IDEAS home Printed from https://ideas.repec.org/a/eee/insuma/v114y2024icp223-241.html
   My bibliography  Save this article

On the factors determining the health profiles and care needs of institutionalized elders

Author

Listed:
  • Shemendyuk, Aleksandr
  • Wagner, Joël

Abstract

In many developed countries, population aging raises a number of issues related to the organization and financing of long-term care. While the determinants of the overall burden and cost of care are well understood, the organization of institutionalized long-term care must meet the needs of the elderly. One way to optimize management is to use information on health problems to assess the infrastructure needed, the qualifications of staff, and the allocation of new entrants. In this research, we determine the typical health profiles of institutionalized elderly using novel longitudinal data from nursing homes in the canton of Geneva, Switzerland. Our data contain comprehensive information on health factors such as impairments of psychological and sensory functions, levels of limitations, and pathologies for 21549 individuals covering the period from 1996 to 2018. First, we perform a spectral clustering algorithm and determine the profiles of the institutionalized individuals. Then, we use multinomial logistic regression to study the effects of the factors that determine these health profiles. Our main findings include eight typical health profiles: the largest group consists of the most “healthy” individuals, who, on average, require the least amount of help with their daily needs and who stay in the institution the longest. We show that, in contrast to age at admission and gender, the limitations and the set of pathologies are relevant factors in determining the profile. Our study sheds light on the typical structures of elderly' health profiles, which can be used by institutions to organize their resources and by insurance companies to derive profile-based products that provide additional insurance coverage in case of special needs.

