Predicting mortality of residents at admission to nursing home: a longitudinal cohort study.

• Published in: BMC Health Services Research
• Main Authors: Hjaltadóttir, Ingibjörg, Hallberg, Ingalill Rahm, Ekwall, Anna Kristensson, Nyberg, Per
• Other Authors: Department of Health Sciences, Lund University, Lund, Sweden. [e-mail]
• Format: Article in Journal/Newspaper
• Language: English
• Published: BioMed Central 2011
• Subjects: Activities of Daily Living; Aged; 80 and over; Cohort Studies; Female; Health Knowledge; Attitudes; Practice; Health Services; Health Status Indicators; Hospitalization; Humans; Iceland; Interview; Psychological; Kaplan-Meier Estimate; Longitudinal Studies; Male; Mortality; Nursing Homes; Professional Competence; Statistics as Topic; Time Factors; Meier; Rho
• Online Access: http://hdl.handle.net/2336/225678; https://doi.org/10.1186/1472-6963-11-86

To access publisher full text version of this article. Please click on the hyperlink in Additional Links field. BACKGROUND: An increasing numbers of deaths occur in nursing homes. Knowledge of the course of development over the years in death rates and predictors of mortality is important for officials responsible for organizing care to be able to ensure that staff is knowledgeable in the areas of care needed. The aim of this study was to investigate the time from residents' admission to Icelandic nursing homes to death and the predictive power of demographic variables, health status (health stability, pain, depression and cognitive performance) and functional profile (ADL and social engagement) for 3-year mortality in yearly cohorts from 1996-2006. METHODS: The samples consisted of residents (N = 2206) admitted to nursing homes in Iceland in 1996-2006, who were assessed once at baseline with a Minimum Data Set (MDS) within 90 days of their admittance to the nursing home. The follow-up time for survival of each cohort was 36 months from admission. Based on Kaplan-Meier analysis (log rank test) and non-parametric correlation analyses (Spearman's rho), variables associated with survival time with a p-value < 0.05 were entered into a multivariate Cox regression model. RESULTS: The median survival time was 31 months, and no significant difference was detected in the mortality rate between cohorts. Age, gender (HR 1.52), place admitted from (HR 1.27), ADL functioning (HR 1.33-1.80), health stability (HR 1.61-16.12) and ability to engage in social activities (HR 1.51-1.65) were significant predictors of mortality. A total of 28.8% of residents died within a year, 43.4% within two years and 53.1% of the residents died within 3 years. CONCLUSION: It is noteworthy that despite financial constraints, the mortality rate did not change over the study period. Health stability was a strong predictor of mortality, in addition to ADL performance. Considering these variables is thus valuable when deciding on the type of ...