Eliciting Patient Treatment Preferences: A Strategy to Integrate Evidence‐Based and Patient‐Centered Care
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The integrated patient-centered evidence-based approach to care is integral to guide practice and enhance the quality of care. In this paper, a strategy to operationalize the integrated approach is described. DESCRIPTION OF STRATEGY: The strategy flows from the processes used to synthesize the best available evidence for interventions that address a clinical problem, and to elicit patient preferences for treatment options, which is an important step in patient-centered care. The strategy consists of three phases: (1) synthesis of evidence about the effectiveness and relevance of interventions derived from research and practice; (2) generation of written material describing the nature, dose, effectiveness, and risks associated with the evidence-based interventions; and (3) using the written descriptions to elicit patient preferences. Examples from an ongoing study are presented to illustrate the implementation of the strategy within the context of research. IMPLICATIONS: Nurses are invited to apply the strategy in practice and to evaluate its feasibility and utility in enhancing the quality of care.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 it