The real cost of care: focus on value for money, rather than price-tags
Bibliographic record
Abstract
The likely basis of our natural aversion to cost-saving initiatives stems from fears that costs will override considerations for effectiveness and that costs are an unfair, biased, and distasteful frame of reference for guiding clinical decisions where life and limb are at stake. Yet, blanket prohibition of cost considerations in clinical decision-making is a ticket to disaster and is based on naive assumptions that healthcare resources are unlimited. In fact, ignoring costs will result in more loss of life and limb than a reasoned approach to considering value for dollar, since a “free-for-all” approach to decision-making results in less value extracted from our given resources. Resources in healthcare are limited, and as a result, choices must be made about what to use and what to forgo in providing medical services. Even if we could eliminate all wasteful practices and limit ourselves only to the interventions in healthcare that “work”, we would still face the quandary that resources are insufficient to meet all needs. Again, this requires making choices about what to include and what to leave out. Ideally, these decisions will be made based on the best available scientific data about what “works” (i.e., evidence-based medicine) and what range of options will offer the most value for patients from within our set of available resources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.002 | 0.012 |
| 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; both teacher heads agree on what is shown here.
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".