Living in a long-term care (LTC) home means heavy reliance on others for daily tasks due to physical and mental challenges. What's tricky is that medical treatment isn't always what residents want. It can make them uncomfortable with little benefit. This is where predictive models can help LTC providers make better, more resident-focused decisions. The purpose of this protocol is to develop and test models that predict (1) the permanent loss of physical independence, (2) severe cognitive decline, and (3) the time a resident spends completely dependent.

The goal is to give LTC staff a heads-up about these changes so they can adapt care plans early, making sure residents get the right kind of help. By looking at how things like age, health issues, and personal preferences play into these outcomes, the models can offer personalized guidance. This isn't about just treating symptoms; it's about understanding each person's journey.

For example, imagine a resident who loves gardening but can't do it alone anymore. A predictive model could help staff know when and how to adjust support, maybe by assigning a helper to join them in the garden instead of phasing out the activity altogether. This way, the resident keeps their favorite pastime and maintains a sense of independence. That's what person-centered care is all about: adapting to needs and wishes, not just treating problems as they arise.

Forecasting Loss in LTC Residents: A New Approach to Care Planning

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