Potential Utility of an Independent Decision-Making Board for Seriously Ill Patients Lacking Decisional Capacity
Bibliographic record
Abstract
Published: B. A. Noah, Potential Utility of an Independent Decision-Making Board for Seriously Ill Patients Lacking Decisional Capacity, 6 ETHICS, MED. AND PUB. HEALTH J. 63 (2018). Physicians acknowledge that they are providing unnecessary medical care at the end of life for a variety of reasons, including fear of malpractice litigation, Medicare’s fee-for service reimbursement mechanism, patient and family requests for care, a culture of denial of mortality, and a physician culture which views a patient’s death as a professional failure. Recent data suggest that more than one-fifth of medical care provided at the end of life is unnecessary. Although the problem of over-provision of medical care is now well recognized in the legal and medical literatures, private-ordering solutions, such as better communication training for physicians or improved patient decision aids, will have only marginally ameliorating effects. The inherent challenges in making medical decisions during terminal illness become even more complex when patients are unable to make these choices for themselves. Although patient autonomy, implemented via informed consent, is the primary principle that governs medical decision-making, including on behalf of patients who have lost decisional capacity, insufficient evidence of the patient’s wishes coupled with uncertainty about prognosis often leaves physicians and family members in a quandary as to whether to implement or to continue providing therapeutic treatment or life-prolonging care. The default operation of the surrogate consent process in the U.S. means that, for patients who do not clearly opt out of life-prolonging treatment before losing decisional capacity, the path of least resistance often will lead to decisions in favor of initiating or continuing life-prolonging care. This state of affairs can lead to substantial stress for all parties concerned, along with the potential for conflict. This Article considers the potential utility and transplantability of a Canadian public decision-support mechanism in this context. In 1996, the provincial government of Ontario implemented a Consent and Capacity Board (CCB), an independent expert body charged, among other things, to mediate and resolve disputes in the context of surrogate decision-making. Two-plus decades of CCB evidence suggest this it provides a better shared, less confrontational and more robust decision-making process than is currently available within the U.S. surrogate decision-making rules. Thus, a CCB type mechanism has the potential to also improve surrogate decision-making at the end of life in the U.S. and this paper discusses the extent to which it is capable of being ‘‘transplanted’’ into the U.S. health system on a state-by-state basis.
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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 | 0.081 | 0.257 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.011 | 0.015 |
| Insufficient payload (model declined to judge) | 0.032 | 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".