Development of a novel rapid response event review process for quality improvement.

INTRODUCTION: Rapid response team (RRT) and code activation events occur relatively commonly in inpatient settings. RRT systems have been the subject of a significant amount of analysis, although this has been largely focused on the impact of RRT system implementation and RRT events on patient outcomes. There is reason to believe that the structured assessment of RRT and code events may be an effective way to identify opportunities for system improvement, although no standardised approach to event analysis is widely accepted. We developed and refined a protocolised system of RRT and code event review, focused on sustainable, timely and high value event analysis meant to inform ongoing improvement activities. METHODS: A group of clinicians with expertise in process and quality improvement created a protocolised analytic plan for rapid response event review, piloted and then iteratively optimised a systematic process which was applied to all subsequent cases to be reviewed. RESULTS: Hospitalist reviewers were recruited and trained in a methodical approach. Each reviewer performed a chart review to summarise RRT events, and collect specific variables for each case (coding). Coding was then reviewed for concordance, at monthly interdisciplinary group meetings and 'Action Items' were identified and considered for implementation. In any 12-month period starting in 2021, approximately 12-15 distinct cases per month were reviewed and coded, offering ample opportunities to identify trends and patterns. CONCLUSION: We have developed an innovative process for ongoing review of RRT-Code events. The review process is easy to implement and has allowed for the timely identification of high value improvement opportunities.

Prevalence and characteristics of medical emergency teams in Switzerland: a nationwide survey of intensive care units.

BACKGROUND: Medical Emergency Teams (METs) have been implemented in many hospitals worldwide and are considered an integral part of the hospital patient safety system. However, data on prevalence, staffing and activation criteria of METs are scarce. Such data are important as they may help to identify areas of quality improvement and barriers to implementation of rapid response systems (RRS). This survey aimed to analyze current characteristics, prevalence, and organization of METs in Switzerland. METHODS: We conducted a cross-sectional nationwide online survey, inviting physicians' and nurses' representatives from all registered adult intensive care units (ICU) in Switzerland. RESULTS: Of the 74 hospitals invited to participate in the survey, 57 responded (response rate 77%). We obtained 82 individual responses (from 50 physicians and 32 nurses). Twenty-five hospitals (44%) have a MET in place. In most Swiss hospitals, METs are composed of ICU consultants (64%) and ICU nurses (40%) and are activated by phone, with a usual response time of less than 10 minutes. The most common triggers are single abnormal vital signs (80%), while multiple-parameter warning scores are less commonly used (28%). While more than half of the nurses have regular trainings for their MET members (57%), most MET physicians (63%) do not. Systematic data collection of MET calls occurs in only 43% of institutions. Finally, the most common reasons for not having a MET are staff shortage (44%) and lack of funding (19%). CONCLUSIONS: Less than 50% of Swiss hospitals with an adult ICU have a MET in place. METs in Switzerland typically include an ICU doctor and an ICU nurse and are available 24/7. Major barriers to MET introduction are staff shortage and lack of funding.

Risk Factors for Deterioration Events in the Pediatric Acute Care Setting.

OBJECTIVES: Rapid response system (RRS) activations resulting in emergency transfers (ETs) and codes outside the ICU are associated with increased mortality and length of stay. We aimed to evaluate the patient and care team characteristics of RRS activations resulting in ETs and codes outside the ICU (together classified as "deterioration events") versus those that did not result in a deterioration event. METHODS: For each RRS activation at our institution from 2019 to 2021, data were gathered on patient demographics and medical diagnoses, care team and treatment factors, and ICU transfer. Descriptive statistics, bivariate analyses, and multivariable logistic regression using a backward elimination model selection method were performed to assess potential risk factors for deterioration events. RESULTS: Over the 3-year period, 1765 RRS activations were identified. Fifty-three (3%) activations were deemed acute care codes, 64 (4%) were noncode ETs, 921 (52%) resulted in nonemergent transfers to an ICU, and 727 (41%) patients remained in an acute care unit. In a multivariable model, any complex chronic condition (adjusted odds ratio, 6.26; 95% confidence interval, 2.83-16.60) and hematology/oncology service (adjusted odds ratio, 2.19; 95% confidence interval, 1.28-3.74) were independent risk factors for a deterioration event. CONCLUSIONS: Patients with medical complexity and patients on the hematology/oncology service had a higher risk of deterioration events than other patients with RRS activations. Further analyzing how our hospital evaluates and treats these specific patient populations is critical as we develop targeted interventions to reduce deterioration events.

