title: Predicting death in the nursing home: development and validation of the 6-month Minimum Data Set mortality risk index.
abstract: BACKGROUND
  Currently, 24% of all deaths nationally occur in nursing homes making this an important focus of care. However, many residents are not identified as dying and thus do not receive appropriate care in the last weeks and months of life. The aim of our study was to develop and validate a predictive model of 6-month mortality risk using functional, emotional, cognitive, and disease variables found in the Minimum Data Set.
  
  
  METHODS
  This retrospective cohort study developed and validated a clinical prediction model using stepwise logistic regression analysis. Our study sample included all Missouri long-term-care residents (43,510) who had a full Minimum Data Set assessment transmitted to the Federal database in calendar year 1999. Death was confirmed by death certificate data.
  
  
  RESULTS
  The validated predictive model with a c-statistic of.75 included the following predictors: a) demographics (age and male sex); b) diseases (cancer, congestive heart failure, renal failure, and dementia/Alzheimer's disease); c) clinical signs and symptoms (shortness of breath, deteriorating condition, weight loss, poor appetite, dehydration, increasing number of activities of daily living requiring assistance, and poor score on the cognitive performance scale); and d) adverse events (recent admission to the nursing home). A simple point system derived from the regression equation can be totaled to aid in predicting mortality.
  
  
  CONCLUSIONS
  A reasonably accurate, validated model has been produced, with clinical application through a scored point system, to assist clinicians, residents, and family members in defining good goals of care around end-of-life care.
authors.affiliation: School of Nursing, University of Nottingham, Nottingham, UK. Davina.Porock@nottingham.ac.uk
authors.forename: Davina
authors.initials: D
authors.lastname: Porock
authors.forename: Debra Parker
authors.initials: DP
authors.lastname: Oliver
authors.forename: Steve
authors.initials: S
authors.lastname: Zweig
authors.forename: Marilyn
authors.initials: M
authors.lastname: Rantz
authors.forename: David
authors.initials: D
authors.lastname: Mehr
authors.forename: Richard
authors.initials: R
authors.lastname: Madsen
authors.forename: Greg
authors.initials: G
authors.lastname: Petroski
mesh_terms: D000203:Activities of Daily Living; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000453:epidemiology; D003072:Cognition Disorders / Q000453:epidemiology; D015331:Cohort Studies; D003644:Death Certificates; D004417:Dyspnea / Q000453:epidemiology; D001068:Feeding and Eating Disorders / Q000453:epidemiology; D005260:Female; D005544:Forecasting; D006333:Heart Failure / Q000453:epidemiology; D006801:Humans; D008297:Male; D008923:Missouri / Q000453:epidemiology; D009026:Mortality; D009369:Neoplasms / Q000453:epidemiology; D009735:Nursing Homes; D051437:Renal Insufficiency / Q000453:epidemiology; D012189:Retrospective Studies; D018570:Risk Assessment; D012737:Sex Factors; D013727:Terminal Care