1 Department of Kinesiology & Physical Education, Wilfrid Laurier University, Waterloo, ON, Canada.
2 Department of Health Sciences, Wilfrid Laurier University, Waterloo, ON, Canada.
3 College of Health Sciences, Faculty of Nursing, University of Alberta, Edmonton, AB, Canada.
4 School of Communication Sciences and Disorders, Western University, London, ON, Canada.
5 Department of Psychology, Centre for Research in Human Development, Concordia University, Montreal, QC, Canada.
6 Department of Psychology, University of Toronto, Mississauga, ON, Canada.
7 School of Health Studies, Western University, London, ON, Canada.
8 Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.

Background: To develop and validate a prediction tool, or nomogram, for the risk of a decline in cognitive performance based on the interRAI Cognitive Performance Scale (CPS).

Methods: Retrospective, population-based, cohort study using Canadian Resident Assessment Instrument for Home Care (RAI-HC) data, collected between 2010 and 2018. Eligible home care clients, aged 18+, with at least two assessments were selected randomly for model derivation (75%) and validation (25%). All clients had a CPS score of zero (intact) or one (borderline intact) on intake into the home care program, out of a possible score of six. All individuals had to remain as home care recipients for the six months observation window in order to be included in the analysis. The primary outcome was any degree of worsening (i.e., increase) on the CPS score within six months. Using the derivation cohort, we developed a multivariable logistic regression model to predict the risk of a deterioration in the CPS score. Model performance was assessed on the validation cohort using discrimination and calibration plots.

Results: We identified 39,292 eligible home care clients, with a median age of 79.0 years, 62.3% were female, 38.8% were married and 38.6% lived alone. On average, 30.3% experienced a worsening on the CPS score within the six-month window (i.e., a change from 0 or 1 to 2, 3, 4, 5, or 6). The final model had good discrimination (c-statistic of 0.65), with excellent calibration.

Conclusions: The model accurately predicted the risk of deterioration on the CPS score over six months among home care clients. This type of predictive model may provide useful information to support decisions for home care clinicians who use interRAI data internationally.