Health Technology Assessment and Value‐Based Care
Bibliographic record
Abstract
Health systems internationally face challenges in incorporating healthcare innovations, including new expensive cancer therapies, into existing budgets. Many are placing increasing emphasis on value-based care and health technology assessment (HTA) to help determine health system priorities and steward evidence-based decisions on cancer care funding. Value-based care seeks to optimize the efficiency of public investments in health systems, set priorities for the allocation of scarce resources, and manage the opportunity costs of allocative decisions. HTA is a decision-aid tool that can assist health professionals and decision makers to design and implement value-based policies on health technology uptake and use. Innovations in cancer biotechnology and care are driving the emergence of high-cost interventions that create challenges for the efficient use of health system resources and deepen the relevance of HTA to achieving value-based cancer care. Here we overview the current landscape of HTA with attention to special implications for cancer treatment and care.
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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 | 0.020 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.036 | 0.006 |
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".