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Hospital Expenditure at the End-of-Life: What Are the Impacts of Health Status and Health Risks?

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  • Claudia Geue
  • Paula Lorgelly
  • James Lewsey
  • Carole Hart
  • Andrew Briggs

Abstract

Background: It is important for health policy and expenditure projections to understand the relationship between age, death and expenditure on health care (HC). Research has shown that older age groups incur lower hospital costs than previously anticipated and that remaining time to death (TTD) was a much stronger indicator for expenditure than age. How health behaviour or risk factors impact on HC utilisation and costs at the end of life is relatively unknown. Smoking and Body Mass Index (BMI) have featured most prominently and mixed findings exist as to the exact nature of this association. Methods: This paper considers the relationship between TTD, age and expenditure for inpatient care in the last 12 quarters of life; and introduces measures of health status and risks. A longitudinal dataset covering 35 years is utilised, including baseline survey data linked to hospital and death records. The effect of age, TTD and health indicators on expenditure for inpatient care is estimated using a two-part model. Results: As individuals approach death costs increase. This effect is highly significant (p

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  • Claudia Geue & Paula Lorgelly & James Lewsey & Carole Hart & Andrew Briggs, 2015. "Hospital Expenditure at the End-of-Life: What Are the Impacts of Health Status and Health Risks?," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-14, March.
    • Handle: RePEc:plo:pone00:0119035
    DOI: 10.1371/journal.pone.0119035
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    References listed on IDEAS

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    1. Claudia Geue & James Lewsey & Paula Lorgelly & Lindsay Govan & Carole Hart & Andrew Briggs, 2012. "Spoilt For Choice: Implications Of Using Alternative Methods Of Costing Hospital Episode Statistics," Health Economics, John Wiley & Sons, Ltd., vol. 21(10), pages 1201-1216, October.
    2. Friedrich Breyer & Normann Lorenz & Thomas Niebel, 2015. "Health care expenditures and longevity: is there a Eubie Blake effect?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(1), pages 95-112, January.
    3. Moorin, Rachael Elizabeth & Holman, Cashel D'Arcy James, 2008. "The cost of in-patient care in Western Australia in the last years of life: A population-based data linkage study," Health Policy, Elsevier, vol. 85(3), pages 380-390, March.
    4. Claudia Geue & Andrew Briggs & James Lewsey & Paula Lorgelly, 2014. "Population ageing and healthcare expenditure projections: new evidence from a time to death approach," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(8), pages 885-896, November.
    5. Sally C. Stearns & Edward C. Norton, 2004. "Time to include time to death? The future of health care expenditure predictions," Health Economics, John Wiley & Sons, Ltd., vol. 13(4), pages 315-327, April.
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    7. Meena Seshamani & Alastair Gray, 2004. "Ageing and health‐care expenditure: the red herring argument revisited," Health Economics, John Wiley & Sons, Ltd., vol. 13(4), pages 303-314, April.
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    Cited by:

    1. Joan Costa‐Font & Cristina Vilaplana‐Prieto, 2020. "‘More than one red herring'? Heterogeneous effects of ageing on health care utilisation," Health Economics, John Wiley & Sons, Ltd., vol. 29(S1), pages 8-29, October.
    2. Idaira Rodriguez Santana & María José Aragón & Nigel Rice & Anne Rosemary Mason, 2020. "Trends in and drivers of healthcare expenditure in the English NHS: a retrospective analysis," Health Economics Review, Springer, vol. 10(1), pages 1-11, December.
    3. Anne Mason & Idaira Rodriguez Santana & María José Aragón & Nigel Rice & Martin Chalkley & Raphael Wittenberg & Jose-Luis Fernandez, 2019. "Drivers of health care expenditure: Final report," Working Papers 169cherp, Centre for Health Economics, University of York.

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