Long waiting lists in elderly care are a growing problem. But what if math could help? Researcher Rebekka Arntzen from Centrum Wiskunde & Informatica (CWI) has developed mathematical models that can reduce waiting times by up to 50%. Her approach optimizes patient placement by considering personal preferences and urgency, ensuring that available capacity is used more efficiently.
Currently, care providers manage their own waiting lists, often leading to inefficiencies and longer delays. Arntzen’s research shows that a centralized approach can significantly improve patient flow. By combining waiting lists and coordinating placements across different care facilities, organizations can better match supply and demand.
Another key insight: increasing placement capacity outside office hours reduces hospital stays. Many elderly patients remain in hospitals longer than necessary simply because care facilities mainly operate during the day. A more flexible system would prevent delays and free up hospital beds for those in urgent need.
While this research focuses on elderly care, its potential goes beyond that. The same data-driven principles could improve efficiency in other sectors, such as mental healthcare, where long waiting lists are also a major challenge. By applying smart scheduling and optimizing care pathways, more patients could receive help sooner.
Better healthcare logistics don’t require major investments—just smarter coordination. Arntzen’s research proves that a well-organized system benefits both patients and care providers. She will present her findings on February 12 at Vrije Universiteit Amsterdam.
Want to learn more? Website CWI.
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