MEI investments (2021): CAD$550K
Project stages
GrayOS was implemented at the CHUM Cancer Centre and at CICL in 2021.
Project stages - to come
Development of a patient portal to allow patients to state their scheduling preferences
Be known in Canada and the US as a leading provider of oncology software by 2022
Assess and quantify the system’s effectiveness in terms of the teams’ time savings, quality of service to clients, number of patients treated and cost savings for the centres
Context of the solution
Customers
Current Business Model – B2B
Gray Oncology Solutions sells GrayOS licenses to medical oncology centres for better management. The price is based on the centre’s resources (number of staff, number of machines, etc.) taken into account by the management system.
Market opportunity
Companies that developed health sector software implemented worldwide in 2025: US$76.45B