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.

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.

Trends of in-hospital cardiac arrests in a single tertiary hospital with a mature rapid response system.

BACKGROUND: Most studies on rapid response system (RRS) have simply focused on its role and effectiveness in reducing in-hospital cardiac arrests (IHCAs) or hospital mortality, regardless of the predictability of IHCA. This study aimed to identify the characteristics of IHCAs including predictability of the IHCAs as our RRS matures for 10 years, to determine the best measure for RRS evaluation. METHODS: Data on all consecutive adult patients who experienced IHCA and received cardiopulmonary resuscitation in general wards between January 2010 and December 2019 were reviewed. IHCAs were classified into three groups: preventable IHCA (P-IHCA), non-preventable IHCA (NP-IHCA), and inevitable IHCA (I-IHCA). The annual changes of three groups of IHCAs were analyzed with Poisson regression models. RESULTS: Of a total of 800 IHCA patients, 149 (18.6%) had P-IHCA, 465 (58.1%) had NP-IHCA, and 186 (23.2%) had I-IHCA. The number of the RRS activations increased significantly from 1,164 in 2010 to 1,560 in 2019 (P = 0.009), and in-hospital mortality rate was significantly decreased from 9.20/1,000 patients in 2010 to 7.23/1000 patients in 2019 (P = 0.009). The trend for the overall IHCA rate was stable, from 0.77/1,000 patients in 2010 to 1.06/1,000 patients in 2019 (P = 0.929). However, while the incidence of NP-IHCA (P = 0.927) and I-IHCA (P = 0.421) was relatively unchanged over time, the incidence of P-IHCA decreased from 0.19/1,000 patients in 2010 to 0.12/1,000 patients in 2019 (P = 0.025). CONCLUSIONS: The incidence of P-IHCA could be a quality metric to measure the clinical outcomes of RRS implementation and maturation than overall IHCAs.

Clinical impact of implementing a rapid-response team based on the Modified Early Warning Score in wards that offer emergency department support.

BACKGROUND: Emergency department (ED) crowding is a frequent situation. To decrease this overload, patients without a life-threating condition are transferred to wards that offer ED support. This study aimed to evaluate if implementing a rapid response team (RRT) triggered by the modified early warning score (MEWS) in high-risk wards offering ED support is associated with decreased in-hospital mortality rate. METHODS: A before-and-after cross-sectional study compared in-hospital mortality rates before and after implementation of an RRT triggered by the MEWS ≥4 in two wards of a tertiary hospital that offer ED support. RESULTS: We included 6863 patients hospitalized in these wards before RRT implementation from July 2015 through June 2017 and 6944 patients hospitalized in these same wards after RRT implementation from July 2018 through June 2020. We observed a statistically significant decrease in the in-hospital mortality rate after intervention, 449 deaths/6944 hospitalizations [6.47% (95% confidence interval (CI) 5.91%- 7.07%)] compared to 534 deaths/6863 hospitalizations [7.78% (95% CI 7.17-8.44)] before intervention; with an absolute risk reduction of -1.31% (95% CI -2.20 --0.50). CONCLUSION: RRT trigged by the MEWS≥4 in high-risk wards that offer ED support was found to be associated with a decreased in-hospital mortality rate. A further cluster-randomized trial should evaluate the impact of this intervention in this setting.

Management and Outcomes of Cardiogenic Shock in Cardiac ICUs With Versus Without Shock Teams.

