Machine learning and blockchain-backed optimized assignment matching for PSWs to improve understaffing and risk during the COVID‑19 outbreak
The COVID‑19 pandemic exposes systemic weakness in how the Personal Support Worker (PSW) industry is operated here in Canada. Lack of validated proof of certifications and microcredentials (first aid, safety training, background checks, etc.) leads to hiring delays, understaffing, and potential risks to patients. This in turn causes issues for PSWs, including low pay, inefficient scheduling, underemployment, and has resulted in an unsustainable PSW “gig economy.” TriNetra is collaborating with ConnexHealth to implement a system for verifying PSW qualifications, achievements, and certifications. They are proposing to collaborate with Seneca to extend the features of this system to include capabilities to match candidates to job assignments based on their entire profiles, including certifications, training, geography, work history, and availability. This will help the COVID crisis by reducing understaffing at care facilities due to difficulty in validating the credentials of potential workers, eliminating travel and skills mismatches between PSWs and their given assignments; and improving PSW quality of life through better assignment matching, recognition for training, and less travel.
This project will initially create a full-featured PSW community portal with blockchain-based credentialing and a machine learning/artificial intelligence-based matching system to address the current need for better and more reliable credentialing and placement software for PSWs. The portal will automatically create individual PSW assignments and schedules to encompass all aspects of their training, availability, and geography. The first two phases of the project will result in a requirements report and optimized matching system to be deployed within the first 12 weeks of the project, and a fully functional system at completion of the 24 week project. This would provide immediate benefit to help reduce understaffing in long-term care facilities and assist PSWs in faster employment at better-matched assignments.
