Development of a Decision Aid for Patients and Families Considering Hospice
Bibliographic record
Abstract
Background: Hospice is underutilized. Miscommunication, decisional complexity, and misunderstanding around engaging hospice may contribute. Shared decision making (SDM), aided by patient decision aids (PtDAs), can improve knowledge and decision quality. Currently, there are no freely available hospice-specific PtDA to facilitate conversions between patients and providers about hospice care. Objective: To develop a theory-based and unbiased hospice specific PtDA. Design: Guided by the Ottawa Decision Support Framework and International Patient Decision Aid Standards, we used a theory-driven, eight-step, iterative, user-centered approach with multistakeholder input to develop a hospice-specific PtDA for anyone facing end-of-life decisions. Subjects: Feedback was obtained from a 10-member Patient Advisory Panel composed of lay patient advisors; focus groups of hospice providers, family caregivers, and patients; and the Palliative Care Research Group at University of Colorado Hospital consisting of palliative care physicians, midlevel providers, nurses, social workers, chaplains, and researchers. Results: There are many challenges in developing an unbiased hospice decision aid, including (1) balancing the provision of education (eligibility, payment) with decisional support, (2) clarifying values and incorporating emotion, (3) ideally representing the potential downsides of hospice, and (4) adequately capturing and describing care alternatives to hospice. Within this context, we developed a 12-page article and 17-minute video PtDAs. The PtDA openly acknowledges the emotional complexity of the decision and incorporates values clarification techniques to help decision makers reflect and evaluate their goals and preferences for end-of-life care. Conclusions: Hospice decision making is complex and emotional, demanding high-quality SDM aided by a formal PtDA. This work resulted in a freely available article and video PtDA for patients considering hospice. The effectiveness and implementation of these tools will be studied in future research. Clinical Trials Registration (NCT03794700 & NCT04458090).
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".