BACKGROUND: Single-center studies suggest that implementation of multidisciplinary cardiogenic shock (CS) teams is associated with improved CS survival. OBJECTIVES: The aim was to characterize practice patterns and outcomes in the management of CS across multiple centers with versus without shock teams. METHODS: The Critical Care Cardiology Trials Network is a multicenter network of cardiac intensive care units (CICUs) in North America. All consecutive medical admissions to each CICU (n = 24) were captured during annual 2-month collection periods (2017-2019; n = 6,872). Shock management and CICU mortality among centers with versus without shock teams were compared using inverse probability weighting. RESULTS: Ten of the 24 centers had shock teams. Among 1,242 CS admissions, 44% were at shock team centers. The groups were well-balanced with respect to demographics, shock etiology, Sequential Organ Failure Assessment score, biochemical markers of end organ dysfunction, and invasive hemodynamics. Centers with shock teams used more pulmonary artery catheters (60% vs 49%; adjusted odds ratio [OR]: 1.86; 95% CI: 1.47-2.35; P < 0.001), less overall mechanical circulatory support (MCS) (35% vs 43%; adjusted OR: 0.74; 95% CI: 0.59-0.95; P = 0.016), and more advanced types of MCS (53% vs 43% of all MCS; adjusted OR: 1.73; 95% CI: 1.19-2.51; P = 0.005) rather than intra-aortic balloon pumps. The presence of a shock team was independently associated with lower CICU mortality (23% vs 29%; adjusted OR: 0.72; 95% CI: 0.55-0.94; P = 0.016). CONCLUSIONS: In this multicenter observational study, centers with shock teams were more likely to obtain invasive hemodynamics, use advanced types of MCS, and have lower risk-adjusted mortality. A standardized multidisciplinary shock team approach may improve outcomes in CS.

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.

Prevalence of rapid response systems in small hospitals: A questionnaire survey.

ABSTRACT: The rapid response system (RRS) was introduced for early stage intervention in patients with deteriorating clinical conditions. Responses to unexpected in-hospital patient emergencies varied among hospitals. This study was conducted to understand the prevalence of RRS in smaller hospitals and to identify the need for improvements in the responses to in-hospital emergencies.A questionnaire survey of 971 acute-care hospitals in western Japan was conducted from May to June 2019 on types of in-hospital emergency response for patients in cardiac arrest (e.g., medical emergency teams [METs]), before obvious deterioration (e.g., rapid response teams [RRTs]), and areas for improvement.We received 149 responses, including those from 56 smaller hospitals (≤200 beds), which provided fewer responses than other hospitals. Response systems for cardiac arrest were used for at least a limited number of hours in 129 hospitals (87%). The absence of RRS was significantly more frequent in smaller hospitals than in larger hospitals (13/56, 23% vs 1/60, 2%; P < .01). METs and RRTs operated in 17 (11%) and 15 (10%) hospitals, respectively, and the operation rate for RRTs was significantly lower in smaller hospitals than in larger hospitals (1/56, 2% vs 12/60, 20%; P < .01). Respondents identified the need for education and more medical staff and supervisors; data collection or involvement of the medical safety management sector was ranked low.The prevalence of RRS or predetermined responses before obvious patient deterioration was ≤10% in small hospitals. Specific education and appointment of supervisors could support RRS in small hospitals.

A Quality Improvement Initiative to Reduce Unnecessary Rapid Responses Using Early Warning Scores.

OBJECTIVES: The Pediatric Early Warning Score (PEWS) is an evidence-based tool that allows early collaborative assessment and intervention for a rapid response team (RRT) activation. The goal of our quality improvement initiative was to reduce the percentage of unnecessary RRT activations by 50% over 2 years without increasing PICU transfers or compromising patient safety and timely evaluation. METHODS: A PEWS system replaced preexisting vital signs-based pediatric RRT criteria and was modified through plan-do-study-act cycles. Unnecessary RRT activations, total RRT activation rate, transfers to the PICU, total clinical interventions performed per RRT, and missed RRT activation rate were compared between intervention periods. Likert scale surveys were administered to measure satisfaction with each modification. RESULTS: There was a significant decrease in the percentage of unnecessary RRT activations from 33% to 3.5% after the implementation of the PEWS and modified-PEWS systems (P < .05). The RRT activation rate decreased from 22.6 to 13.3 RRT activations per 1000 patient care days after implementation of the PEWS and modified-PEWS systems (P < .05), without changes in PICU transfer rates. Physicians reported that the PEWS system improved nursing communication and accuracy of RRT criteria (P < .05). Nursing reported that the PEWS system improved patient management and clinical autonomy (P < .05). CONCLUSIONS: The PEWS systems have been an effective means of identifying deteriorating pediatric patients and reducing unnecessary RRT activations. The new system fosters collaboration and communication at the bedside to prevent acute deterioration, perform timely interventions, and ultimately improve patient safety and outcomes.

Emergencies within hospital wards: An observational study of the non-technical skills of medical emergency teams.

