Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial.

OBJECTIVES: Machine learning algorithms can outperform older methods in predicting clinical deterioration, but rigorous prospective data on their real-world efficacy are limited. We hypothesized that real-time machine learning generated alerts sent directly to front-line providers would reduce escalations. DESIGN: Single-center prospective pragmatic nonrandomized clustered clinical trial. SETTING: Academic tertiary care medical center. PATIENTS: Adult patients admitted to four medical-surgical units. Assignment to intervention or control arms was determined by initial unit admission. INTERVENTIONS: Real-time alerts stratified according to predicted likelihood of deterioration sent either to the primary team or directly to the rapid response team (RRT). Clinical care and interventions were at the providers' discretion. For the control units, alerts were generated but not sent, and standard RRT activation criteria were used. MEASUREMENTS AND MAIN RESULTS: The primary outcome was the rate of escalation per 1000 patient bed days. Secondary outcomes included the frequency of orders for fluids, medications, and diagnostic tests, and combined in-hospital and 30-day mortality. Propensity score modeling with stabilized inverse probability of treatment weight (IPTW) was used to account for differences between groups. Data from 2740 patients enrolled between July 2019 and March 2020 were analyzed (1488 intervention, 1252 control). Average age was 66.3 years and 1428 participants (52%) were female. The rate of escalation was 12.3 vs. 11.3 per 1000 patient bed days (difference, 1.0; 95% CI, -2.8 to 4.7) and IPTW adjusted incidence rate ratio 1.43 (95% CI, 1.16-1.78; p < 0.001). Patients in the intervention group were more likely to receive cardiovascular medication orders (16.1% vs. 11.3%; 4.7%; 95% CI, 2.1-7.4%) and IPTW adjusted relative risk (RR) (1.74; 95% CI, 1.39-2.18; p < 0.001). Combined in-hospital and 30-day-mortality was lower in the intervention group (7% vs. 9.3%; -2.4%; 95% CI, -4.5% to -0.2%) and IPTW adjusted RR (0.76; 95% CI, 0.58-0.99; p = 0.045). CONCLUSIONS: Real-time machine learning alerts do not reduce the rate of escalation but may reduce mortality.

The impact of frailty and rapid response team activation on patients admitted to the intensive care unit: A case-control matched, observational, single-centre cohort study.

BACKGROUND: Frailty is a multi-dimensional syndrome associated with mortality and adverse outcomes in patients admitted to the intensive care unit (ICU). Further investigation is warranted to explore the interplay among factors such as frailty, clinical deterioration triggering a medical emergency team (MET) review, and outcomes following admission to the ICU. METHODS: Single-centre, retrospective observational case-control study of adult patients (>18 years) admitted to a medical-surgical ICU with (cases) or without (controls) a preceding MET review between 4 h and 14 days prior. Matching was performed for age, ICU admission diagnosis, Acute Physiology and Chronic Health Evaluation III (APACHE III) score and the 8-point Clinical Frailty Scale (CFS). Cox proportional hazard regression modelling was performed to determine associations with 30-day mortality after admission to ICU. RESULTS: A total of 2314 matched admissions were analysed. Compared to non-frail patients (CFS 1-4), mortality was higher in all frail patients (CFS 5-8), at 31% vs. 13%, and in frail patients admitted after MET review at 33%. After adjusting for age, APACHE, antecedent MET review and CFS in the Cox regression, mortality hazard ratio increased by 26% per CFS point and by 3% per APACHE III point, while a MET review was not an independent predictor. Limitations of medical treatment occurred in 30% of frail patients, either with or without a MET antecedent, and this was five times higher compared to non-frail patients. CONCLUSION: Frail patients admitted to ICU have a high short-term mortality. An antecedent MET event was associated with increased mortality but did not independently predict short-term survival when adjusting for confounding factors. The intrinsic significance of frailty should be primarily considered during MET review of frail patients. This study suggests that routine frailty assessment of hospitalised patients would be helpful to set goals of care when admission to ICU could be considered.

Patient outcomes following medical emergency team review on general wards: Development of predictive models.

