Does age or life expectancy better predict health care expenditures?

Area of Science:

• Health Economics
• Biostatistics
• Demography

Background:

• Determining factors for healthcare expenditure prediction remains a challenge.
• Existing models often struggle with the censoring of death, particularly concerning end-of-life spending.

Purpose of the Study:

• To compare the predictive power of chronological age versus predicted remaining life expectancy on healthcare expenditures.
• To account for both survivors and deceased individuals by using predicted life expectancy.

Main Methods:

• Hazard models were used to estimate life expectancy based on demographics and health.
• Regression analyses compared the predictive capabilities of age and life expectancy for healthcare costs.
• Predicted life expectancy was employed to overcome data censoring issues related to mortality.

Main Results:

• Life expectancy significantly outperforms age in predicting healthcare expenditures.
• The predictive power of life expectancy decreases when health status measures are included.
• Age offers minimal additional predictive value once life expectancy is considered.

Conclusions:

• Remaining life expectancy is a superior predictor of healthcare spending compared to chronological age.
• Models using life expectancy project lower future healthcare expenditures than age-based models.
• Increasing longevity may have a less substantial economic impact on healthcare costs than anticipated.