Implementing a case management intervention for frequent users of the emergency department (I-CaM): an effectiveness-implementation hybrid trial study protocol
Bibliographic record
Abstract
BACKGROUND: ED overcrowding represents a significant public health problem in developed countries. Frequent users of the emergency departments (FUEDs; reporting 5 or more ED visits in the past year) are often affected by medical, psychological, social, and substance use problems and account for a disproportionately high number of ED visits. Past research indicates that case management (CM) interventions are a promising way to reduce ED overcrowding and improve FUEDs' quality of life. There is, however, very limited knowledge about how to disseminate and implement this intervention on a large scale to diverse clinical settings, including community hospitals and non-academic centers. This paper describes the protocol of a research project aiming to implement a CM intervention tailored to FUEDs in the public hospitals with ED in the French-speaking region of Switzerland and evaluate both the implementation process and effectiveness of the CM intervention. METHODS: This research project uses a hybrid study design assessing both implementation and clinical outcomes. The implementation part of the study uses mixed methods a) to describe quantitatively and qualitatively factors that influence the implementation process, and b) to examine implementation effectiveness. The clinical part of the study uses a within-subject design (pre-post intervention) to evaluate participants' trajectories on clinical variables (e.g., quality of life, ED use) after receiving the CM intervention. We designed the study based on two implementation science frameworks. The Generic Implementation Framework guided the overall research protocol design, whereas the RE-AIM (reach, efficacy, adoption, implementation and maintenance) framework guided the implementation and effectiveness evaluations. DISCUSSION: This research project will contribute to implementation science by providing key insights into the processes of implementing CM into broader practice. This research project is also likely to have both clinical and public health implications. TRIAL REGISTRATION: NCT03641274 , Registered 20 August 2018.
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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 | 0.040 | 0.035 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.030 | 0.005 |
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".