End-of-Life Health Costs Were Predicted Primarily by Prior Health Costs, and Secondarily by Temporal, Health and Demographic Factors.

We examined regression models predicting health services standardized costs (HSSC) during the years preceding death using varied temporal parameters related to the dependent and independent variables. The regression models sought to elucidate how costs before the final year of life, temporal factors, and demographics are associated with costs in the final year. Anonymized data were derived from the records of Israel's largest health maintenance organization for 71,855 people aged 65+ in 2006, who died between 2008 and 2011. In the regression models, the Independent Variables of , , and (as measured by the Charlson Comorbidity Index) were significant predictors of the dependent variable of . However, the strongest predictor (independent variable) of the dependent variable, was the independent variable, . Prediction was more accurate when the predicting period was closer to the predicted period. Accuracy declined as the predicted period approached death. The results provide insights into methodological considerations in the process of prediction of end-of-life expenditures, which may assist in setting methodological standards that may facilitate arriving at consistent findings in this field. While end-of-life is associated with aberrant increases in costs, that is, increases that deviate from prior predictions, significant predictions can still be made.