Cutting Healthcare Costs without Rationing at the Bedside: Preserving the Doctor-Patient Fiduciary Relationship
Bibliographic record
Abstract
In his essay on bedside rationing, Peter Ubel argues that in an era of rising healthcare costs, it is time to relax the patient-centered ethic of physicians as unconditional patient advocates so they can individualize rationing decisions. This paper raises several concerns with the arguments and the examples he provides to make his case. First, he overlooks cost-effectiveness when making medical spending decisions. Second, his examples of wasteful, unproven and potentially harmful interventions call for physician education, not rationing, as he suggests. Third, informed patients can play a role in lowering costs through shared decision making. Fourth, individualized rationing decisions will worsen already pervasive disparities in medical care. The paper envisions the ideal cost-conscious physician as one who is knowledgeable about cost-effective practices, avoids unproven interventions whenever possible, and facilitates shared decision making through patient education. Such an individual would not, however, withhold interventions of proven benefit except when accommodating a patient's preferences for a particular therapy. The doctor and patient can only work together within the constraints of system-wide rationing if the fiduciary relationship is never violated.
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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 | 0.011 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.081 | 0.050 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".