Predictors of institutionalization of dementia patients in mild and moderate stages: a 4-year prospective analysis

Abstract

Background: Institutionalization is the most important milestone in the care of dementia patients. This study was aimed at identifying relevant predictors of institutionalization in a broad empirical context and interpreting them on the basis of the predictor model proposed by Luppa et al. [Dement Geriatr Cogn Disord 2008;26:65-78].

Methods: At the start of this study, 357 patients with mild to moderate dementia were examined by their general practitioners, and a telephone interview was conducted with their caregivers. Four years later, the outcomes 'institutionalization' and 'death' were determined from health insurance data. Forty-one variables were examined for their predictive influence by univariate and multivariate Cox regression.

Results: The risk of institutionalization increased significantly (p ≤ 0.05) with older ages of patients [hazard ratio (HR) = 1.05] and caregivers (HR = 1.03), a higher educational level of the caregiver (HR = 1.83), greater use of community health services (HR = 1.59), greater caregiver burden (HR = 1.02), and when the caregiver and patient lived apart (HR = 1.97).

Conclusion: The results show that there is a multifactorial influence on institutionalization of dementia patients by sociodemographic, health-related, and psychological aspects as well as the care situation, thus validating the predictor model by Luppa et al. [Dement Geriatr Cogn Disord 2008;26:65-78]. Caregiver burden was found to be the strongest predictor accessible to interventions.

Keywords: Age; Caregivers; Community health services; Cost of illness; Home nursing; Long-term care; Models, theoretical; Nursing homes; Primary health care; Proportional hazard models.

Fig. 1

Capital letters represent variables in the model by Luppa et al. [49]. Variables in our study are in parentheses (…), 39 variables are shown (the adjustment variables study arm B and C are excluded). Significant predictors from our multivariate analysis are given in bold. Some variables cannot be assigned to the predictor model by Luppa et al. [49]: EQ-5D (P), Incalzi Comorbidity Index, antidementia drugs, psychopharmaceutical drugs, and nonpharmacological therapy. Black boxes contain suggestions for modifications of the model by Luppa et al. [49]. Arrows indicate shifts within the modifications. P = Patient; CG = caregiver.