Development of a prognostic model for six-month mortality in older adults with declining health.

CONTEXT: Estimation of six-month prognosis is essential in hospice referral decisions, but accurate, evidence-based tools to assist in this task are lacking. OBJECTIVES: To develop a new prognostic model, the Patient-Reported Outcome Mortality Prediction Tool (PROMPT), for six-month mortality in community-dwelling elderly patients. METHODS: We used data from the Medicare Health Outcomes Survey linked to vital status information. Respondents were 65 years old or older, with self-reported declining health over the past year (n=21,870), identified from four Medicare Health Outcomes Survey cohorts (1998-2000, 1999-2001, 2000-2002, and 2001-2003). A logistic regression model was derived to predict six-month mortality, using sociodemographic characteristics, comorbidities, and health-related quality of life (HRQOL), ascertained by measures of activities of daily living and the Medical Outcomes Study Short Form-36 Health Survey; k-fold cross-validation was used to evaluate model performance, which was compared with existing prognostic tools. RESULTS: The PROMPT incorporated 11 variables, including four HRQOL domains: general health perceptions, activities of daily living, social functioning, and energy/fatigue. The model demonstrated good discrimination (c-statistic=0.75) and calibration. Overall diagnostic accuracy was superior to existing tools. At cut points of 10%-70%, estimated six-month mortality risk sensitivity and specificity ranged from 0.8% to 83.4% and 51.1% to 99.9%, respectively, and positive likelihood ratios at all mortality risk cut points ≥40% exceeded 5.0. Corresponding positive and negative predictive values were 23.1%-64.1% and 85.3%-94.5%. Over 50% of patients with estimated six-month mortality risk ≥30% died within 12 months. CONCLUSION: The PROMPT, a new prognostic model incorporating HRQOL, demonstrates promising performance and potential value for hospice referral decisions. More work is needed to evaluate the model.

Duke Scholars

Author Bryce B. Reeve Population Health Sciences