The burden of osteoporosis in Saudi Arabia: a scorecard and economic model
Bibliographic record
Abstract
Objectives: Aging populations are contributing to an increased volume of osteoporotic fractures. The goals of this study were to (1) develop a scorecard on epidemiological burden, policy framework, service provision, and service uptake for osteoporosis in Saudi Arabia and (2) estimate the direct costs of managing osteoporotic fractures in Saudi Arabia.Methods: Osteoporosis data specific to Saudi Arabia were collected through a systematic literature review and surveys with osteoporosis experts. The data were used to build a scorecard, as done previously for the European Union and select Latin American countries. The scorecard applied traffic light colour coding to identify areas of risk in Saudi Arabia’s management of osteoporosis. The data were also used to parameterize a burden of illness model. The model estimated the direct medical costs of fractures among adults aged 50–89 years in Saudi Arabia. The model included hospitalization, testing, hip fracture surgery, and drug costs.Results: In Saudi Arabia, the Ministry of Health was aware of impending increases in the number of fractures and had prioritized osteoporosis on the national agenda. Accordingly, reimbursement restrictions for osteoporosis diagnosis and treatment were minimal. However, a national fracture registry and unified system for monitoring care were not in operation. This represents a critical gap in care that will continue to contribute to the underdiagnosis and undertreatment of osteoporosis if not addressed. In total, 174,225 osteoporosis-related fractures were estimated to occur in Saudi Arabia in 2019, with an annual cost of SR2.38 billion ($636 million USD; $1.55 billion PPP). Hospitalization was the primary cost driver.Conclusions: In 2019, Saudi Arabia was expected to incur SR2.38 billion ($636 million USD; $1.55 billion PPP) in costs owing to 174,225 osteoporosis-related fractures. The establishment of a national fracture registry and implementation of fracture liaison services will be paramount to reducing the fracture burden.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".