AIM: To develop and internally validate risk prediction models for subsequent clinical deterioration, unplanned ICU admission and death among ward patients following medical emergency team (MET) review. DESIGN: A retrospective cohort study of 1500 patients who remained on a general ward following MET review at an Australian quaternary hospital. METHOD: Logistic regression was used to model (1) subsequent MET review within 48 h, (2) unplanned ICU admission within 48 h and (3) hospital mortality. Models included demographic, clinical and illness severity variables. Model performance was evaluated using discrimination and calibration with optimism-corrected bootstrapped estimates. Findings are reported using the TRIPOD guideline for multivariable prediction models for prognosis or diagnosis. There was no patient or public involvement in the development and conduct of this study. RESULTS: Within 48 h of index MET review, 8.3% (n = 125) of patients had a subsequent MET review, 7.2% (n = 108) had an unplanned ICU admission and in-hospital mortality was 16% (n = 240). From clinically preselected predictors, models retained age, sex, comorbidity, resuscitation limitation, acuity-dependency profile, MET activation triggers and whether the patient was within 24 h of hospital admission, ICU discharge or surgery. Models for subsequent MET review, unplanned ICU admission, and death had adequate accuracy in development and bootstrapped validation samples. CONCLUSION: Patients requiring MET review demonstrate complex clinical characteristics and the majority remain on the ward after review for deterioration. A risk score could be used to identify patients at risk of poor outcomes after MET review and support general ward clinical decision-making. RELEVANCE TO CLINICAL PRACTICE: Our risk calculator estimates risk for patient outcomes following MET review using clinical data available at the bedside. Future validation and implementation could support evidence-informed team communication and patient placement decisions.

A systematic review of the facilitators and barriers to rapid response team activation.

BACKGROUND: Outcomes associated with rapid response teams (RRTs) are inconsistent. This may be due to underlying facilitators and barriers to RRT activation that are affected by team leaders and health systems. AIMS: The aim of this study was to synthesize the published research about facilitators and barriers to nurse-led RRT activation in the United States (U.S.). METHODS: A systematic review was conducted. Four databases were searched from January 2000 to June 2023 for peer-reviewed quantitative, qualitative, and mixed methods studies reporting facilitators and barriers to RRT activation. Studies conducted outside the U.S. or with physician-led teams were excluded. RESULTS: Twenty-five studies met criteria representing 240,140 participants that included clinicians and hospitalized adults. Three domains of facilitators and barriers to RRT activation were identified: (1) hospital infrastructure, (2) clinician culture, and (3) nurses' beliefs, attributes, and knowledge. Categories were identified within each domain. The categories of perceived benefits and positive beliefs about RRTs, knowing when to activate the RRT, and hospital-wide policies and practices most facilitated activation, whereas the categories of negative perceptions and concerns about RRTs and uncertainties surrounding RRT activation were the dominant barriers. LINKING EVIDENCE TO ACTION: Facilitators and barriers to RRT activation were interrelated. Some facilitators like hospital leader and physician support of RRTs became barriers when absent. Intradisciplinary communication and collaboration between nurses can positively and negatively impact RRT activation. The expertise of RRT nurses should be further studied.

Assessment of Hospital Medical Emergency Team Operations in a Tertiary Care Center in Turkey.

BACKGROUND: Rapid Response Teams, strategically devised to mitigate mortality and morbidity stemming from unforeseen deteriorations and cardiac arrests within healthcare facilities, are ubiquitously implemented on a global scale. AIM: The aim of the study is to compare emergency physicians (EPs) and non-EPs on management protocols of Hospital Medical Emergency Teams (HoMET). METHODS: This was a retrospective cross-sectional study. The hospital archive underwent a retrospective scanning process, and patient records were meticulously examined. The assessment encompassed various facets, including demographic characteristics, activation locations, and response and intervention times of HoMET teams, composed of both EPs and other healthcare professionals. Data analysis was conducted using SPSS software version 20.0. RESULTS: A total of 1056 calls were included, with 52% (n = 549) involving male patients. The average age was 67.15 ± 19.45 years. EPs served as the team leader in 53% of the calls. Cardiac arrest was considered in 93.6% of the cases. The EPs group exhibited a higher average patient age, longer intervention times, and shorter arrival times (P < 0.001, P = 0.027, P < 0.001, respectively). A significant difference was observed in the locations of the calls and the groups of calls considering cardiac arrest (P < 0.001, P < 0.001, respectively). CONCLUSION: The optimization of intervention teams is imperative given the persistently high incidence and mortality rates associated with in-hospital cardiac arrests. Leveraging the expertise of EPs in the management of arrests and critical patients can potentially enhance the effectiveness of these teams. Nonetheless, further research is warranted to comprehensively explore and validate this aspect.

