Deployment Of Rapid Response Team Research Articles

Reduction of in-hospital cardiac arrest with sequential deployment of rapid response team and medical emergency team to the emergency department and acute care wards.

PurposeThis study aimed to determine if sequential deployment of a nurse-led Rapid Response Team (RRT) and an intensivist-led Medical Emergency Team (MET) for critically ill patients in the Emergency Department (ED) and acute care wards improved hospital-wide cardiac arrest rates.MethodsIn this single-center, retrospective observational cohort study, we compared the cardiac arrest rates per 1000 patient-days during two time periods. Our hospital instituted a nurse-led RRT in 2012 and added an intensivist-led MET in 2014. We compared the cardiac arrest rates during the nurse-led RRT period and the combined RRT-MET period. With the sequential approach, nurse-led RRT evaluated and managed rapid response calls in acute care wards and if required escalated care and co-managed with an intensivist-led MET. We specifically compared the rates of pulseless electrical activity (PEA) in the two periods. We also looked at the cardiac arrest rates in the ED as RRT-MET co-managed patients with the ED team.ResultsHospital-wide cardiac arrests decreased from 2.2 events per 1000 patient-days in the nurse-led RRT period to 0.8 events per 1000 patient-days in the combined RRT and MET period (p-value = 0.001). Hospital-wide PEA arrests and shockable rhythms both decreased significantly. PEA rhythms significantly decreased in acute care wards and the ED.ConclusionImplementing an intensivist-led MET-RRT significantly decreased the overall cardiac arrest rate relative to the rate under a nurse-led RRT model. Additional MET capabilities and early initiation of advanced, time-sensitive therapies likely had the most impact.

Analyses of the performance of the Ebola virus disease alert management system in South Sudan: August 2018 to November 2019.

South Sudan implemented Ebola virus disease preparedness interventions aiming at preventing and rapidly containing any importation of the virus from the Democratic Republic of Congo starting from August 2018. One of these interventions was a surveillance system which included an Ebola alert management system. This study analyzed the performance of this system. A descriptive cross-sectional study of the Ebola virus disease alerts which were reported in South Sudan from August 2018 to November 2019 was conducted using both quantitative and qualitative methods. As of 30 November 2019, a total of 107 alerts had been detected in the country out of which 51 (47.7%) met the case definition and were investigated with blood samples collected for laboratory confirmation. Most (81%) of the investigated alerts were South Sudanese nationals. The alerts were identified by health workers (53.1%) at health facilities, at the community (20.4%) and by screeners at the points of entry (12.2%). Most of the investigated alerts were detected from the high-risk states of Gbudwe (46.9%), Jubek (16.3%) and Torit (10.2%). The investigated alerts commonly presented with fever, bleeding, headache and vomiting. The median timeliness for deployment of Rapid Response Team was less than one day and significantly different between the 6-month time periods (K-W = 7.7567; df = 2; p = 0.0024) from 2018 to 2019. Strengths of the alert management system included existence of a dedicated national alert hotline, case definition for alerts and rapid response teams while the weaknesses were occasional inability to access the alert toll-free hotline and lack of transport for deployment of the rapid response teams which often constrain quick response. This study demonstrates that the Ebola virus disease alert management system in South Sudan was fully functional despite the associated challenges and provides evidence to further improve Ebola preparedness in the country.

No more pediatric code blues on the floor: evolution of pediatric rapid response teams and situational awareness plans.

Reducing or eliminating code blues that occur on the inpatient, noncritical care units of children's hospitals is a challenging yet achievable goal. The mechanism to accomplish this involves several levels of effort. The implementation of effective pediatric rapid response teams is a well identified part of the process. Rapid response teams can allow for appropriate clinical interventions for deteriorating patients and may ultimately result in a reduction in hospital-wide mortality as well as efficient transfer to the pediatric intensive care unit (PICU) when necessary. The timely deployment of rapid response teams is dependent upon the appropriate recognition of patients at risk for deterioration. This recognition can be optimized by relying on assessments as simple as utilization of parental intuition to those as complex as big data models which utilize multiple predictor variables extracted from the electronic medical record. Ultimately, the goal to proactively identify patients at risk of deterioration may allow for prevention of clinical decline via appropriate and timely interventions, and if unsuccessful at that level, may allow for improved outcomes via optimized resuscitation care in the PICU.

The role of a national-emergency operations center in 2016/2017 meningitis outbreak response

Introduction : outbreaks of bacterial Cerebrospinal Meningitis are known to result in high morbidity and mortality. Outbreaks with such a high impact attract a multi-level, multi-partner response. While the accompanying deployment of human and material resources is beneficial for response, effective utilization may be compromised without a central coordinating structure. Activating an Incident Management System (IMS) is therefore vital. This paper describes the role of an IMS in coordinating response to the 2017 CSM outbreak, which resulted in 14,280 cases with CFR of 8%. Methods : on the 3rd of April, 2017, a national IMS led by the Nigeria Centre for Disease Control (NCDC) was activated coinciding with the peak of the outbreak (Epi-week 14, 2017). Terms of Reference and an emergency response plan was defined based on five response pillars- Coordination, Case management, Surveillance and Epidemiology, Risk Communications and Vaccines management. Activities implemented include: Bi-weekly CSM EOC meetings and situational report development, deployment of rapid response teams (RRT) to affected States, technical support to States to support reactive vaccination campaigns. Other activities included sensitization of stakeholders, monitoring of epidemiological trends using dashboards, development and review of SOPs, weekly feedbacks to affected States as well as multi-layered advocacies. Results : the IMS activation enhanced coordination of all response activities by the Government and partners. A long tail of the epidemic prior to EOC activation was shortened and CFR reduced from 11.2% to 8.0%. Reactive vaccination campaigns were better coordinated yielding high coverage rates in Zamfara (97%), Sokoto (97%) and Yobe (105%) States. Multi-level mapping and strategic deployment of all partners’ resources was achieved. Development and dissemination of bi-weekly situational reports aided response decisions and kept stakeholders and the general public abreast of outbreak status. Decision making was evidence-based as outbreak dashboards were used to review epidemic trends. Engagement with stakeholders (media, traditional and religious institutions) helped in social mobilization. Guidelines and SOPs development improved sub-national response by eliminating the use of multiple guidelines on same thematic area. Conclusion : the containment of CSM outbreak is partly attributable to the activation of the IMS, which aided timely identification of response gaps and proffering solutions. Although the IMS was activated only at the peak of the outbreak, a drastic reduction in new cases was recorded. The use of an IMS for coordinating future outbreaks is highly recommended.

Deployment of Rapid Response Teams by 31 Hospitals in a Statewide Collaborative

Deployment of Rapid Response Teams by 31 Hospitals in a Statewide Collaborative