BACKGROUND: Medical emergency teams are essential in responding to acute deterioration of patients in hospitals, requiring both clinical and non-technical skills. This study aims to assess the non-technical skills of medical emergency teams during hospital ward emergencies and explore team members perceptions and experiences of the use non-technical skills during medical emergencies. METHODS: A multi-methods study was conducted in two phases. During phase one observation and assessment of non-technical skills used in medical emergencies using the Team Emergency Assessment Measure (TEAM™) was conducted; and in the phase two in-depth interviews were undertaken with medical emergency team members. RESULTS: Based on 20 observations, mean TEAM™ ratings for non-technical skill domains were: 'leadership' 5.0 out of 8 (±2.0); 'teamwork' 21.6 out of 28 (±3.6); and 'task management' 6.5 out of 8 (±1.4). The mean 'global' score was 7.5 out of 10 (±1.5). The qualitative findings identified three areas, 'individual', 'team' and 'other' contributing factors, which impacted upon the non-technical skills of medical emergency teams. CONCLUSION: Non-technical skills of hospital medical emergency teams differ, and the impact of the skill mix on resuscitation outcomes was recognised by team members. These findings emphasize the importance non-technical skills in resuscitation training and well-developed processes for medical emergency teams.

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.

Características epidemiológicas de los pacientes atendidos en el sector de reanimación de un servicio de emergencia en un hospital de tercer nivel de Argentina / Epidemiological features of patients admitted to the resuscitation unit at an emergency department of a third level hospital in Argentina

Introducción. Conocer las características epidemiológicas (CE) de una población resulta primordial para la definición de estrategias sanitarias. Nuestro objetivo es describir las características de pacientes críticos ingresados al sector reanimación (SR). Materiales y métodos. Estudio descriptivo y retrospectivo realizado en un servicio de urgencias de un hospital de tercer nivel entre 2/7/2018 y 1/7/2019. Se incluyeron todos los pacientes ingresados a SR. Se registró edad, sexo, motivo de ingreso, condición crónica, procedimientos diagnósticos y terapéuticos efectuados. Los datos fueron obtenidos del libro de registro y la historia clínica informatizada, y analizados con software Redcap Versión 8.9.2. Las variables categóricas se expresaron como frecuencias y porcentajes y las continuas con mediana y rango intercuartílico. Resultados. Ingresaron 2292 pacientes. El 94% fueron menores de 16 años. El 56,5% presentaba condiciones crónicas (CC), siendo más frecuentes las enfermedades neurológicas (29%), endocrino/metabólicas (15,5%) y cardiovasculares (11%). Los motivos de ingreso más habituales: enfermedad respiratoria aguda baja (31%), estado epiléptico (13%), sepsis (13%) y deshidratación grave (7%). Estudios complementarios más utilizados: laboratorio (54%), radiografía (28%), hemocultivos (23%). Los procedimientos realizados con más frecuencia fueron la colocación de acceso venoso periférico (67%), cánula nasal de alto flujo (6%) y ventilación mecánica (5%). Las drogas más indicadas: oxígeno (42%), fluidos (34%), antibióticos (22%). El 14% ingresó a cuidados intensivos. Hubo 11 paros cardiorrespiratorios y 6 óbitos. Conclusiones. En el SR se asisten pacientes críticos con patologías de alta prevalencia como también pacientes con enfermedades crónicas complejas. La evaluación periódica de CE resulta una herramienta fundamental para detectar dificultades y elaborar estrategias de mejora (AU)

Introduction. Knowledge on the epidemiological characteristics (EC) of a population is essential to define healthcare strategies. Our aim was to describe the characteristics of critical patients admitted to the resuscitation unit (RU). Materials and methods. A descriptive and retrospective study was conducted at an emergency department of a third-level hospital between 2/7/2018 and 1/7/2019. All patients admitted to the RU were included. Age, sex, reason for admission, underlying disease, and diagnostic and therapeutic procedures performed were recorded. The data were obtained from the logbook and electronic records, and analyzed using Redcap software Version 8.9.2. Categorical variables were expressed as frequencies and percentages and continuous variables as median and interquartile range. Results. 2292 patients were admitted; 94% were younger than 16 years of age. Overall, 56.5% had underlying diseases (UD), the most common of which were neurological (29%), endocrine/metabolic (15.5%), and cardiovascular (11%) disorders. The most common reasons for admission were acute lower respiratory tract disease (31%), status epilepticus (13%), sepsis (13%), and severe dehydration (7%). The most frequently used complementary studies were laboratory tests (54%), x-rays (28%), and hemocultures (23%). The most frequently performed procedures were peripheral venous line (67%), high-flow nasal cannula (6%), and mechanical ventilation (5%) placement. The most frequently indicated medications were oxygen (42%), fluids (34%), and antibiotics (22%). Overall, 14% required admission to the intensive care unit. There were 11 cardiorespiratory arrests and six deaths. Conclusions. Critical patients with highly prevalent diseases as well as patients with complex underlying diseases are seen at the RU. Periodic EC evaluation is a key tool for detecting difficulties and developing improvement strategies (AU)