Implementation and Outcomes of a Difficult Airway Code Team Composed of Anesthesiologists in a Korean Tertiary Hospital: A Retrospective Analysis of a Prospective Registry.

BACKGROUND: In 2017, we established an airway call (AC) team composed of anesthesiologists to improve emergency airway management outside the operating room. In this retrospective analysis of prospectively collected data from the airway registry, we describe the characteristics of patients attended to and practices by the AC team during the first 4 years of implementation. METHODS: All AC team activations in which an airway intervention was performed by the AC team between June 2017 and May 2021 were analyzed. RESULTS: In all, 359 events were analyzed. Activation was more common outside of working hours (62.1%) and from the intensive care unit (85.0%); 36.2% of AC activations were due to known or anticipated difficult airway, most commonly because of acquired airway anomalies (n = 49), followed by airway edema or bleeding (n = 32) and very young age (≤ 1 years; n = 30). In 71.3% of the cases, successful intubation was performed by the AC team at the first attempt. However, three or more attempts were performed in 33 cases. The most common device used for successful intubation was the videolaryngoscope (59.7%). Tracheal intubation by the AC team failed in nine patients, who then required surgical airway insertion by otolaryngologists. However, there were no airway-related deaths. CONCLUSIONS: When coupled with appropriate assistance from an otolaryngologist AC system, an AC team composed of anesthesiologists could be an efficient way to provide safe airway management outside the operating room. TRIAL REGISTRATION: Clinical Research Information Service Identifier: KCT0006643.

Introduction of a standardised maternity early warning system: indicative data from a before-and-after study at a large pilot site before national rollout in Aotearoa New Zealand.

Strong evidence now demonstrates that recognition and response systems using standardised early warning scores can help prevent harm associated with in-hospital clinical deterioration in non-pregnant adult patients. However, a standardised maternity-specific early warning system has not yet been agreed in the UK. In Aotearoa New Zealand, following the nationwide implementation of the standardised New Zealand Early Warning Score (NZEWS) for adult inpatients, a modified maternity-specific variation (NZMEWS) was piloted in a major tertiary hospital in Auckland, before national rollout. Following implementation in July 2018, we observed a significant and sustained reduction in severe maternal morbidity as measured by emergency response calls to women who were very unwell (emergency response team call), and a non-significant reduction in cardiorespiratory arrest team calls. Emergency response team calls to maternity wards fell from a median of 0.8 per 100 births at baseline (January 2017-May 2018) to 0.6 per 100 births monthly (from March 2019 to December 2020) (p < 0.0001). Cardiorespiratory arrest team calls to maternity wards fell from 0.14 per 100 births per quarter (quarter 1 2017-quarter 2 2018) to 0.09 calls per 100 births per quarter after NZMEWS was introduced (quarter 3 2018-quarter 4 2020) (p = 0.2593). These early results provide evidence that NZMEWS can detect and prevent deterioration of pregnant women, although there are multiple factors that may have contributed to the reduction in emergency response calls noted.

Characteristics and Prognosis of Hospitalized Patients at High Risk of Deterioration Identified by the Rapid Response System: a Multicenter Cohort Study.

We aimed to investigate the characteristics and prognosis of high risk hospitalized patients identified by the rapid response system (RRS). A multicentered retrospective cohort study was conducted from June 2019 to December 2020. The National Early Warning Score (NEWS) was used for RRS activation. The outcome was unexpected intensive care unit (ICU) admission within 24 hours after RRS activation. The 11,459 patients with RRS activations were included. We found distinct clinical characteristics in patients who underwent ICU admission. All NEWS parameters were associated with the risk of unexpected ICU admission except body temperature. Body mass index, pulmonary disease, and cancer are related to the decreased risk of unexpected ICU admission. In conclusion, there were differences in clinical characteristics among high risk patients, and those differences were associated with unexpected ICU admissions. Clinicians should consider factors relating to unexpected ICU admission in the management of high risk patients identified by RRS.

Risk Factors for Early Medical Emergency Team Reactivation in Hospitalized Patients.

