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The health and economic consequences of osteopenia- and osteoporosis-attributable hip fractures in Germany: estimation for 2002 and projection until 2050

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Abstract

Summary

The health and economic burden of osteopenia- and osteoporosis-attributable hip fractures (OHF) in Germany was estimated for 2002 and projected until 2050. We found 108,341 OHF resulting in 2,998 million Euros cost, which will more than double by the year 2050, calling for improvement and development of prevention strategies for OHF.

Introduction

This study aimed to estimate the health impact and the societal costs of OHF in Germany in the year 2002 and to extrapolate these estimates to the years 2020 and 2050.

Methods

We estimated OHF-attributable deaths, years of potential life lost (YPLL) and quality-adjusted life years lost (QALYs) using attributable fractions. Direct costs for acute treatment, rehabilitation, nursing care, non-medical costs and indirect costs for sickness absence, early retirement and mortality were estimated. All estimates were extrapolated to 2020 and 2050 using an estimation of future population composition and life expectancy.

Results

We found 108,341 OHF resulting in 3,485 deaths, 22,724 YPLL, 114,058 QALYs, 2,736 millions of Euros direct cost and 262 millions of Euros indirect costs. Projection to 2020 showed corresponding increases of 44%, 62%, 56%, 49%, 47% and 33%, whereas the projection to 2050 resulted in changes of 128%, 215%, 196%, 152%, 138% and 90%, respectively.

Conclusions

OHF have considerable impact on health and direct costs in the elderly. Both may strongly increase in future decades due to demographic changes, calling for improvement and development of effective strategies for preventing and dealing with OHF.

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Acknowledgement

We are most grateful to Claus König, M.Sc. for providing mathematical advice.

Conflict of interest

None.

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Correspondence to A. Konnopka.

Additional information

Alexander Konnopka and Nadine Jerusel were equally contributing to this manuscript.

Appendix

Appendix

Relative risk of HF due to osteopenia and osteoporosis

For a BMD-dependent, variable we used—according to De Laet et al. [7]—a value of 2.6 per standard deviation and we used the T score as the basis for the standard deviation. Osteopenia and Osteoporosis are defined by intervals of bone density in a standard normal distribution. In order to consider the probability that a person has a certain bone density, a 2.6 T score was weighted with the density function of a standard normal distribution to account for the probability of having a certain T score. The relative risks for osteopenia (RR 1 ) and osteoporosis (RR 2 ) were calculated as follows:

$$\begin{array}{*{20}l} {{RR_{1} = \frac{{{\int\limits_{ - 2.5}^{ - 1} {\frac{1}{{{\sqrt {2\pi } }}}} }e^{{ - \frac{1}{2}T^{2} }} 2.6^{{ - T}} }}{{{\int\limits_{ - 2.5}^{ - 1} {\frac{1}{{{\sqrt {2\pi } }}}e^{{ - \frac{1}{2}T^{2} }} } }}} = 4.359597} \hfill} & {{RR_{2} = \frac{{{\int\limits_{ - \infty }^{ - 2.5} {\frac{1}{{{\sqrt {2\pi } }}}} }e^{{ - \frac{1}{2}T^{2} }} 2.6^{{ - T}} }}{{{\int\limits_{ - \infty }^{ - 2.5} {\frac{1}{{{\sqrt {2\pi } }}}e^{{ - \frac{1}{2}T^{2} }} } }}} = 15.566375} \hfill} \\ \end{array} .$$
(2)

Mortality (M OHF )

Age- and gender-specific multiplication of the OAF with the HF-associated deaths M HF :

$$M_{{OHF}} = OAF \times M_{{HF}} .$$
(3)

Years of potential life lost

Determination of gender-specific probabilities p l of reaching future ages A + n (n = 1, 2, 3… 100 − A) of maximally up to 100 years for each age group A. For each age group A, addition of the p l of all future years of life and multiplication with M OHF :

$$YPLL = M_{{OHF}} \times {\sum\limits_A^{100} {p_{{\text{l}}} } }.$$
(4)

Quality-adjusted life years lost

Fracture associated QALY loss (QALY1)

Age- and gender-specific multiplication of the OAF with the inpatient HF cases HF IC and subtraction of M OHF . Then multiplication with post-fractural QALY loss and correction by p l for the second post-fractural year:

$$QALY_{1} = {\left( {OAF \times HF_{{IC}} - M_{{OHF}} } \right)} \times {\left( {0.2 + p_{{\text{l}}} \times 0.1} \right)}.$$
(5)

QALY loss among people who need nursing care (QALY2)

Age- and gender-specific determination of OHF-attributable nursing care cases from inpatient cases HF IC with the help of:

  • Probability p c of outpatient or inpatient nursing care needs according to HF,

  • Probability p cp that a person needed no nursing care before HF,

  • Probability p cf of a person in age A without HF also needing no nursing care in the future,

  • Probability p l of a person in age A experiencing future life years A + n (n = 2, 3, 4… 100 − A).

