Early warning systems and rapid response systems for the prevention of patient deterioration on acute adult hospital wards
Bibliographic record
Abstract
BACKGROUND: Early warning systems (EWS) and rapid response systems (RRS) have been implemented internationally in acute hospitals to facilitate early recognition, referral and response to patient deterioration as a solution to address suboptimal ward-based care. EWS and RRS facilitate healthcare decision-making using checklists and provide structure to organisational practices through governance and clinical audit. However, it is unclear whether these systems improve patient outcomes. This is the first update of a previously published (2007) Cochrane Review. OBJECTIVES: To determine the effect of EWS and RRS implementation on adults who deteriorate on acute hospital wards compared to people receiving hospital care without EWS and RRS in place. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase and two trial registers on 28 March 2019. We subsequently ran a MEDLINE update on 15 May 2020 that identified no further studies. We checked references of included studies, conducted citation searching, and contacted experts and critical care organisations. SELECTION CRITERIA: We included randomised trials, non-randomised studies, controlled before-after (CBA) studies, and interrupted time series (ITS) designs measuring our outcomes of interest following implementation of EWS and RRS in acute hospital wards compared to ward settings without EWS and RRS. DATA COLLECTION AND ANALYSIS: Two review authors independently checked studies for inclusion, extracted data and assessed methodological quality using standard Cochrane and Effective Practice and Organisation of Care (EPOC) Group methods. Where possible, we standardised data to rates per 1000 admissions; and calculated risk differences and 95% confidence intervals (CI) using the Newcombe and Altman method. We reanalysed three CBA studies as ITS designs using segmented regression analysis with Newey-West autocorrelation adjusted standard errors with lag of order 1. We assessed the certainty of evidence using the GRADE approach. MAIN RESULTS: We included four randomised trials (455,226 participants) and seven non-randomised studies (210,905 participants reported in three studies). All 11 studies implemented an intervention comprising an EWS and RRS conducted in high- or middle-income countries. Participants were admitted to 282 acute hospitals. We were unable to perform meta-analyses due to clinical and methodological heterogeneity across studies. Randomised trials were assessed as high risk of bias due to lack of blinding participants and personnel across all studies. Risk of bias for non-randomised studies was critical (three studies) due to high risk of confounding and unclear risk of bias due to no reporting of deviation from protocol or serious (four studies) but not critical due to use of statistical methods to control for some but not all baseline confounders. Where possible we presented original study data which reported the adjusted relative effect given these were appropriately adjusted for design and participant characteristics. We compared outcomes of randomised and non-randomised studies reported them separately to determine which studies contributed to the overall certainty of evidence. We reported findings from key comparisons. Hospital mortality Randomised trials provided low-certainty evidence that an EWS and RRS intervention may result in little or no difference in hospital mortality (4 studies, 455,226 participants; results not pooled). The evidence on hospital mortality from three non-randomised studies was of very low certainty (210,905 participants). Composite outcome (unexpected cardiac arrests, unplanned ICU admissions and death) One randomised study showed that an EWS and RRS intervention probably results in no difference in this composite outcome (adjusted odds ratio (aOR) 0.98, 95% CI 0.83 to 1.16; 364,094 participants; moderate-certainty evidence). One non-randomised study suggests that implementation of an EWS and RRS intervention may slightly reduce this composite outcome (aOR 0.85, 95% CI 0.72 to 0.99; 57,858 participants; low-certainty evidence). Unplanned ICU admissions Randomised trials provided low-certainty evidence that an EWS and RRS intervention may result in little or no difference in unplanned ICU admissions (3 studies, 452,434 participants; results not pooled). The evidence from one non-randomised study is of very low certainty (aOR 0.88, 95% CI 0.75 to 1.02; 57,858 participants). ICU readmissions No studies reported this outcome. Length of hospital stay Randomised trials provided low-certainty evidence that an EWS and RRS intervention may have little or no effect on hospital length of stay (2 studies, 21,417 participants; results not pooled). Adverse events (unexpected cardiac or respiratory arrest) Randomised trials provided low-certainty evidence that an EWS and RRS intervention may result in little or no difference in adverse events (3 studies, 452,434 participants; results not pooled). The evidence on adverse events from three non-randomised studies (210,905 participants) is very uncertain. AUTHORS' CONCLUSIONS: Given the low-to-very low certainty evidence for all outcomes from non-randomised studies, we have drawn our conclusions from the randomised evidence. This evidence provides low-certainty evidence that EWS and RRS may lead to little or no difference in hospital mortality, unplanned ICU admissions, length of hospital stay or adverse events; and moderate-certainty evidence of little to no difference on composite outcome. The evidence from this review update highlights the diversity in outcome selection and poor methodological quality of most studies investigating EWS and RRS. As a result, no strong recommendations can be made regarding the effectiveness of EWS and RRS based on the evidence currently available. There is a need for development of a patient-informed core outcome set comprising clear and consistent definitions and recommendations for measurement as well as EWS and RRS interventions conforming to a standard to facilitate meaningful comparison and future meta-analyses.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".