Supporting patients facing difficult health care decisions: use of the Ottawa Decision Support Framework.
Bibliographic record
Abstract
OBJECTIVE: To investigate family physicians' views on factors that make health care decisions difficult for patients, interventions family physicians use to support patients making decisions, and interventions proposed by the Ottawa Decision Support Framework (ODSF). DESIGN: Thirteen group discussions. SETTING: Five family practice units. PARTICIPANTS: One hundred twenty family physicians. INTERVENTIONS: The multifaceted implementation intervention consisted of feedback from participants, a reminder at point of care, and an interactive workshop. During the workshop, family physicians were asked about their views on 2 videos both showing the concluding phase of a simulated clinical encounter with a woman facing a decision about hormone therapy. One video showed usual care; the other showed use of the ODSF process and related tools. Content was analyzed using observations by non-participants, field notes, material collected from participants during workshops, evaluation forms completed at the end of workshops, and comments written on exit questionnaires from the implementation trial. MAIN OUTCOME MEASURES: Family physicians' views on the types of difficult decisions their patients face, the factors that make decisions difficult for patients, the interventions family physicians use to support patients' decisions, and the interventions proposed by the ODSF. RESULTS: The 2 most frequently cited factors making decisions difficult for patients were experiencing uncertainty and fears about adverse outcomes. Before being introduced to the ODSF, participants had used mostly information-related strategies to provide decision support. After learning about the ODSF, participants overwhelmingly identified assessing patients' values as a priority. At the end of the workshop, the 5 changes in practice participants most frequently intended to make were, in order of importance, to assess patients' values, to ask about patients' preferred role in decision making, to screen for decisional conflict, to assess support or undue pressure on patients, and to increase patients' involvement in decision making. CONCLUSION: The ODSF process and related tools have the potential to broaden family physicians' views on supporting patients facing difficult decisions.
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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 | 0.032 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".