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The cost of frailty in France

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Abstract

The objective of the present work is to explore the incremental costs of frailty associated with ambulatory health care expenditures (HCE) among the French population of community-dwellers aged 65 or more in 2012. We make use of a unique dataset that combines nationally representative health survey with respondents’ National Health Insurance data on ambulatory care expenditures. Several econometric specifications of generalized linear models are tested and an exponential model with gamma errors is eventually retained. Because frailty is a distinct health condition, its contribution to HCE was assessed in comparison with other health covariates (including chronic diseases and functional limitations, time-to-death, and a multidimensional composite health index). Results indicate that whatever health covariates are considered, frailty provides significant additional explanative power to the models. Frailty is an important omitted variable in HCE models. It depicts a progressive condition, which has an incremental effect on ambulatory health expenditures of roughly €750 additional euros for pre-frail individuals and €1500 for frail individuals.

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Notes

  1. The health index combines several measures by means of a data reduction statistical technique (multiple correspondence analysis). The maths behind this synthetic index make it bear the same properties of variance decomposition in the regression model as the set of variables it is made of. In other words, this health index has the advantage of being mathematically equivalent to a set of health measures, without the disadvantage of a larger number of variables could have on multicollinearity. The health index thus does not modify the coefficient estimates in the regression when substituted to a large set of health measures, and provides more accurate standard errors. Because it is a data reduction process, there is no need for external validity of the health index.

  2. GLM offer great flexibility in the choice of the functional form and the variance distribution. Basu and Rathouz [26] suggest the use of extended estimating equations (EEE) in order to estimate the appropriate link and variance functions. EEE rests on a flexible semi-parametric extension of the GLM model using power function (Box-Cox transformation) for the link function. As such, EEE are also referred to as Power-GLM or PGLM. Notice that the log-link function is a special case where the link parameter (i.e., the denominator of the power-function) is zero. Two alternative forms of variance distribution, power or quadratic, are also considered. EEE simultaneously estimates the link and variance parameters from the data along with the regression coefficients. Not only EEE can be used directly to estimate a model for health care costs they can also be used to select the appropriate link and variance functions for GLM. Comparison between PGLM and corresponding GLM based on standard goodness-of-fit tests provides interesting sensitivity analysis. Our results (not displayed here but available upon request) suggest that the value of link parameter λ = 0.205 is significantly equal to zero (p = 0.646) so the link function should be logarithmic, and estimates of variance parameters θ 1 and θ 2 are statistically equal to 1 (p = 0.602) and 2 (p = 0.369), respectively. This eventually suggests that the appropriate model should be close to our initial choice of GLM with Log-Gamma specification. Notice that a modified Park test on Model 4B strongly supports the choice of Gamma variance (p = 0.769).

References

  1. Zweifel, P., Felder, S., Meiers, M.: Ageing of population and health care expenditure: a red herring? Health Econ. 8, 485–496 (1999)

    Article  CAS  PubMed  Google Scholar 

  2. Werblow, A., Felder, S., Zweifel, P.: Population ageing and health care expenditure: a school of ‘red herrings’? Health Econ. 16, 1109–1126 (2007)

    Article  PubMed  Google Scholar 

  3. Cutler, D.M.: Declining disability among the elderly. Health Aff. 20, 11–27 (2001)

    Google Scholar 

  4. Martin, L.G., Freedman, V.A., Schoeni, R.F., et al.: Trends in disability and related chronic conditions among people ages fifty to sixty-four. Health Aff. 29, 725–731 (2010)

    Article  Google Scholar 

  5. Cambois, E., Blachier, A., Robine, J.M.: Aging and health in France: an unexpected expansion of disability in mid-adulthood over recent years. Eur. J. Pub. Health 23, 575–581 (2013)

    Article  Google Scholar 

  6. Chernew, M.E., Goldman, D.P., Pan, F., et al.: Disability and health care spending among Medicare beneficiaries. Health Aff. 24(Suppl 2), W5R42–W5R52 (2005)

    Google Scholar 

  7. Rockwood, K., Fox, R.A., Stolee, P., et al.: Frailty in elderly people: an evolving concept. CMAJ. Can. Med. Assoc. J. 150, 489–495 (1994)

    CAS  Google Scholar 

  8. Strawbridge, W.J., Shema, S.J., Balfour, J.L., et al.: Antecedents of frailty over three decades in an older cohort. J. Gerontol. Ser. B, Psychol. Sci. Soc. Sci. 53, S9–S16 (1998)

    Article  CAS  Google Scholar 

  9. Fried, L.P., Ettinger, W.H., Lind, B., et al.: Physical disability in older adults: a physiological approach. Cardiovascular Health Study Research Group. J. Clin. Epidemiol. 47, 747–760 (1994)

    Article  CAS  PubMed  Google Scholar 

  10. Abellan van Kan, G., Rolland, Y., Bergman, H., et al.: The I.A.N.A task force on frailty assessment of older people in clinical practice. J. Nutr., Health Aging 12, 29–37 (2008)

    Article  CAS  Google Scholar 

  11. Kulmala, J., Nykanen, I., Manty, M., et al.: Association between frailty and dementia: a population-based study. Gerontology 60, 16–21 (2014)

