Cognitive Change Among Nursing Home Residents: CogRisk-NH Scale Development to Predict Decline.

Objectives: Examine cognitive changes over time among nursing home residents and develop a risk model for identifying predictors of cognitive decline.

Design: Using secondary analysis design with Minimum Data Set data, cognitive status was based on the Cognitive Performance Scale (CPS).

Setting And Participants: Baseline and 7 quarterly follow-up analyses of US and Canadian interRAI data (N = 1,257,832) were completed.

Methods: Logistic regression analyses identified predictors of decline to form the CogRisk-NH scale.

Results: At baseline, about 15% of residents were cognitively intact (CPS = 0), and 11.2% borderline intact (CPS = 1). The remaining more intact, with mild impairment (CPS = 2), included 15.0%. Approximately 59% residents fell into CPS categories 3 to 6 (moderate to severe impairment). Over time, increasing proportions of residents declined: 17.1% at 6 months, 21.6% at 9 months, and 34.0% at 21 months. Baseline CPS score was a strong predictor of decline. Categories 0 to 2 had 3-month decline rates in midteens, and categories 3 to 5 had an average decline rate about 9%. Consequently, a 2-submodel construction was employed-one for CPS categories 0 to 2 and the other for categories 3 to 5. Both models were integrated into a 6-category risk scale (CogRisk-NH). CogRisk-NH scale score distribution had 15.9% in category 1, 26.84% in category 2, and 36.7% in category 3. Three higher-risk categories (ie, 4-6) represented 20.6% of residents. Mean decline rates at the 3-month assessment ranged from 4.4% to 28.3%. Over time, differentiation among risk categories continued: 6.9% to 38.4.% at 6 months, 11.0% to 51.0% at 1 year, and 16.2% to 61.4% at 21 months, providing internal validation of the prediction model.

Conclusions And Implications: Cognitive decline rates were higher among residents in less-impaired CPS categories. CogRisk-NH scale differentiates those with low likelihood of decline from those with moderate likelihood and, finally, much higher likelihood of decline. Knowledge of resident risk for cognitive decline enables allocation of resources targeting amenable factors and potential interventions to mitigate continuing decline.