OBJECTIVES: The objective of this study was to investigate the risk factors for early medical emergency team reactivation (which is defined as repeated medical emergency team calls within 72 hr after the index medical emergency team call) in the patients remaining on the ward after index medical emergency team activation. DESIGN: Retrospective analysis with prospectively collected data. SETTING: A university-affiliated, tertiary referral hospital. PATIENTS: All consecutive patients over 18 years old who received medical emergency team intervention. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of the 3,989 cases eligible for analysis, 514 cases (12.9%) were classified into the reactivation group, with the remainder assigned to the nonreactivation group. In a multivariate analysis, chronic lung disease (odds ratio, 1.38; 95% CI, 1.03-1.86; p = 0.032), chronic liver disease (odds ratio, 1.44; 95% CI, 1.04-1.99; p = 0.028), activation due to bedside concern about overall deterioration without abnormal physiological variables (odds ratio, 1.30; 95% CI, 1.00-1.68; p = 0.049), advice or consultation only for medical emergency team intervention (odds ratio, 0.78; 95% CI, 0.63-0.97; p = 0.027), and discussion about treatment limitation (odds ratio, 0.39; 95% CI, 0.25-0.60; p < 0.001) were independently associated with medical emergency team reactivation. In the reactivation group, 249 patients (48.5%) were transferred to the ICU after repeated calls. Medical department admission (odds ratio, 1.68; 95% CI, 1.12-2.52; p = 0.012), chronic liver disease (odds ratio, 1.73; 95% CI, 1.07-2.79; p = 0.025), hematological malignancies (odds ratio, 1.63; 95% CI, 1.10-2.41; p = 0.015), and tachypnea at the end of medical emergency team were risk factors for medical emergency team reactivation requiring ICU admission. Discussion about treatment limitation (odds ratio, 0.14; 95% CI, 0.05-0.40; p < 0.001) was also associated with decreased risk of medical emergency team reactivation requiring ICU admission. CONCLUSIONS: An increased risk of early medical emergency team reactivation was associated with medical emergency team activation by bedside concern about overall deterioration and patients with chronic lung or liver disease.

Performance of a Clinical Decision Support Tool to Identify PICU Patients at High Risk for Clinical Deterioration.

OBJECTIVES: To evaluate the translation of a paper high-risk checklist for PICU patients at risk of clinical deterioration to an automated clinical decision support tool. DESIGN: Retrospective, observational cohort study of an automated clinical decision support tool, the PICU Warning Tool, adapted from a paper checklist to predict clinical deterioration events in PICU patients within 24 hours. SETTING: Two quaternary care medical-surgical PICUs-The Children's Hospital of Philadelphia and Cincinnati Children's Hospital Medical Center. PATIENTS: The study included all patients admitted from July 1, 2014, to June 30, 2015, the year prior to the initiation of any focused situational awareness work at either institution. INTERVENTIONS: We replicated the predictions of the real-time PICU Warning Tool by retrospectively querying the institutional data warehouse to identify all patients that would have flagged as high-risk by the PICU Warning Tool for their index deterioration. MEASUREMENTS AND MAIN RESULTS: The primary exposure of interest was determination of high-risk status during PICU admission via the PICU Warning Tool. The primary outcome of interest was clinical deterioration event within 24 hours of a positive screen. The date and time of the deterioration event was used as the index time point. We evaluated the sensitivity, specificity, positive predictive value, and negative predictive value of the performance of the PICU Warning Tool. There were 6,233 patients evaluated with 233 clinical deterioration events experienced by 154 individual patients. The positive predictive value of the PICU Warning Tool was 7.1% with a number needed to screen of 14 patients for each index clinical deterioration event. The most predictive of the individual criteria were elevated lactic acidosis, high mean airway pressure, and profound acidosis. CONCLUSIONS: Performance of a clinical decision support translation of a paper-based tool showed inferior test characteristics. Improved feasibility of identification of high-risk patients using automated tools must be balanced with performance.

Characteristics and outcomes of rapid response team activations for hypotension in orthopaedic patients.