    Article  PubMed  Google Scholar 

  12. Fried, L.P., Tangen, C.M., Walston, J., et al.: Frailty in older adults: evidence for a phenotype. J. Gerontol. Ser. A, Biol. Sci. Med. Sci. 56, M146–M156 (2001)

    Article  CAS  Google Scholar 

  13. Fried, L.P., Ferrucci, L., Darer, J., et al.: Untangling the concepts of disability, frailty, and comorbidity: implications for improved targeting and care. J. Gerontol. Ser. A, Biol. Sci. Med. Sci. 59, 255–263 (2004)

    Article  Google Scholar 

  14. Rochat, S., Cumming, R.G., Blyth, F., et al.: Frailty and use of health and community services by community-dwelling older men: the concord health and ageing in men project. Age Ageing 39, 228–233 (2010)

    Article  PubMed  Google Scholar 

  15. Lahousse, L., Maes, B., Ziere, G., et al.: Adverse outcomes of frailty in the elderly: the Rotterdam Study. Eur. J. Epidemiol. 29, 419–427 (2014)

    Article  PubMed  Google Scholar 

  16. Ilinca, S., Calciolari, S.: The patterns of health care utilization by elderly Europeans: frailty and its implications for health systems. Health Serv. Res. 50, 305–320 (2015)

    Article  PubMed  Google Scholar 

  17. Hoeck, S., Francois, G., Geerts, J., et al.: Health-care and home-care utilization among frail elderly persons in Belgium. Eur. J. Pub. Health 22, 671–677 (2012)

    Article  Google Scholar 

  18. Gnjidic, D., Hilmer, S.N., Blyth, F.M., et al.: High-risk prescribing and incidence of frailty among older community-dwelling men. Clin. Pharmacol. Ther. 91, 521–528 (2012)

    Article  CAS  PubMed  Google Scholar 

  19. Woo, J., Leung, J.: Multi-morbidity, dependency, and frailty singly or in combination have different impact on health outcomes. Age. 36, 923–931 (2014)

    Article  PubMed  Google Scholar 

  20. Peklar, J., O’Halloran, A.M., Maidment, I.D., et al.: Sedative load and frailty among community-dwelling population aged ≥65 years. J. Am. Med. Dir. Assoc. 16, 282–289 (2015)

    Article  PubMed  Google Scholar 

  21. Kiely, D.K., Cupples, L.A., Lipsitz, L.A.: Validation and comparison of two frailty indexes: the MOBILIZE Boston Study. J. Am. Geriatr. Soc. 57, 1532–1539 (2009)

    Article  PubMed  PubMed Central  Google Scholar 

  22. Alemayehu, B., Warner, K.E.: The lifetime distribution of health care costs. Health Serv. Res. 39, 627–642 (2004)

    Article  PubMed  PubMed Central  Google Scholar 

  23. Lynn, J.: Reliable and sustainable comprehensive care for frail elderly people. JAMA 310, 1935–1936 (2013)

    Article  CAS  PubMed  Google Scholar 

  24. Seshamani, M., Gray, A.: Ageing and health-care expenditure: the red herring argument revisited. Health Econ. 13, 303–314 (2004)

    Article  PubMed  Google Scholar 

  25. de Meijer, C., Koopmanschap, M., DU, T.B., et al.: Determinants of long-term care spending: age, time to death or disability? J. Health Econ. 30, 425–438 (2011)

    Article  PubMed  Google Scholar 

  26. Basu, A., Rathouz, P.J.: Estimating marginal and incremental effects on health outcomes using flexible link and variance function models. Biostatistics. 6, 93–109 (2005)

    Article  PubMed  Google Scholar 

  27. Copas, J.: Regression, prediction and shrinkage. J. R. Stat. Soc. 45, 311–354 (1983)

    Google Scholar 

  28. Pregibon, D.: Goodness of link tests for generalized linear models. Appl. Stat. 29, 15–24 (1980)

    Article  Google Scholar 

  29. Hosmer, D., Lemeshow, S.: Applied logistic regression. Wiley, New York (2000)

    Book  Google Scholar 

  30. Santos-Eggimann, B., Cuenoud, P., Spagnoli, J., et al.: Prevalence of frailty in middle-aged and older community-dwelling Europeans living in 10 countries. J. Gerontol. Ser. A, Biol. Sci. Med. Sci. 64, 675–681 (2009)

    Article  Google Scholar 

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Acknowledgments

The authors would like to thank IRDES staff (Paris, France) for knowledge sharing on ESPS data. This work was supported by a grant from the National Solidarity Fund for Autonomy (CNSA, France)—COMPAS Research Project 2012–2015 (Research on Ageing, Functional disability, and Health Care Expenditures). The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under grant Agreement number 115,621, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007–2013) and EFPIA companies’ in kind contribution”.

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  1. LIRAES (EA 4470), Université Paris Descartes, Sorbonne-Paris-Cité, 45 rue des Saints Pères, 75006, Paris, France

    Nicolas Sirven & Thomas Rapp

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  1. Nicolas Sirven
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  2. Thomas Rapp
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Correspondence to Nicolas Sirven.

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Sirven, N., Rapp, T. The cost of frailty in France. Eur J Health Econ 18, 243–253 (2017). https://doi.org/10.1007/s10198-016-0772-7

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  • DOI: https://doi.org/10.1007/s10198-016-0772-7

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