RESUMO
OBJECTIVES: Describe the rate of death over 4 consecutive quarters and determine optimal categorization of residents into risk-of-death categories, expanding the Changes in Health, Endstage Disease & Symptoms and Signs (CHESS) scale. DESIGN: Using secondary analysis design with Minimum Data Set (MDS) data, the CHESS scale provided the base upon which the DeathRisk-NH scale was developed. SETTING AND PARTICIPANTS: Baseline and 4 quarterly follow-up analyses of Canadian (n = 109,145) and US (n = 1,075,611) nursing home resident data were completed. METHODS: Logistic regression analyses identified predictors of death, additive to CHESS, to form the DeathRisk-NH scale. The independent variable set used MDS items, focusing on clinical complexity indicators, diagnostic conditions, and measures of severe clinical distress. RESULTS: Country cohorts had similar percentages of residents with mean activities of daily living hierarchy scores, dependence in mobility, continence, memory, and overall, CHESS scores. The percentage of individuals who died increased from 10.5% (3 months) to 30.7% (12 months). The average annual death rate for this cohort was 5.5 times higher than the national annual death rate of approximately 5.6%. CONCLUSIONS AND IMPLICATIONS: The DeathRisk-NH is an effective prediction model to identify residents at risk of death within the first 12 months after admission to the nursing home. The tool may be helpful in patient care planning, resource allocation, and excess death monitoring.