BACKGROUND: Hypotension following orthopaedic surgery has been associated with increased morbidity and mortality. Rapid response teams (RRT) review patients on hospital wards with hypotension. AIM: To evaluate the epidemiology of hypotensive RRT activations in adult orthopaedic patients to identify contributing factors and areas for future quality improvement. METHODS: Timing of RRT activations, presumed causes of hypotension and associated treatments were assessed. RESULTS: Among 963 RRT activations in 605 patients over 3 years, the first calls of 226 of 605 patients were due to hypotension, and 213 (94.2%) of 226 had sufficient data for analysis. The median age was 79 (interquartile range 66-87) years; 58 (27.2%) were male, and comorbidities were common. Most (68%) surgery was emergent, and 75.1% received intraoperative vasopressors for hypotension. Most activations occurred within 24 h of surgery, and hypovolaemia, infection and arrhythmias were common presumed causes. Fluid boluses occurred in 173 (81.2%), and the time between surgery and RRT activation was 10 (4.0-26.5) h. in cases where fluid boluses were given, compared with 33 (15.5-61.5) h. where they were not (P < 0.001). Blood transfusion (30, 14.1%) and withholding of medications were also common. Hospital mortality was 8.5% (18), and 13.6% (29) were admitted to critical care at some stage. In-hospital death was associated with older age, functional dependence, arrhythmia and presumed infection. CONCLUSIONS: Hypotension-related RRT calls in orthopaedic patients are common. Future interventional studies might focus on perioperative fluid therapy and vaso-active medications, as well as withholding of anti-hypertensive medications preoperatively.

Impact of increased calls to rapid response systems on unplanned ICU admission.

BACKGROUND: Whether hospital bed number and rapid response system (RRS) call rate is associated with the clinical outcomes of patients who have RRS activations is unknown. We test a hypothesis that hospital volume and RRS call rates are associated with the clinical outcomes of patients with RRSs. METHODS: This is a retrospective chart analysis of an existing dataset associated with In-Hospital Emergency Registry in Japan. In the present study, 4818 patients in 24 hospitals from April 2014 to March 2018 were analyzed. Primary outcome variable was an unplanned intensive care unit (ICU) admission after RRS activation. RESULTS: In the primary analysis of the study using a multivariate analysis adjusting potential confounding factors, higher RRS call rate was significantly associated with decreased unplanned ICU admissions (P < 0.0001, Odds ratio [OR] 0.95, 95% confidence interval [CI] 0.92-0.98), but there was no significant association of hospital volume with unplanned ICU admissions (P = 0.44). In the secondary analysis of the study, there was a non-significant trend of increased cardiac arrest on arrival at the location of the RRS provider at large-volume hospitals (P = 0.084, OR 1.16, 95% CI 0.98-1.38). Large-volume hospitals had a significantly higher 1-month mortality rate (P = 0.0040, OR 1.10, 95% CI 1.03-1.18). CONCLUSION: Hospitals with increased RRS call rates had significantly decreased unplanned ICU admission in patients who had RRS activations. Patients who had RRS activations at large-volume hospitals had an increased 1-month mortality rate.

The prevalence and characteristics of rapid response systems in hospitals with pediatric intensive care units in Japan and barriers to their use.

OBJECTIVE: The use of pediatric rapid response systems (RRSs) to improve the safety of hospitalized children has spread in various western countries including the United States and the United Kingdom. We aimed to determine the prevalence and characteristics of pediatric RRSs and barriers to use in Japan, where epidemiological information is limited. DESIGN: A cross-sectional online survey. SETTING: All 34 hospitals in Japan with pediatric intensive care units (PICUs) in 2019. PARTICIPANTS: One PICU physician per hospital responded to the questionnaire as a delegate. MAIN OUTCOME MEASURES: Prevalence of pediatric RRSs in Japan and barriers to their use. RESULTS: The survey response rate was 100%. Pediatric RRSs had been introduced in 14 (41.2%) institutions, and response teams comprised a median of 6 core members. Most response teams employed no full-time members and largely comprised members from multiple disciplines and departments who served in addition to their main duties. Of 20 institutions without pediatric RRSs, 11 (55%) hoped to introduce them, 14 (70%) had insufficient knowledge concerning them and 11 (55%) considered that their introduction might be difficult. The main barrier to adopting RRSs was a perceived personnel and/or funding shortage. There was no significant difference in hospital beds (mean, 472 vs. 524, P = 0.86) and PICU beds (mean, 10 vs. 8, P = 0.34) between institutions with/without pediatric RRSs. CONCLUSIONS: Fewer than half of Japanese institutions with PICUs had pediatric RRSs. Operating methods for and obstructions to RRSs were diverse. Our findings may help to popularize pediatric RRSs.

Predictors of mortality and cost among surgical patients requiring rapid response team activation.

