Improving health care professionals’ collaboration to facilitate patient participation in decisions regarding life-prolonging care: An action research project
Bibliographic record
Abstract
Much improvement is needed to facilitate patient involvement in medical decision-making related to life-prolonging care. Prior research focuses mainly on the communication in the physician-patient dyad; few studies have identified how other professionals are involved. Using a Research Action design, two rounds of interviews with four interprofessional groups from various clinical settings of a health center in Quebec, Canada were conducted between 2009 and 2010. The 37 participants represented nine professions (nurse, dietitian, occupational therapist, orderly, pastoral worker, physician, physiotherapist, respiratory therapist and social worker). The first round of interviews confirmed that all of these professionals are involved, in various ways, in communicating with patients regarding their goals of care. Based on these results, the research group developed two communications tools (paper forms) to facilitate the documentation of patient care goals. The first form includes a designated area where all professionals can note patients' comments regarding decisions related to life-prolonging care. The second is a prescription form to document in the medical file the patient's goals of care. Both tools were submitted to, and fine-tuned by, the professionals in the second round of interviews. These results confirm that interprofessional collaboration to facilitate patient participation in goals-of-care decisions is both possible and valued.
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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 | 0.120 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".