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 <i>age</i>, <i>sex</i>, and <i>comorbidity</i> (as measured by the Charlson Comorbidity Index) were significant predictors of the dependent variable of <i>HSSC during the final year of life</i>. However, the strongest predictor (independent variable) of the dependent variable, <i>HSSC in the final year of life</i> was the independent variable, <i>HSSC in the years preceding the final year of life</i>. 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.

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Publication Details

Journal
INQUIRY The Journal of Health Care Organization Provision and Financing
Published
2025-03-29
DOI
https://doi.org/10.1177/00469580251326315
Primary Topic
Global Health Care Issues
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Moshe Hoshen, Michal Skornick-Bouchbinder, Jiska Cohen‐Mansfield
INQUIRY The Journal of Health Care Organization Provision and Financing
Global Health Care Issues
article

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

Moshe Hoshen, Michal Skornick-Bouchbinder, Jiska Cohen‐Mansfield
article en

Abstract

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 <i>age</i>, <i>sex</i>, and <i>comorbidity</i> (as measured by the Charlson Comorbidity Index) were significant predictors of the dependent variable of <i>HSSC during the final year of life</i>. However, the strongest predictor (independent variable) of the dependent variable, <i>HSSC in the final year of life</i> was the independent variable, <i>HSSC in the years preceding the final year of life</i>. 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.

INQUIRY The Journal of Health Care Organization Provision and FinancingVol. 62
Tel Aviv University (IL), Clalit Health Services (IL)
Minerva Foundation
Openalex Percentile: Top 90%
Global Health Care Issues
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