Background: Prior studies of rapid response team (RRT) implementation for surgical patients have demonstrated mixed results with respect to reductions in poor outcomes. The aim of this study was to identify predictors of in-hospital mortality and hospital costs among surgical inpatients requiring RRT activation. Methods: We analyzed data prospectively collected from May 2012 to May 2016 at The Ottawa Hospital. We included patients who were at least 18 years of age, who were admitted to hospital, who received either preoperative or postoperative care, and and who required RRT activation. We created a multivariable logistic regression model to describe mortality predictors and a multivariable generalized linear model to describe cost predictors. Results: We included 1507 patients. The in-hospital mortality rate was 15.9%. The patient-related factors most strongly associated with mortality included an Elixhauser Comorbidity Index score of 20 or higher (odds ratio [OR] 3.60, 95% confidence interval [CI] 1.96-6.60) and care designations excluding admission to the intensive care unit and cardiopulmonary resuscitation (OR 3.52, 95% CI 2.25-5.52). The strongest surgical predictors included neurosurgical admission (OR 2.09, 95% CI 1.17-3.75), emergent surgery (OR 2.04, 95% CI 1.37-3.03) and occurrence of 2 or more operations (OR 1.73, 95% CI 1.21-2.46). Among RRT factors, occurrence of 2 or more RRT assessments (OR 2.01, 95% CI 1.44-2.80) conferred the highest mortality. Increased cost was strongly associated with admitting service, multiple surgeries, multiple RRT assessments and medical comorbidity. Conclusion: RRT activation among surgical inpatients identifies a population at high risk of death. We identified several predictors of mortality and cost, which represent opportunities for future quality improvement and patient safety initiatives.

Contexte: Les études sur la mobilisation d'équipes d'intervention rapide (EIR) auprès de patients en chirurgie ont donné des résultats mitigés quant à la réduction des issues négatives. La présente étude visait à déterminer les facteurs prédictifs de coûts pour les hôpitaux et de mortalité chez les patients en chirurgie nécessitant la mobilisation d'une EIR. Méthodes: Nous avons analysé des données recueillies de manière prospective de mai 2012 à mai 2016 à l'Hôpital d'Ottawa. Nous avons inclus les patients hospitalisés de 18 ans et plus qui ont reçu des soins préopératoires ou postopératoires et qui ont nécessité l'intervention d'une EIR. Nous avons ensuite créé un modèle de régression logistique multivariée pour décrire les facteurs prédictifs de mortalité et un modèle linéaire généralisé multivarié pour décrire les facteurs prédictifs de coûts. Résultats: Nous avons retenus 1507 patients. Le taux global de mortalité à l'hôpital était de 15,9 %. Les principaux facteurs de mortalité liés au patient étaient un indice de comorbidité d'Elixhauser supérieur ou égal à 20 (rapport de cotes [RC] 3,60, intervalle de confiance [IC] à 95 % 1,96­6,60) et des objectifs de soins excluant l'admission à l'unité des soins intensifs et la réanimation cardiorespiratoire (RC 3,52, IC à 95 % 2,25­5,52). Les principaux facteurs prédictifs liés aux interventions sont l'admission en neurochirurgie (RC 2,09, IC à 95 % 1,17­3,75), l'intervention chirurgicale d'urgence (RC 2,04, IC à 95 % 1,37­3,03) et le fait d'avoir subi au moins 2 opérations (RC 1,73, IC à 95 % 1,21­2,46). Parmi les facteurs liés aux EIR, la tenue d'au moins 2 évaluations par l'EIR s'accompagnait du mortalité le plus élevé (RC 2,01, IC à 95 % 1,44­2,80). L'augmentation des coûts était étroitement associée au service d'admission, aux interventions chirurgicales multiples, aux évaluations multiples par l'EIR et à la comorbidité médicale. Conclusion: La mobilisation d'EIR auprès de patients en chirurgie permet de mettre en évidence une population à risque élevé de décès. Nous avons découvert plusieurs facteurs prédictifs de mortalité et de coûts, dont on pourra se servir pour améliorer la qualité des soins et la sécurité des patients.

Rapid Response Team Activations in an Israeli Tertiary Care Pediatric Hospital: Analysis of 614 Events.

