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Determinants of received long-term care – Individual responses to regional nursing home provisions

Health Care Management Science volume 19, pages 326–337 (2016)Cite this article

Abstract

Existing literature analyzing the choice of received long-term care by frail elderly (65+ years) predominantly focuses on physical and psychological conditions of elderly people as factors that influence the decision for a particular type of care. Until now, however, the regional in-patient long-term care supply has been neglected as influential factor in this decision-making process. In this study, we analyze the determinants of received long-term care in Germany by explicitly taking the regional supply of nursing homes into account. We estimate a multinomial probit model to illustrate this decision-making process. Therefore, within this discrete choice setting we distinguish between all available types of long-term care in Germany, i.e. four different types of formal and informal care provision. We find that the decision for long-term in-patient care is significantly correlated with the regional supply of nursing home beds, while controlling for physical and psychological conditions of the individual.

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Fig. 1

Notes

  1. For price adjustments, price indices for out-patient as well as in-patient health care services are considered using 2012 as base year [30].

  2. A general overview on care provision and its taxonomy is provided by [22].

  3. Detailed definitions of the variables are provided in Table 3 in the Appendix.

  4. For the long list of variables we performed a collinearity check. This check revealed correlations on a moderate level for all variable combinations.

  5. A theoretical illustration of this model is provided in [8, 14] and [43].

  6. Other authors also assume that individuals choose that alternatives providing them the highest utility level (see e.g. [27, 41]).

  7. Intuitively, an interaction term of both dummy variables for women und living alone may be of interest. However, due to the non-linearity of the model an interaction term does not allow for correct inference about sign, magnitude or statistical significance of the estimated interaction effect as shown by [1]. Therefore, we forgo including this interaction term in the model.

  8. The average marginal effects for this model specification are provided in Table 4 in the Appendix.

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Acknowledgments

We thank Thomas K. Bauer, Dörte Heger, Ingo Kolodziej, Sandra Schaffner, Ansgar Wübker and three anonymous referees for helpful comments and suggestions. We are grateful to our colleagues from the WINEG for the access to the data of the Techniker Krankenkasse. Financial support by the German Research Foundation (DFG) and the Ruhr Graduate School in Economics is gratefully acknowledged.

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Affiliations

  1. Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Hohenzollernstr. 1-3, 45128, Essen, Germany

    Adam Pilny & Magdalena A. Stroka

  2. Ruhr Graduate School in Economics, Ruhr-University Bochum, Bochum, Germany

    Adam Pilny

  3. Ruhr-University Bochum, Bochum, Germany

    Magdalena A. Stroka

  4. WINEG - Scientific Institute of TK for Benefit and Efficiency in Health Care, Bramfelder Str. 140, 22305, Hamburg, Germany

    Magdalena A. Stroka

Authors
  1. Adam Pilny
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  2. Magdalena A. Stroka
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Correspondence to Adam Pilny.

Appendix

Appendix

Table 3 Definition of variables
Full size table
Table 4 Robustness check – average marginal effects
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Pilny, A., Stroka, M.A. Determinants of received long-term care – Individual responses to regional nursing home provisions. Health Care Manag Sci 19, 326–337 (2016). https://doi.org/10.1007/s10729-015-9333-3

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Keywords

  • Informal care
  • Formal care
  • Choice of care
  • Administrative data
  • Nursing home supply
  • Multinomial probit model