Cost of Healthcare Services in Geriatric Neuro-oncology: A descriptive Analysis.
Bibliographic record
Abstract
BACKGROUND: The percentage of brain tumor incidence exceeds 50% in the geriatric population admitted at Khoula Hospital (a tertiary care hospital in Oman) as compared to the younger population, furthermore, geriatric patients impose a higher cost of healthcare in general. Therefore, geriatric tumor care is causing a significant burden on the healthcare service in Oman. For this reason, we have developed this study to identify the cost of care for this group. METHODS: Medical data with their costs were collected retrospectively for 108 patients diagnosed with a brain tumor above the age of 65 years and admitted at Khoula Hospital between 2016 and 2019. RESULTS: The two most common diagnoses in terms of incidence were Meningiomas (31.73%) and Glioblastomas (16.34%). Lymphoma peaked with regards to the cost, with an average cost of 8993.83 USD per diagnosis, followed by glioblastoma and then metastatic lesions (with 5039.18 and 4915.76 USD respectively). Of these surgeries, 82.61% were elective, most of which had a cost above or equal to the average. Emergency surgeries showed equal numbers above and below the average cost of surgeries (P< 0.05). The total costs of imaging were 73759.4 USD, with CT (35.8%) + MRI (32.9%) forming 68.7% of the total imaging costs. While laboratory investigation costs totaled 64110.93 USD. CONCLUSION: The cost of tumor care in Oman is variable based on multiple factors. The reported results represent useful information forming the basis for further analysis such as cost-benefit analysis, cost-effectiveness analysis, and cost-utility analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".