A conceptual framework for interprofessional shared decision making in home care: Protocol for a feasibility study
Bibliographic record
Abstract
BACKGROUND: Shared decision making (SDM) is fundamental to informed consent and client-centered care. So far, SDM frameworks have been limited to the client-physician dyad, even though care is increasingly delivered by interprofessional (IP) teams. IP collaboration is especially essential in home care, one of health care's most rapidly growing areas. This study will assess whether it is possible to practice SDM in IP home care. METHODS/DESIGN: We will use a qualitative case study and a quantitative survey to capture the macro, meso and micro levels of stakeholders in home care. The case study will follow the knowledge-to-action process framework to evaluate the work of an IP home care team at a Quebec City health center. Sources of data will include one-on-one interviews with patients, family caregivers or surrogates and significant others, and administrators; a focus group of home care health professionals; organizational documents; and government policies and standards. The interview guide for the interviews and the focus group will explore current practices and clinical problems addressed in home care; factors that could influence the implementation of the proposed IP approach to SDM; the face and content validity of the approach; and interventions to facilitate the implementation and evaluation of the approach. The survey will ask 300 health professionals working in home care at the health center to complete a questionnaire based on the Theory of Planned Behaviour that measures their intentions to engage in an IP approach to SDM. We will use our analysis of the individual interviews, the focus group and the survey to elaborate a toolkit for implementing an IP approach to SDM in home care. Finally, we will conduct a pilot study in Alberta to assess the transferability of our findings. DISCUSSION: We believe that developing tools to implement IP SDM in home care is essential to strengthening Canada's healthcare system and furthering patient-centered care. This study will contribute to the evaluation of IP SDM delivery models in home care. It will also generate practical, policy-oriented knowledge regarding the barriers and facilitators likely to influence the practice of IP SDM in home care.
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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 | 0.113 | 0.088 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.063 | 0.009 |
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".