Development of a Pragmatic Measure for Evaluating and Optimizing Rapid Response Systems
Bibliographic record
Abstract
OBJECTIVES: Standard metrics for evaluating rapid response systems (RRSs) include cardiac and respiratory arrest rates. These events are rare in children; therefore, years of data are needed to evaluate the impact of RRSs with sufficient statistical power. We aimed to develop a valid, pragmatic measure for evaluating and optimizing RRSs over shorter periods of time. METHODS: We reviewed 724 medical emergency team and 56 code-blue team activations in a children's hospital between February 2010 and February 2011. We defined events resulting in ICU transfer and noninvasive ventilation, intubation, or vasopressor infusion within 12 hours as "critical deterioration." By using in-hospital mortality as the gold standard, we evaluated the test characteristics and validity of this proximate outcome metric compared with a national benchmark for cardiac and respiratory arrest rates, the Child Health Corporation of America Codes Outside the ICU Whole System Measure. RESULTS: Critical deterioration (1.52 per 1000 non-ICU patient-days) was more than eightfold more common than the Child Health Corporation of America measure of cardiac and respiratory arrests (0.18 per 1000 non-ICU patient-days) and was associated with >13-fold increased risk of in-hospital death. The critical deterioration metric demonstrated both criterion and construct validity. CONCLUSIONS: The critical deterioration rate is a valid, pragmatic proximate outcome associated with in-hospital mortality. It has great potential for complementing existing patient safety measures for evaluating RRS performance.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".