A machine learning recommender system to tailor preference assessments to enhance person-centered care among nursing home residents.

In order to streamline the preference assessment process for nursing home residents, we used the 16 preference items from the MDS 3.0 Section F to develop a machine learning recommender system (similar to Netflix) to identify additional Preferences for Everyday Living Inventory-Nursing Home (PELI-NH) items that may also be important to specific residents. The recommender system successfully provides guidance on how to best tailor the preference items asked of residents. The system can support preference assessment in busy clinical environments, contributing to the feasibility of delivering person-centered care.