Using the Minimum Data Set to Determine Predictors of Terminal Restlessness Among Nursing Home Residents

Abstract

The aim of this study was to determine predictive variables of terminal restlessness that were selected from the Minimum Data Set (MDS) among nursing home residents. A descriptive, cross-sectional design was used to retrospectively review decedents' Minimum Data Set records. Four independent variables from the MDS (distressed mood, problem conditions, pain, and medications) were examined as to whether they were predictive variables of terminal restlessness by utilizing path analysis statistical method. Residents from a nursing home located in the northwestern United States who died during 2000 and 2001, had at least one MDS record and no comatose in their MDS cognitive patterns were selected. A total of 84 decedents' records were consequently recruited for use in this study. A path analysis result showed (a) 44.6% of the variance in distressed mood is predicted by two variables: problem conditions (beta = .557) and pain (beta = .193) and (b) 34% of the variance in terminal restlessness is predicted by two variables: pain (beta = .370) and distressed mood (beta = .313). Results indicate that residents who (a) had more problem conditions and more pain are more likely to have distressed moods and (b) experienced more pain and had more distressed moods have a higher incidence of terminal restlessness. These findings provide important and valuable clinical implications. A careful evaluation of pain is necessary, especially as many elders are not able to communicate well during the terminal phase of their lives. How to access residents' moods and provide appropriate and immediate interventions, comfort, and even just being there for them are imperative for nursing home care providers.