Background
Methods
Modeling approach
Cost tracking
Determination of life time costs and fracture events
Epidemiological input data
Fracture probabilities – general population
Age | Hip | Other femur | Clinical vertebral | Humerus | Pelvis | Wrist |
---|---|---|---|---|---|---|
50-54 | 0.00038 | 0.00010 | 0.00095 | 0.00085 | 0.00018 | 0.00221 |
55-59 | 0.00071 | 0.00014 | 0.00144 | 0.00143 | 0.00028 | 0.00390 |
60-64 | 0.00104 | 0.00021 | 0.00192 | 0.00194 | 0.00038 | 0.00491 |
65-69 | 0.00187 | 0.00033 | 0.00316 | 0.00272 | 0.00071 | 0.00620 |
70-74 | 0.00334 | 0.00054 | 0.00456 | 0.00360 | 0.00127 | 0.00684 |
75-79 | 0.00772 | 0.00102 | 0.00634 | 0.00530 | 0.00285 | 0.00866 |
80-84 | 0.01605 | 0.00162 | 0.01132 | 0.00716 | 0.00544 | 0.00973 |
85-89 | 0.02791 | 0.00262 | 0.01378 | 0.00872 | 0.00890 | 0.00916 |
90-94 | 0.03625 | 0.00324 | 0.01339 | 0.00861 | 0.01172 | 0.00740 |
95+ | 0.03960 | 0.00382 | 0.01052 | 0.00795 | 0.01118 | 0.00530 |
Fracture probabilities for women with and without a previous fracture
Fracture probabilities for women with and without osteoporosis
Fracture probabilities for women living and not living in a NH
Probability of developing osteoporosis
Probability of institutionalization in a NH
Mortality
Cost input data
Cost category* | Hip | Other femur | Clinical vertebral | Humerus | Pelvis | Wrist |
---|---|---|---|---|---|---|
Hospital treatment (plus outpatient aftercare costs) | 8,554 | 8,395 | 6,324 | 5,764 | 5,005 | 3,794 |
Rehabilitation (if required after hospitalization) | 2,187 | 2,187 | 2,092 | 2,337 | 2,177 | 2,337 |
Outpatient costs (if no hospitalization required) | n. a. | n. a. | 1,614 | 835 | 963 | 835 |
Professional home care (age > 65, not in NH) | 2,174 | 2,174 | 2,212 | 937 | 2,174 | 525 |
Informal home care (age > 65, not in NH) | 2,361 | 2,361 | 2,016 | 2,961 | 2,361 | 581 |
Yearly long term care cost (age > 65, in NH) | 25,759 | 25,759 | 25,759 | 25,759 | 25,759 | 25,759 |
Inpatient costs
Outpatient costs
Informal care costs
Productivity costs
Model assumptions
Assumptions regarding event probabilities | Impact§
|
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We applied osteoporosis prevalence rates and BMD-values from US-NHANES III reference data | *** |
We estimated “total” fracture probabilities by dividing fracture probabilities based on hospital cases with age-independent hospital probabilities |
**
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We assumed highest fracture related NH probability when more than one fractures occurs in the same time interval |
**
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We modeled fracture related entry in a NH only after a hospital stay |
**
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We assumed that only NH entries within 3 months after a fracture may be attributable to the fracture event itself |
**
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We applied age-dependent relative fracture risk by one standard deviation decrease in BMD to hip fractures and age-independent relative risks to other fractures |
**
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We assumed that osteoporosis risk attributions were calculated exclusively on BMD values measured at the femoral neck |
**
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We assumed that osteoporosis prevalence rates do not differ between women living in a NH and women who do not |
*
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We applied relative fracture risk and prevalence for previous fractures from an international meta-analysis |
*
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We applied relative fracture risk by one standard deviation decrease in BMD from international studies |
*
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We applied fracture mortality data from a Canadian study |
*
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We assumed the highest fracture excess mortality when more than one fracture occurs in the same time interval |
*
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We allowed first entry in a NH firstly for women aged 65 or older |
*
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We assumed that individuals in a NH remain there for their remaining lifetime |
*
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We assumed that patients with osteoporosis will have osteoporosis for their remaining lifetime |
*
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We allowed a maximum possible age of 100 years |
