Impact of nighttime Rapid Response Team activation on outcomes of hospitalized patients with acute deterioration

Fernando, Shannon M.; Reardon, Peter M.; Bagshaw, Sean M.; Scales, Damon C.; Murphy, Kyle; Shen, Jennifer; Tanuseputro, Peter; Heyland, Daren K.; Kyeremanteng, Kwadwo

doi:10.1186/s13054-018-2005-1

Cited by 25 publications

(33 citation statements)

References 41 publications

(48 reference statements)

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“…with daytime activation, which is in conflict with previous studies [21,22]. This may be attributable to the difference in the activation method of the MET: while the MET was activated only by calling from the ward staff in those studies, MET activation in our study was based on electronic medical record-based screening as well as calling.…”

Section: Plos Onecontrasting

confidence: 82%

Predictive powers of the Modified Early Warning Score and the National Early Warning Score in general ward patients who activated the medical emergency team

et al. 2020

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Background The current early warning scores may be insufficient for medical emergency teams (METs) to use in assessing the severity and the prognosis of activated patients. We evaluated the predictive powers of the Modified Early Warning Score (MEWS) and the National Early Warning Score (NEWS) for 28-day mortality and to analyze predictors of 28-day mortality in general ward patients who activate the MET. Methods Adult general ward inpatients who activated the MET in a tertiary referral teaching hospital between March 2009 and December 2016 were included. The demographic and clinical characteristics and physiologic parameters at the time of MET activation were collected, and MEWS and NEWS were calculated. Results A total of 6,729 MET activation events were analyzed. Patients who died within 28 days were younger (mean age 60 vs 62 years), were more likely to have malignancy (72% vs 53%), were more likely to be admitted to the medical department rather than the surgical department (93% vs 80%), had longer intervals from admission to MET activation (median, 7 vs 5 days), and were less likely to activate the MET during nighttime hours (5 PM to 8 AM) (61% vs 66%) compared with those who did not die within 28 days (P < 0.001 for all comparisons). The areas under the receiver operating characteristic curves of MEWS and NEWS for 28-day mortality were 0.58 (95% CI, 0.56-0.59) and 0.60 (95% CI, 0.59-0.62), which were inferior to that of the logistics regression model (0.73; 95% CI, 0.72-0.74; P < 0.001 for both comparisons).

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Section: Plos Onecontrasting

confidence: 82%

Predictive powers of the Modified Early Warning Score and the National Early Warning Score in general ward patients who activated the medical emergency team

et al. 2020

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“…We found that hematologic oncology inpatients who experience RRS activation had an in-hospital mortality rate of 41.9%, which is higher than mortality among other previously studied RRS populations, including the elderly [37], general oncology patients [41], and surgical patients [42] (36.2%, 33%, and 28.4%, respectively). In our database, in-hospital mortality among non-hematologic oncology RRS patients was 29.9% [43], suggesting markedly higher mortality among the hematologic oncology population, as expected. This suggests that the hematologic oncology population is uniquely vulnerable, which may be due to the risk of infection and treatment-related complications in these patients, as described earlier.…”

Section: Discussionsupporting

confidence: 67%

Outcomes of hospitalized hematologic oncology patients receiving rapid response system activation for acute deterioration

