Exploring Factors in the Systematic Use of Outcome Measures: A Multi-Disciplinary Rehabilitation Team Perspective
Bibliographic record
Abstract
Purpose: The implementation of routine outcome measurement was initiated as a quality improvement initiative in a unit delivering intensive functional rehabilitation for people with lower limb amputation. Two years post-implementation, completion rates remained low which raised the need to gain an indepth understanding of the factors that might impact the systematic use of Outcome Measures (OMs). Method: A qualitative exploratory study embedded in the ongoing quality improvement initiative was designed. Data were gathered through a focus group with members of a multidisciplinary rehabilitation team. A deductive content analysis was performed using Consolidated Framework for Implementation Research (CFIR) as a guide to explore factors that impact routine outcome measurement. Results: Respondents perceived OMs as valid and offering clear advantages in clinical practice. At the organizational level, lack of fit with clinical practice, loss of project leaders and lack of clear management directives had negative repercussions on the use of OMs. Conclusion: Our results suggest that a dedicated project leader throughout the implementation process and effective communication may contribute to bypassing barriers associated to practice changes leading to a more systematic use of OMs among clinicians.
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How this classification was reachedexpand
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".