BACKGROUND: Rapid response teams (RRT) reduce in-hospital mortality and cardiac arrests. There are only a few articles describing RRT activations outside of North America and Australia. OBJECTIVES: To describe demographic and clinical variables of RRT activations using 13 years of data. METHODS: Schneider Children's Medical Center of Israel is a pediatric hospital with the busiest pediatric emergency department in the country. We analyzed demographic and clinical data of RRT activation from 1 January 2008 to 31 December 2018. RESULTS: During the study period there were 614 RRT activations with an average of 55.8 activations per year (range 43-76). RRT activations occurred most commonly for children aged 0-12 months (43%) as compared to children 1-5 years of age (25%), 6-10 years of age (12%), 11-18 years of age (18%), and adults (2%). The most common reason for activation was respiratory deterioration (45.8%) followed by neurologic alteration (21%), and cardiac arrest (18%). Following resuscitation, 47% of the patients were admitted to the pediatric intensive care unit and 12% were pronounced dead. Intubation was performed in 48.9% of activations, chest compressions in 20.5%, intraosseous line insertion in 9.4%, and defibrillation in 3.4%. Procedures were usually performed in the emergency department (ED). CONCLUSIONS: We describe RRT including RRT activations in the ED. The high frequency of interventions should be utilized to direct staff training for the RRT and the ED. The lack of standardization of reporting data for RRT activations makes comparisons among hospitals difficult.

Characteristics of Rapid Response Calls in the United States: An Analysis of the First 402,023 Adult Cases From the Get With the Guidelines Resuscitation-Medical Emergency Team Registry.

OBJECTIVES: To characterize the rapid response team activations, and the patients receiving them, in the American Heart Association-sponsored Get With The Guidelines Resuscitation-Medical Emergency Team cohort between 2005 and 2015. DESIGN: Retrospective multicenter cohort study. SETTING: Three hundred sixty U.S. hospitals. PATIENTS: Consecutive adult patients experiencing rapid response team activation. INTERVENTIONS: Rapid response team activation. MEASUREMENTS AND MAIN RESULTS: The cohort included 402,023 rapid response team activations from 347,401 unique healthcare encounters. Respiratory triggers (38.0%) and cardiac triggers (37.4%) were most common. The most frequent interventions-pulse oximetry (66.5%), other monitoring (59.6%), and supplemental oxygen (62.0%)-were noninvasive. Fluids were the most common medication ordered (19.3%), but new antibiotic orders were rare (1.2%). More than 10% of rapid response teams resulted in code status changes. Hospital mortality was over 14% and increased with subsequent rapid response activations. CONCLUSIONS: Although patients requiring rapid response team activation have high inpatient mortality, most rapid response team activations involve relatively few interventions, which may limit these teams' ability to improve patient outcomes.

Prevalence, Risk Factors, and Clinical Consequences of Recurrent Activation of a Rapid Response Team: A Multicenter Observational Study.

INTRODUCTION: Rapid response teams (RRTs) are groups of health-care providers, implemented by hospitals to respond to distressed hospitalized patients on the hospital wards. Patients assessed by the RRT for deterioration may be admitted to the intensive care unit (ICU) or may be triaged to remain on the wards, putting them at risk of recurrent deterioration and repeat RRT activation. Previous studies evaluating outcomes of patients with recurrent deterioration and multiple RRT activations have produced conflicting results. METHODS: We used a prospectively collected multicenter registry from 2 hospitals within a single tertiary-level hospital system between 2012 and 2016. Comparisons were made between patients with a single RRT activation and those with multiple RRT activations over the course of their admission. Primary outcome was in-hospital mortality, which was analyzed using multivariable logistic regression. RESULTS: A total of 5995 patients who had any RRT activation were analyzed. Of that, 1183 (19.7%) patients had recurrent deterioration and multiple RRT activations during their admission. Risk factors for recurrent deterioration included admission from a home setting (as opposed to a long-term care facility), RRT activation during nighttime hours, and delay (>1 hour) to RRT activation. Recurrent deterioration was associated with increased odds of mortality (adjusted odds ratio [OR]: 1.44 [1.28-1.64], P = <.001). Increasing number of RRT activations were associated with increasing risk of mortality. Patients with recurrent deterioration had prolonged median hospital length of stay (21.0 days vs 12.0 days, P < .001), while patients with only a single activation were more likely to be admitted to the ICU (adjusted OR: 2.30 [1.96-2.70], P < .001). CONCLUSIONS: Recurrent deteriorations leading to RRT activations among hospitalized patients are associated with increased odds of mortality and prolonged hospital length of stay. This work identifies a group of patients who warrant closer attention to help reduce adverse outcomes.

Segmented Regression and Difference-in-Difference Methods: Assessing the Impact of Systemic Changes in Health Care.

