Evaluating processes of care and outcomes of children in hospital (EPOCH): study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: The prevention of near and actual cardiopulmonary arrest in hospitalized children is a patient safety imperative. Prevention is contingent upon the timely identification, referral and treatment of children who are deteriorating clinically. We designed and validated a documentation-based system of care to permit identification and referral as well as facilitate provision of timely treatment. We called it the Bedside Paediatric Early Warning System (BedsidePEWS). Here we describe the rationale for the design, intervention and outcomes of the study entitled Evaluating Processes and Outcomes of Children in Hospital (EPOCH). METHODS/DESIGN: EPOCH is a cluster-randomized trial of the BedsidePEWS. The unit of randomization is the participating hospital. Eligible hospitals have a Pediatric Intensive Care Unit (PICU), are anticipated to have organizational stability throughout the study, are not using a severity of illness score in hospital wards and are willing to be randomized. Patients are >37 weeks gestational age and <18 years and are hospitalized in inpatient ward areas during all or part of their hospital admission. Randomization is to either BedsidePEWS or control (no severity of illness score) in a 1:1 ratio within two strata (<200, ≥ 200 hospital beds). All-cause hospital mortality is the selected primary outcome. It is objective, independent of do-not-resuscitate status and can be reliably measured. The secondary outcomes include (1) clinical outcomes: clinical deterioration, severity of illness at and during ICU admission, and potentially preventable cardiac arrest; (2) processes of care outcomes: immediate calls for assistance, hospital and ICU readmission, and perceptions of healthcare professionals; and (3) resource utilization: ICU days and use of ICU therapies. DISCUSSION: Following funding by the Canadian Institutes of Health Research and local ethical approvals, site enrollment started in 2010 and was closed in February 2014. Patient enrollment is anticipated to be complete in July 2015. The results of EPOCH will strengthen the scientific basis for local, regional, provincial and national decision-making and for the recommendations of national and international bodies. If negative, the costs of hospital-wide implementation can be avoided. If positive, EPOCH will have provided a scientific justification for the major system-level changes required for implementation. TRIAL REGISTRATION: NCT01260831 ClinicalTrials.gov date: 14 December 2010.
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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 | 0.006 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".