Impact of nighttime Rapid Response Team activation on outcomes of hospitalized patients with acute deterioration
Bibliographic record
Abstract
BACKGROUND: Rapid Response Teams (RRTs) are groups of healthcare providers that are used by many hospitals to respond to acutely deteriorating patients admitted to the wards. We sought to identify outcomes of patients assessed by RRTs outside standard working hours. METHODS: We used a prospectively collected registry from two hospitals within a single tertiary care-level hospital system between May 1, 2012, and May 31, 2016. Patient information, outcomes, and RRT activation information were stored in the hospital data warehouse. Comparisons were made between RRT activation during daytime hours (0800-1659) and nighttime hours (1700-0759). The primary outcome was in-hospital mortality, analyzed using a multivariable logistic regression model. RESULTS: A total of 6023 RRT activations on discrete patients were analyzed, 3367 (55.9%) of which occurred during nighttime hours. Nighttime RRT activation was associated with increased odds of mortality, as compared with daytime RRT activation (adjusted OR 1.34, 95% CI 1.26-1.40, P = 0.02). The time periods associated with the highest odds of mortality were 0600-0700 (adjusted OR 1.30, 95% CI 1.09-1.61) and 2300-2400 (adjusted OR 1.34, 95% CI 1.01-1.56). Daytime RRT activation was associated with increased odds of intensive care unit admission (adjusted OR 1.40, 95% CI 1.31-1.50, P = 0.02). Time from onset of concerning symptoms to RRT activation was shorter among patients assessed during daytime hours (P < 0.001). CONCLUSIONS: Acutely deteriorating ward patients assessed by an RRT at nighttime had a higher risk of in-hospital mortality. This work identifies important shortcomings in health service provision and quality of care outside daytime hours, highlighting an opportunity for quality improvement.
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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 | 0.000 | 0.000 |
| 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".