Perioperative investigators and professionals increasingly seek to evaluate whether implementing systematic practice changes improves outcomes compared to a previous routine. Cluster randomized trials are the optimal design to assess a systematic practice change but are often impractical; investigators, therefore, often select a before-after design. In this Statistical Grand Rounds, we first discuss biases inherent in a before-after design, including confounding due to periods being completely separated by time, regression to the mean, the Hawthorne effect, and others. Many of these biases can be at least partially addressed by using appropriate designs and analyses, which we discuss. Our focus is on segmented regression of an interrupted time series, which does not require a concurrent control group; we also present alternative designs including difference-in-difference, stepped wedge, and cluster randomization. Conducting segmented regression well requires a sufficient number of time points within each period, along with a robust set of potentially confounding variables. This method compares preintervention and postintervention changes over time, divergences in the outcome when an intervention begins, and trends observed with the intervention compared to trends projected without it. Difference-in-difference methods add a concurrent control, enabling yet stronger inference. When done well, the discussed methods permit robust inference on the effect of an intervention, albeit still requiring assumptions and having limitations. Methods are demonstrated using an interrupted time series study in which anesthesiologists took responsibility for an adult medical emergency team from internal medicine physicians in an attempt to improve outcomes.

Efficacy and Safety of Pediatric Critical Care Physician Telemedicine Involvement in Rapid Response Team and Code Response in a Satellite Facility.

OBJECTIVES: Satellite inpatient facilities of larger children's hospitals often do not have on-site intensivist support. In-house rapid response teams and code teams may be difficult to operationalize in such facilities. We developed a system using telemedicine to provide pediatric intensivist involvement in rapid response team and code teams at the satellite facility of our children's hospital. Herein, we compare this model with our in-person model at our main campus. DESIGN: Cross-sectional. SETTING: A tertiary pediatric center and its satellite facility. PATIENTS: Patients admitted to the satellite facility. INTERVENTIONS: Implementation of a rapid response team and code team model at a satellite facility using telemedicine to provide intensivist support. MEASUREMENTS AND MAIN RESULTS: We evaluated the success of the telemedicine model through three a priori outcomes: 1) reliability: involvement of intensivist on telemedicine rapid response teams and codes, 2) efficiency: time from rapid response team and code call until intensivist response, and 3) outcomes: disposition of telemedicine rapid response team or code calls. We compared each metric from our telemedicine model with our established main campus model. MAIN RESULTS: Critical care was involved in satellite campus rapid response team activations reliably (94.6% of the time). The process was efficient (median response time 7 min; mean 8.44 min) and effective (54.5 % patients transferred to PICU, similar to the 45-55% monthly rate at main campus). For code activations, the critical care telemedicine response rate was 100% (6/6), with a fast response time (median 1.5 min). We found no additional risk to patients, with no patients transferred from the satellite campus requiring a rapid escalation of care defined as initiation of vasoactive support, greater than 60 mL/kg in fluid resuscitation, or endotracheal intubation. CONCLUSIONS: Telemedicine can provide reliable, timely, and effective critical care involvement in rapid response team and Code Teams at satellite facilities.

National Early Warning Score vs Rapid Response Team criteria-Prevalence, misclassification, and outcome.

PURPOSE: The purpose of this study was to examine the prevalence of deviating vital parameters in general ward patients using rapid response team (RRT) criteria and National Early Warning Score (NEWS), assess exam duration, correct calculation and classification of risk score as well as mortality and adverse events. METHODS: Point prevalence study of vital parameters according to NEWS and RRT criteria of all adult patients admitted to general wards at a Scandinavian university hospital with a mature RRT. PRIMARY OUTCOME: prevalence of at-risk patients fulfilling at least one RRT criteria, total NEWS of 7 or greater or a single NEWS parameter of 3 (red NEWS). SECONDARY OUTCOMES: mortality in-hospital and within 30 days or adverse events within 24 hours. RESULTS: We assessed 598 (75%) of 798 admitted patients and examiners captured a fulfilled RRT calling criterion in 50 patients (8.4%), 36 (6.0%) had NEWS ≥ 7, 34 with a red NEWS parameter. Red NEWS occurred in 112 patients (18.7%). Secondary outcomes were fulfilled in 49 patients (8.2%). Mortality overall was 6.5% within 30 days, 1.8% in hospital. In 134 patients (22.4%) the manual calculation of score for NEWS was incorrectly performed by examiner. CONCLUSION: Even with a mature RRT in place, we captured patients with failing physiology in general wards reflecting afferent limb failure. Manual calculation of NEWS is frequently incorrect, possibly leading to misclassification of patients at risk.