A framework for clinical care pathway renewal: an example from inflammatory bowel disease
Bibliographic record
Abstract
BACKGROUND: Clinical care pathways (CCPs) contribute to standardized, high-quality care and reduce variation in healthcare delivery. However, CCPs must be regularly reviewed and updated to reflect current evidence-based clinical practice guidelines. In the literature, the development and implementation of CCPs is well described, but there is little to guide the process for renewal of CCPs as new evidence becomes available. METHODS: We sought to develop a recurrent framework for CCP renewal and apply this to provincial established CCPs for inflammatory bowel disease (IBD). The proposed framework was guided by a review matrix stratified based on two factors: risk to change and clinical impact of the CCPs. An in-person CCP workshop was conducted to facilitate advisor engagement, establish consensus on the review process, and apply the review matrix to existing IBD CCPs. Attendees, including gastroenterologists, nurses, pharmacists, colorectal surgeons, and a family physician, were invited to offer feedback on the proposed framework and vote on the definitions associated with each level of the matrix. They then applied the framework to existing CCPs in two voting rounds. RESULTS: A proposed framework for CCP renewal was drafted by a multidisciplinary leadership group and presented to 22 IBD stakeholders at the in-person workshop. After a discussion, attendees agreed the matrix should include four levels, based on either high or low risk to change and high or low clinical impact. Risk to change was defined as how quickly new evidence would evolve and render the CCP out of date, and clinical impact was defined as how important the CCP is to quality IBD care. Using the revised review matrix, the attendees were able to reach agreement regarding the level to be assigned to each existing CCP. CONCLUSIONS: The framework, based on risk to change and clinical impact is a valuable starting point to standardize the process of updating and renewing clinical pathways. Revising CCPs using our proposed framework ensures pathways are up-to-date and available to assist healthcare professionals in clinical decision-making. This framework can be adapted and customized to suit CCPs across healthcare disciplines and to facilitate the establishment of a renewal process.
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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 | 0.056 | 0.649 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".