Suggested Citation

  • Shemendyuk, Aleksandr & Wagner, Joël, 2024. "On the factors determining the health profiles and care needs of institutionalized elders," Insurance: Mathematics and Economics, Elsevier, vol. 114(C), pages 223-241.
    • Handle: RePEc:eee:insuma:v:114:y:2024:i:c:p:223-241
    DOI: 10.1016/j.insmatheco.2023.12.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167668723001051
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.insmatheco.2023.12.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Patrizio Vanella & Moritz Heß & Christina B. Wilke, 2020. "A probabilistic projection of beneficiaries of long-term care insurance in Germany by severity of disability," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(3), pages 943-974, June.
    2. Michel Fuino & Andrey Ugarte Montero & Joël Wagner, 2022. "On the drivers of potential customers' interest in long‐term care insurance: Evidence from Switzerland," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 25(3), pages 271-302, September.
    3. Fu, Yu & Sherris, Michael & Xu, Mengyi, 2022. "Functional disability with systematic trends and uncertainty: a comparison between China and the US," Annals of Actuarial Science, Cambridge University Press, vol. 16(2), pages 289-318, July.
    4. Albarrán, Irene & Alonso-González, Pablo J. & Arribas-Gil, Ana & Grané, Aurea, 2019. "How Functional Data Can Enhance The Estimation Of Health Expectancy: The Case Of Disabled Spanish Population," ASTIN Bulletin, Cambridge University Press, vol. 49(1), pages 57-84, January.
    5. Mengyi Xu & Michael Sherris & Ramona Meyricke, 2019. "Systematic Mortality Improvement Trends and Mortality Heterogeneity: Insights from Individual-Level HRS Data," North American Actuarial Journal, Taylor & Francis Journals, vol. 23(2), pages 197-219, April.
    6. Ugarte Montero, Andrey & Wagner, Joël, 2023. "On potential information asymmetries in long-term care insurance: A simulation study using data from Switzerland," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 230-241.
    7. Jeffrey R. Brown & Amy Finkelstein, 2009. "The Private Market for Long‐Term Care Insurance in the United States: A Review of the Evidence," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(1), pages 5-29, March.
    8. F. Thomas Juster & Richard Suzman, 1995. "An Overview of the Health and Retirement Study," Journal of Human Resources, University of Wisconsin Press, vol. 30, pages 7-56.
    9. Fuino, Michel & Wagner, Joël, 2020. "Duration of long-term care: Socio-economic factors, type of care interactions and evolution," Insurance: Mathematics and Economics, Elsevier, vol. 90(C), pages 151-168.
    10. Joelle H. Fong & Michael Sherris & James Yap, 2017. "Forecasting disability: application of a frailty model," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2017(2), pages 125-147, February.
    11. Bladt, Martin & Fuino, Michel & Shemendyuk, Aleksandr & Wagner, Joël, 2023. "Modelling the burden of long-term care for institutionalised elderly based on care duration and intensity," Annals of Actuarial Science, Cambridge University Press, vol. 17(1), pages 83-117, March.
    12. Ludovico Carrino & Cristina Elisa Orso & Giacomo Pasini, 2018. "Demand of long‐term care and benefit eligibility across European countries," Health Economics, John Wiley & Sons, Ltd., vol. 27(8), pages 1175-1188, August.
    13. Daniel Gottlieb & Olivia S. Mitchell, 2020. "Narrow Framing and Long‐Term Care Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(4), pages 861-893, December.
    14. Brito, M. R. & Chávez, E. L. & Quiroz, A. J. & Yukich, J. E., 1997. "Connectivity of the mutual k-nearest-neighbor graph in clustering and outlier detection," Statistics & Probability Letters, Elsevier, vol. 35(1), pages 33-42, August.
    15. Fuino, Michel & Wagner, Joël, 2018. "Long-term care models and dependence probability tables by acuity level: New empirical evidence from Switzerland," Insurance: Mathematics and Economics, Elsevier, vol. 81(C), pages 51-70.
    16. Guccione, A.A. & Felson, D.T. & Anderson, J.J. & Anthony, J.M. & Zhang, Y. & Wilson, P.W.F. & Kelly-Hayes, M. & Wolf, P.A. & Kreger, B.E. & Kannel, W.B., 1994. "The effects of specific medical conditions on the functional limitations of elders in the Framingham study," American Journal of Public Health, American Public Health Association, vol. 84(3), pages 351-358.
    17. Michael Sherris & Pengyu Wei, 2021. "A Multi-state Model of Functional Disability and Health Status in the Presence of Systematic Trend and Uncertainty," North American Actuarial Journal, Taylor & Francis Journals, vol. 25(1), pages 17-39, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ventura-Marco, Manuel & Vidal-Meliá, Carlos & Pérez-Salamero González, Juan Manuel, 2023. "Joint life care annuities to help retired couples to finance the cost of long-term care," Insurance: Mathematics and Economics, Elsevier, vol. 113(C), pages 122-139.
    2. Chen, An & Fuino, Michel & Sehner, Thorsten & Wagner, Joël, 2022. "Valuation of long-term care options embedded in life annuities," Annals of Actuarial Science, Cambridge University Press, vol. 16(1), pages 68-94, March.
    3. Martin Eling & Omid Ghavibazoo, 2019. "Research on long-term care insurance: status quo and directions for future research," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 44(2), pages 303-356, April.
    4. Hwang, In Do, 2021. "Prospect theory and insurance demand: Empirical evidence on the role of loss aversion," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 95(C).
    5. Norton, E.C., 2016. "Health and Long-Term Care," Handbook of the Economics of Population Aging, in: Piggott, John & Woodland, Alan (ed.), Handbook of the Economics of Population Aging, edition 1, volume 1, chapter 0, pages 951-989, Elsevier.
    6. Fuino, Michel & Wagner, Joël, 2020. "Duration of long-term care: Socio-economic factors, type of care interactions and evolution," Insurance: Mathematics and Economics, Elsevier, vol. 90(C), pages 151-168.
    7. Haas, Steven, 2008. "Trajectories of functional health: The 'long arm' of childhood health and socioeconomic factors," Social Science & Medicine, Elsevier, vol. 66(4), pages 849-861, February.
    8. Michel Fuino & Andrey Ugarte Montero & Joël Wagner, 2022. "On the drivers of potential customers' interest in long‐term care insurance: Evidence from Switzerland," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 25(3), pages 271-302, September.
    9. Ugarte Montero, Andrey & Wagner, Joël, 2023. "On potential information asymmetries in long-term care insurance: A simulation study using data from Switzerland," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 230-241.
    10. Rashmita Basu, 2013. "Willingness-to-pay to prevent Alzheimer’s disease: a contingent valuation approach," International Journal of Health Economics and Management, Springer, vol. 13(3), pages 233-245, December.
    11. Elder, Harold W. & Rudolph, Patricia M., 2000. "Beliefs and actions: expectations and savings decisions by older Americans," Financial Services Review, Elsevier, vol. 9(1), pages 33-45, 00.
    12. M. Martin Boyer & Philippe De Donder & Claude Denys Fluet & Marie-Louise Leroux & Pierre-Carl Michaud, 2018. "A Canadian Parlor Room-Type Approach to the Long-Term Care Insurance Puzzle," CIRANO Working Papers 2018s-13, CIRANO.
    13. Quitterie Roquebert & Jonathan Sicsic & Thomas Rapp, 2021. "Health measures and long-term care use in the European frail population," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(3), pages 405-423, April.
    14. Mariacristina De Nardi & Eric French & John Bailey Jones, 2016. "Medicaid Insurance in Old Age," American Economic Review, American Economic Association, vol. 106(11), pages 3480-3520, November.
    15. Hugo Benitez-Silva & Moshe Buchinsky & John Rust & Emine Boz & Joseph B. Nichols & Sharbani Roy & Ignez Tristao, 2005. "Health Status, Insurance, and Expenditures in the Transition from Work to Retirement," Department of Economics Working Papers 05-11, Stony Brook University, Department of Economics.
    16. Wändi Bruine de Bruin & Michael F. Bryan & Simon M. Potter & Giorgio Topa & Wilbert Van der Klaauw, 2008. "Rethinking the measurement of household inflation expectations: preliminary findings," Staff Reports 359, Federal Reserve Bank of New York.
    17. Khwaja, Ahmed & Silverman, Dan & Sloan, Frank, 2007. "Time preference, time discounting, and smoking decisions," Journal of Health Economics, Elsevier, vol. 26(5), pages 927-949, September.
    18. Lee M. Lockwood, 2018. "Incidental Bequests and the Choice to Self-Insure Late-Life Risks," American Economic Review, American Economic Association, vol. 108(9), pages 2513-2550, September.
    19. Chiara Canta & Helmuth Cremer, 2021. "Opting out and topping up reconsidered: Informal care under uncertain altruism," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(1), pages 259-283, February.
    20. Pamela Giustinelli & Charles F. Manski, 2018. "Survey Measures Of Family Decision Processes For Econometric Analysis Of Schooling Decisions," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 81-99, January.

    More about this item

    Keywords

    Long-term care; Institutional care; Spectral clustering; Multinomial logistic regression; Empirical data;
    All these keywords.

    JEL classification:

    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:insuma:v:114:y:2024:i:c:p:223-241. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505554 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.