Validation of descriptive clinical pathway criteria in the systematic identification of publications in emergency medicine
Bibliographic record
Abstract
Background Heterogeneity in both the definition and terminology of clinical pathways presents a challenge to the systematic identification of primary studies for review purposes. Recently developed clinical pathway identification criteria may facilitate both the identification and assessment of clinical pathway studies. The goal of this publication is the validation of these five criteria in a descriptive systematic review of actively implemented clinical pathway studies in the emergency department setting. The main outcome measure is the inter-rater agreement of investigators using the clinical pathway criteria. Methods We performed a systematic literature search from 2006 to 2015 using MEDLINE, EMBASE, CENTRAL, and CINAHL. All types of prospective trial designs were eligible. We identified relevant publications using the above-mentioned clinical pathway criteria. Two reviewers independently collected data using a piloted data abstraction tool. Results We identified 5947 publications, with 472 potentially relevant full text publications retrieved. Of these, 357 did not meet preliminary study inclusion criteria, leaving 115 publications where the clinical pathway criteria were applied. Ultimately, 44 publications were included. The inter-rater agreement of the criteria was very good (κ = 0.81, 95% Confidence Interval = 0.70–0.92). The vast majority of studies were excluded because the intervention did not meet the criterion of being multidisciplinary in nature. Conclusion These criteria are a useful instrument to reliably identify clinical pathway publications for systematic review purposes in an emergency department setting. Future modification of these criteria may improve their usefulness. Particular attention should be placed on clarifying what is meant by multidisciplinary involvement within the context of clinical pathway interventions, with specific emphasis placed on delineating the level of involvement of each discipline and their decision-making responsibility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".