Understanding the role of the physiatrist and how to improve the continuum of care for trauma patients: a qualitative study
Bibliographic record
Abstract
PURPOSE: Transitions across care settings can be stressful for trauma patients, and when poorly executed, can lead to poor outcomes. Early physical medicine and rehabilitation (PM&R) consults in acute care settings can optimize the continuum of care for trauma patients, but there is a need for additional insight on its impact. This study aimed to better understand how early PM&R consults influence the continuum of care between acute and rehabilitation trauma settings. METHODS: Four focus groups were conducted with 21 trauma acute care and rehabilitation staff, and data were analyzed via content analysis. RESULTS: The main themes identified were: (1) patient-level considerations (i. readiness for rehab [mental health]; ii. patient education and expectations for rehab); (2) clinical-team considerations (i. physiatry role clarity and role limitations; ii. access and accuracy of information; iii. departmental silos); and (3) system-level considerations (i. occupancy and discharge pressures; ii. inter-facility coordination and patient flow). CONCLUSIONS: Although both acute and rehabilitation care staff find early PM&R consults as being important to support the recovery of trauma patients, there is a need for greater role clarity of the physiatrist across settings and a more refined implementation approach to better meet the communication needs of clinical staff. Implications for RehabilitationEarly physical medicine and rehabilitation consults are seen by acute care and rehabilitation front-line staff as valuable for optimizing the continuum of trauma care.There is a lack of clarity on the role of physiatrists among acute care and rehabilitation clinical staff.The physiatrist plays an important role to help prepare trauma patients for rehabilitation. For patients with complex physical and/or mental health challenges, the physiatrist can also serve as an advocate for access to rehabilitation services.
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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 | 0.020 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".