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Cost-effectiveness of hip protector use on a geriatric ward in Germany: a Markov model

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Abstract

Summary

In this study, we determined the cost-effectiveness of hip protector use compared with no hip protector on a geriatric ward in Germany. From both the societal and the statutory health insurance (SHI) perspectives, the cost-effectiveness ratios for the provision of hip protectors were below €12,000/quality-adjusted life year (QALY) even if unrelated costs in added life years were included.

Introduction

The aim of this study is to determine the cost-effectiveness of the provision of hip protectors compared with no hip protectors on a geriatric ward in Germany.

Methods

A lifetime decision-analytic Markov model was developed. Costs were measured from the societal and from the statutory health insurance (SHI) perspectives and comprised direct medical, non-medical and unrelated costs in additional life years gained. Health outcomes were measured in terms of quality-adjusted life years (QALYs). To reflect several levels of uncertainty, first- and second-order Monte Carlo simulation (MCS) approaches were applied.

Results

Hip protector use compared with no hip protector results in savings (costs, −5.1/QALYs, 0.003) for the societal perspective. For the SHI perspective, the incremental cost-effectiveness ratio was €4416 €/QALY (costs, +13.4). If unrelated costs in life years gained were included, the cost-effectiveness ratio increases to €9794/QALY for the societal perspective and to €11,426/QALY for the SHI perspective. In the MCS, for the societal perspective without unrelated costs, 47 % of simulations indicated hip protectors to be cost saving (i.e. lower costs and higher effects).

Conclusion

Although the gain in QALYs due to the provision of providing hip protectors to patients on geriatric wards is small, all scenarios showed acceptable cost-effectiveness ratios or even savings.

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Conflicts of interest

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Authors and Affiliations

  1. Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Health Economics and Health Care Management, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany

    B. Stollenwerk, T. Bartmus & F. Klug

  2. Institute of Health Economics and Clinical Epidemiology of the University of Cologne, Gleueler Straße 176-178, 50935, Cologne, Germany

    S. Stock & D. Müller

Authors
  1. B. Stollenwerk
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  2. T. Bartmus
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  3. F. Klug
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  4. S. Stock
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  5. D. Müller
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Corresponding author

Correspondence to B. Stollenwerk.

Additional information

Björn Stollenwerk and Thomas Bartmus contributed equally to this work.

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Figure A1

Scatterplots of incremental costs and effects (cost-effectiveness plain) for: societal perspective with unrelated medical costs (top left); societal perspective without unrelated medical costs (top right); statutory health insurance (SHI) perspective with unrelated medical costs (bottom left); SHI perspective without unrelated medical costs (bottom right). QALYs, quality-adjusted life years (GIF 50 kb)

High Resolution (TIFF 7500 kb)

Appendix

Appendix

Table 3 Sensitivity analyses for key parameters within their 95 % confidence intervals for roll back estimates (societal perspective with related and unrelated health expenditures)
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Table 4 Specification of cost components that were assigned to each perspective
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Table 5 Deterministic sensitivity analyses for key parameters of ANCOVA within their 95 % confidence intervals for roll back estimates for a mixed population at the age of 80 years for societal perspective with unrelated costs
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Table 6 Deterministic sensitivity analyses for key parameters identified via ANCOVA analysis. The values applied for deterministic sensitivity analysis correspond to the upper and the lower bound of the 95 % conficence interval. Values correspond to roll back estimates for a mixed population at the age of 80 years for societal perspective without unrelated costs
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Table 7 Deterministic sensitivity analyses for key parameters identified via ANCOVA analysis. The values applied for deterministic sensitivity analysis correspond to the upper and the lower bound of the 95 % conficence interval. Values correspond to roll back estimates for a mixed population at the age of 80 for SHI insurants perspective with unrelated costs
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Table 8 Deterministic sensitivity analyses for key parameters identified via ANCOVA analysis. The values applied for deterministic sensitivity analysis correspond to the upper and the lower bound of the 95 % conficence interval. Values correspond to roll back estimates for a mixed population at the age of eighty for SHI insurants perspective without unrelated costs
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Table 9 Deterministic sensitivity analysis with 30 % of the excess mortality attributable to hip fractures (roll back estimates)
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Stollenwerk, B., Bartmus, T., Klug, F. et al. Cost-effectiveness of hip protector use on a geriatric ward in Germany: a Markov model. Osteoporos Int 26, 1367–1379 (2015). https://doi.org/10.1007/s00198-014-3008-7

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