Uso de tarjetas de medicación en el manejo de estado epiléptico en un servicio de emergencias. Mejoras en prescripción, preparación y administración de drogas / Use of medication cards in the management of statu epilepticus at an emergency department. Improvements in drug prescription, preparation and administration

Introducción: Los errores de medicación (EM) causan una elevada morbimortalidad y generan costos innecesarios. El servicio de emergencias (SE) presenta un mayor riesgo de EM que otras áreas. El desarrollo de una herramienta que estandarice el uso de fármacos podría mejorar la seguridad y el proceso de medicación. Objetivos: Evaluar las mejoras en el proceso de medicación mediante el uso de tablas de medicación (TM) durante la atención del estado epiléptico (EE). Materiales y métodos: Se realizó un estudio de tipo antes y después no controlado. La intervención fue el desarrollo e implementación de TM. Se relevó in situ la prescripción, preparación y administración de fármacos incluidos en las TM durante segunda quincena de Octubre y mes de Noviembre 2016, previo a la implementación de la herramienta, y en el mismo período de 2017, luego de la inducción e implementación de las tablas. Se registraron los EM y se categorizaron de acuerdo a la etapa del proceso en que ocurrieron. Resultados: En el período pre-intervención se realizaron 14 registros, 86% (12) tenía al menos un error; 57% (8) errores en la etapa de prescripción, 57% (8) en la de preparación y 21% (3) en la de administración. En el período post-intervención se realizaron 17 registros, 12% (2) tenía por lo menos un EM. No se registraron errores en la fase de prescripción, hubo 12% (2) de errores de preparación y 6% (1) de administración. Conclusión: La implementación de las TM para la estandarización del uso de fármacos en EE resultó una medida muy positiva, mejorando la seguridad en el proceso de medicación (AU)

Introduction: Medication errors (ME) are associated with high morbidity mortality and lead to unnecessary costs. The risk of ME is higher at the emergency department (ED) than in other areas. Developing a tool that standardizes drug use may improve safety and medication processes. Objectives: To evaluate improvements in the medication process by using medication cards (MCs) during status epilepticus (SE) care. Materials and methods: An uncontrolled before-and-after study was conducted. The intervention was the development and implementation of MCs. The in situ prescription, preparation, and administration of drugs included in the MCs was recorded during the second half of October and November 2016, prior to the implementation of the tool, and in the same period of 2017, after the introduction and implementation of the MCs. ME were recorded and categorized according to the stage of the process in which they occurred. Results: In the pre-intervention period 14 episodes were recorded; in 86% (12) at least one error occurred; 57% (8) were ME in the prescription stage, 57% (8) were ME in the preparation stage, and 21% (3) were ME in the administration stage. In the post-intervention period 17 errors were recorded, in 12% (2) at least one ME occurred. No errors were recorded in the prescription stage, 12% (2) were preparation errors, and 6% (1) administration errors. Conclusion: The implementation of MCs for the standardization of medications used in the RU was successful, improving safety in the medication process (AU)

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.

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.

Quantifying the Impact of Resuscitation-Team Activation in Hospital Emergency Departments.

Hospital emergency department (ED) operations are affected when critically ill or injured patients arrive. Such events often lead to the initiation of specific protocols, referred to as Resuscitation-team Activation (RA), in the ED of Mayo Clinic, Rochester, MN where this study was conducted. RA events lead to the diversion of resources from other patients in the ED to provide care to critically ill patients; therefore, it has an impact on the entire ED system. This paper presents a data-driven and flexible statistical learning model to quantify the impact of RA on the ED. The model learns the pattern of operations in the ED from historical patient arrival and departure timestamps and quantifies the impact of RA by measuring the deviation of the departure of patients during RA from normal processes. The proposed method significantly outperforms baseline methods based on measuring the average time patients spend in the ED.