Multiplication of the care cases with QALY loss whilst considering future years:

$$QALY_{2} = {\left( {OAF \times HF_{{IC}} - M_{{OHF}} } \right)} \times p_{{\text{c}}} \times p_{{{\text{cp}}}} \times {\left( {{\sum\limits_{A + 2}^{100} {p_{{{\text{cf}}}} \times p_{{\text{l}}} \times 0.1} }} \right)}.$$
(6)

Mortality-attributable QALY loss (QALY3)

Calculated as with YPLL, but weighting p l with age- and gender-specific EQ-5D index values EQ:

$$QALY_{3} = M_{{OHF}} \times {\left( {{\sum\limits_A^{100} {p_{{\text{l}}} \times EQ} }} \right)}.$$
(7)

Resource utilisation and direct costs

Inpatient medical treatment and rehabilitation (DC1)

Age- and gender-specific multiplication of the OAF with the HF-associated hospital care days HF ID and rehabilitation days HF RD and the average costs per care day C 1ID and C 1RD :

$$DC_{1} = OAF \times {\left( {HF_{{ID}} \times C_{{1ID}} + HF_{{RD}} \times C_{{1RD}} } \right)}.$$
(8)

Outpatient treatment and non-medical costs for health protection, rescue services, administration and “other services” (DC2)

Determination of the portion of inpatient OHF cases in inpatient cases of S70–S79 (ICD-10: injuries of hip and thigh) and application to recorded costs C S70–S79 :

$$DC_{2} = \frac{{OAF \times HF_{{IC}} }}{{{\text{S70}} - {\text{S79}}}} \times C_{{{\text{S70 - S79}}}} .$$
(9)

Nursing care (DC3)

Determination of OHF-attributable nursing care cases analogous to QALY 2 . Multiplication of the current and future OHF-attributable nursing care cases by the costs for inpatient and outpatient nursing care C 3. Consideration of the first year at 50% and discounting of costs of future n years by r = 5% per year:

$$\begin{aligned} & DC_{3} = {\left( {OAF \times HF_{{IC}} - M_{{OHF}} } \right)} \times p_{{\text{c}}} \times p_{{{\text{cp}}}} \times {\left( {0.5 \times C_{3} + {\sum\limits_{A + 1}^{90} {p_{{{\text{cf}}}} \times p_{{\text{l}}} \times C_{3} \times \frac{1}{{{\left( {1 + r} \right)}^{n} }}} }} \right)}. \\ & \\ \end{aligned} $$
(10)

Non-medical costs for research, education and investments (DC4)

Determination of the gender-specific portion of all OHF-attributable medical costs of the year 2002 from the entire medical costs of the year 2002 C t and application to the costs for research, education and investments C 4:

$$DC_{4} = \frac{{DC_{1} + DC_{2} + DC_{{3{\left( {2002} \right)}}} }}{{C_{t} }} \times C_{4} .$$
(11)

Indirect costs

Yearly productivity (P)

Age- and gender-specific multiplication of the sum of yearly average gross salaries GS and employer participation in social security S by the probability of a paid activity p w. Addition of the product of the yearly unpaid work hours T and net salary per hour of a household helper:

(12)

Sickness absence (IC1)

Age- and gender-specific multiplication of the OAF by the product of inpatient HF cases HF IC and average HF-associated inability to work I W as well as HF-associated rehabilitation days HF RD followed by evaluation with P:

$$IC_{1} = OAF \times {\left( {HF_{{IC}} \times I_{W} + HF_{{RD}} } \right)} \times P.$$
(13)

Early retirement (IC2)

Age- and gender-specific multiplication of the OAF by the early retirements ER and the severity level of the early retirement SC. Consideration of the first year at 50% and evaluation with P. Starting at 70 years old, reduction of unpaid productivity by 10% every 5 years (not shown in formula) and discounting future n years by r = 5%:

$$IC_{2} = OAF \times ER \times SC \times {\left( {0.5 \times P + {\sum\limits_{A + 1}^{95} {p_{{\text{l}}} \times P \times \frac{1}{{{\left( {1 + r} \right)}^{n} }}} }} \right)}.$$
(14)

Mortality (IC3)

Determination as in early retirement, but based on OHF-attributable deaths M OHF :

$$IC_{3} = M_{{OHF}} \times {\left( {0.5 \times P + {\sum\limits_{A + 1}^{95} {p_{{\text{l}}} \times P \times \frac{1}{{{\left( {1 + r} \right)}^{n} }}} }} \right)}.$$
(15)

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Konnopka, A., Jerusel, N. & König, HH. The health and economic consequences of osteopenia- and osteoporosis-attributable hip fractures in Germany: estimation for 2002 and projection until 2050. Osteoporos Int 20, 1117–1129 (2009). https://doi.org/10.1007/s00198-008-0781-1

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