et al. 2019

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Background Patients with hematologic malignancies who are admitted to hospital are at increased risk of deterioration and death. Rapid response systems (RRSs) respond to hospitalized patients who clinically deteriorate. We sought to describe the characteristics and outcomes of hematologic oncology inpatients requiring rapid response system (RRS) activation, and to determine the prognostic accuracy of the SIRS and qSOFA criteria for in-hospital mortality of hematologic oncology patients with suspected infection. Methods We used registry data from two hospitals within The Ottawa Hospital network, between 2012 and 2016. Consecutive hematologic oncology inpatients who experienced activation of the RRS were included in the study. Data was gathered at the time of RRS activation and assessment. The primary outcome was in-hospital mortality. Logistical regression was used to evaluate for predictors of in-hospital mortality. Results We included 401 patients during the study period. In-hospital mortality for all included patients was 41.9% (168 patients), and 145 patients (45%) were admitted to ICU following RRS activation. Among patients with suspected infection at the time of RRS activation, Systemic Inflammatory Response Syndrome (SIRS) criteria had a sensitivity of 86.9% (95% CI 80.9–91.6) and a specificity of 38.2% (95% CI 31.9–44.8) for predicting in-hospital mortality, while Quick Sequential Organ Failure Assessment (qSOFA) criteria had a sensitivity of 61.9% (95% CI 54.1–69.3) and a specificity of 91.4% (95% CI 87.1–94.7). Factors associated with increased in-hospital mortality included transfer to ICU after RRS activation (adjusted odds ratio [OR] 3.56, 95% CI 2.12–5.97) and a higher number of RRS activations (OR 2.45, 95% CI 1.63–3.69). Factors associated with improved survival included active malignancy treatment at the time of RRS activation (OR 0.54, 95% CI 0.34–0.86) and longer hospital length of stay (OR 0.78, 95% CI 0.70–0.87). Conclusions Hematologic oncology inpatients requiring RRS activation have high rates of subsequent ICU admission and mortality. ICU admission and higher number of RRS activations are associated with increased risk of death, while active cancer treatment and longer hospital stay are associated with lower risk of mortality. Clinicians should consider these factors in risk-stratifying these patients during RRS assessment. Electronic supplementary material The online version of this article (10.1186/s13054-019-2568-5) contains supplementary material, which is available to authorized users.

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“…There are no electronic or manual screening tools used for early detection of deterioration on the hospital wards. We conducted a retrospective analysis of prospectively collected data from The Ottawa Hospital Data Warehouse, a health administrative database that has been used widely in previous research [ 12 – 15 ]. Data quality assessments were performed during development and are executed routinely as new data are included.…”

Section: Methodsmentioning

confidence: 99%

Emergency Department disposition decisions and associated mortality and costs in ICU patients with suspected infection

et al. 2018

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BackgroundFollowing emergency department (ED) assessment, patients with infection may be directly admitted to the intensive care unit (ICU) or alternatively admitted to hospital wards or sent home. Those admitted to the hospital wards or sent home may experience future deterioration necessitating ICU admission.MethodsWe used a prospectively collected registry from two hospitals within a single tertiary care hospital network between 2011 and 2014. Patient information, outcomes, and costs were stored in the hospital data warehouse. Patients were categorized into three groups: (1) admitted directly from the ED to the ICU; (2) initially admitted to the hospital wards, with ICU admission within 72 hours of initial presentation; or (3) sent home from the ED, with ICU admission within 72 hours of initial presentation. Using multivariable logistic regression, we sought to compare outcomes and total costs between groups. Total costs were evaluated using a generalized linear model.ResultsA total of 657 patients were included; of these, 338 (51.4%) were admitted directly from the ED to the ICU, 246 (37.4%) were initially admitted to the wards and then to the ICU, and 73 (11.1%) were initially sent home and then admitted to the ICU. In-hospital mortality was lowest among patients admitted directly to the ICU (29.5%), as compared with patients admitted to the ICU from wards (42.7%) or home (61.6%) (P < 0.001). As compared with direct ICU admission, disposition to the ward was associated with an adjusted OR of 1.75 (95% CI, 1.22–2.50; P < 0.01) for mortality, and disposition home was associated with an adjusted OR of 4.02 (95% CI, 2.32–6.98). Mean total costs were lowest among patients directly admitted to the ICU ($26,748), as compared with those admitted from the wards ($107,315) and those initially sent home ($71,492) (P < 0.001). Cost per survivor was lower among patients directly admitted to the ICU ($37,986) than either those initially admitted to the wards ($187,230) or those sent home ($186,390) (P < 0.001).ConclusionsIn comparison with direct admission to the ICU, patients with suspected infection admitted to the ICU who have previously been discharged home or admitted to the ward are associated with higher in-hospital mortality and costs.Electronic supplementary materialThe online version of this article (10.1186/s13054-018-2096-8) contains supplementary material, which is available to authorized users.

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Impact of nighttime Rapid Response Team activation on outcomes of hospitalized patients with acute deterioration

Cited by 25 publications

References 41 publications

Predictive powers of the Modified Early Warning Score and the National Early Warning Score in general ward patients who activated the medical emergency team

Predictive powers of the Modified Early Warning Score and the National Early Warning Score in general ward patients who activated the medical emergency team

Outcomes of hospitalized hematologic oncology patients receiving rapid response system activation for acute deterioration

Emergency Department disposition decisions and associated mortality and costs in ICU patients with suspected infection

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