*
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Assumptions regarding costing
| |
We assumed that rehabilitation probabilities after a hospital stay do not differ between women living in NH and those who do not. | ** |
We applied Austria data for average hours of informal and professional home care by fracture type, also we assumed that the consumed hours are equivalent for hip, other femur and pelvis | ** |
We assumed age-dependent fracture unit costs | * |
We assumed that the outpatient costs for humerus and wrist as well as the costs for pelvis, other femur and hip fractures are equivalent | * |
We took outpatient resource use data from a study considering fracture patients with inflammatory bowel disease | * |
We assumed that average informal and professional home care costs are only applicable for individuals not living in NH aged older than 65 years | * |
Scenario analysis
Sensitivity analysis
Results
Base case
Direct cost
| Undiscounted | Discounted (3%) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
By fracture type
| Average risk (95%UI) | % | Not at risk (95%UI) | % | Excess (95%UI) | % | Average risk (95%UI) | % | Not at risk (95%UI) | % | Excess (95%UI) | % |
Hip
| 3,399 | 42.7 | 1,449 | 34.4 | 1,950 | 52.1 | 1,277 | 39.1 | 585 | 30.9 | 692 | 50.4 |
(2,933-4,116) | (398–2,466) | (1,070-3,179) | (1,102-1,541) | (204–939) | (394–1,108) | |||||||
Other femur
| 388 | 4.9 | 188 | 4.5 | 200 | 5.3 | 157 | 4.8 | 85 | 4.5 | 72 | 5.2 |
(316–461) | (83–270) | (106–331) | (126–181) | (44–114) | (39–115) | |||||||
Clinical vertebral
| 1,452 | 18.2 | 880 | 20.9 | 573 | 15.3 | 623 | 19.1 | 404 | 21.3 | 219 | 15.9 |
(1,156-2,042) | (504–1,425) | (279–983) | (494–886) | (251–631) | (109–367) | |||||||
Humerus
| 1,182 | 14.9 | 664 | 15.8 | 518 | 13.8 | 532 | 16.3 | 328 | 17.3 | 204 | 14.9 |
(951–1,377) | (320–846) | (299–829) | (422–611) | (180–395) | (121–318) | |||||||
Pelvis
| 773 | 9.7 | 413 | 9.8 | 360 | 9.6 | 295 | 9.0 | 169 | 8.9 | 126 | 9.2 |
(617–958) | (173–646) | (176–609) | (236–364) | (83–253) | (63–209) | |||||||
Wrist
| 763 | 9.6 | 621 | 14.7 | 143 | 3.8 | 385 | 11.8 | 324 | 17.1 | 61 | 4.4 |
(557–1,070) | (423–876) | (71–252) | (282–550) | (229–467) | (31–103) | |||||||
Total
| 7,958 | 100 | 4,214 | 100 | 3,744 | 100 | 3,269 | 100 | 1,895 | 100 | 1,374 | 100 |
(6,883-8,940) | (2,027-6,018) | (2,045-5,939) | (2,814-3,664) | (1,064-2,538) | (774–2,134) |
Direct cost
| Undiscounted | Discounted (3%) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
By healthcare sector
| Average risk (95%UI) | % | Not at risk (95%UI) | % | Excess (95%UI) | % | Average risk (95%UI) | % | Not at risk (95%UI) | % | Excess (95%UI) | % |
Inpatient
| ||||||||||||
Hospital | 4,237 | 36.2 | 2,170 | 36.3 | 2,067 | 36.2 | 1,743 | 38.9 | 992 | 39.9 | 751 | 37.6 |
(3,853-4,500) | (1,029-3,085) | (1,147-3,322) | (1,582-1,830) | (565–1,306) | (432–1,181) | |||||||
Rehabilitation | 272 | 2.3 | 125 | 2.1 | 146 | 2.6 | 105 | 2.4 | 53 | 2.1 | 52 | 2.6 |
(245–290) | (42–182) | (87–241) | (93–110) | (23–72) | (31–83) | |||||||
Long term care | 3,731 | 31.9 | 1,758 | 29.4 | 1,973 | 34.5 | 1,210 | 27.0 | 590 | 23.7 | 620 | 31.1 |
(3,349-4,159) | (475–2,834) | (920–3,481) | (1,071-1,324) | (185–913) | (285–1,073) | |||||||
Outpatient
| ||||||||||||
Physiotherapy, physician, analgesics | 1,000 | 8.6 | 579 | 9.7 | 422 | 7.4 | 433 | 9.7 | 276 | 11.1 | 157 | 7.9 |
(418–1,949) | (182–1,182) | (132–1,017) | (182–825) | (99–544) | (52–370) | |||||||
Prof. home care | 1,105 | 9.5 | 605 | 10.1 | 500 | 8.7 | 443 | 9.9 | 257 | 10.4 | 186 | 9.3 |
(800–1,401) | (275–925) | (262–843) | (320–561) | (130–379) | (100–308) | |||||||
Family
| ||||||||||||
Informal care | 1,344 | 11.5 | 735 | 12.3 | 609 | 10.7 | 544 | 12.1 | 316 | 12.7 | 228 | 11.5 |
(1,205-1,414) | (370–997) | (346–991) | (487–569) | (178–409) | (133–365) | |||||||
Total
| 11,689 | 100 | 5,973 | 100 | 5,716 | 100 | 4,479 | 100 | 2,485 | 100 | 1,995 | 100 |
(10,406-12,929) | (2,533-8,757) | (2,988-9,466) | (3,942-4,898) | (1,258-3,424) | (1,076-3,215) |
Scenario analysis
Sensitivity analysis
Validation
Age | Fracture rates | Fractures per woman | Proportion | |
---|---|---|---|---|
expected | modeled | 0 | 77.63% | |
50-54 | 0.0004 | 0.0003 | 1 | 17.57% |
60-64 | 0.0010 | 0.0011 | 2 | 3.92% |
70-74 | 0.0033 | 0.0034 | 3 | 0.75% |
80-84 | 0.0161 | 0.0156 | 4 | 0.12% |
90-95 | 0.0363 | 0.0355 | 5 | 0.02% |
95+ | 0.0396 | 0.0400 | 6 | 0.00% |