Development of Rapid Response Capabilities in a Large COVID-19 Alternate Care Site Using Failure Modes and Effect Analysis with In Situ Simulation.

Preparedness measures for the anticipated surge of coronavirus disease 2019 (COVID-19) cases within eastern Massachusetts included the establishment of alternate care sites (field hospitals). Boston Hope hospital was set up within the Boston Convention and Exhibition Center to provide low-acuity care for COVID-19 patients and to support local healthcare systems. However, early recognition of the need to provide higher levels of care, or critical care for the potential deterioration of patients recovering from COVID-19, prompted the development of a hybrid acute care-intensive care unit. We describe our experience of implementing rapid response capabilities of this innovative ad hoc unit. Combining quality improvement tools for hazards detection and testing through in situ simulation successfully identified several operational hurdles. Through rapid continuous analysis and iterative change, we implemented appropriate mitigation strategies and established rapid response and rescue capabilities. This study provides a framework for future planning of high-acuity services within a unique field hospital setting.

Mejora en la seguridad de un proceso clínico utilizando el análisis modal de fallos y efectos: profilaxis de la enfermedad tromboembólica venosa en pacientes críticos / Improvement of the safety of a clinical process using failure mode and effects analysis: Prevention of venous thromboembolic disease in critically ill patients

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Estrategias para aumentar la seguridad del paciente en hemodiálisis: Aplicación del sistema de análisis modal de fallos y efectos (sistema AMFE) / Strategies to increase patient safety in Hemodialysis: Application of the modal analysis system of errors and effects (FEMA system)

Antecedentes: La población en hemodiálisis (HD) es de alto riesgo. En estos pacientes un fallo puede tener consecuencias catastróficas, por lo que son necesarios sistemas que garanticen su seguridad en un entorno con alta tecnología y gran interacción del factor humano. Objetivos: Mostrar una sistemática de trabajo, reproducible en cualquier unidad de HD, que consiste en registrar las complicaciones y fallos ocurridos durante la sesión, definir cuáles de estas complicaciones podrían ser consideradas eventos adversos (EA) y, por tanto, prevenibles y realizar un análisis sistemático tanto de ellos como de los fallos reales o potenciales subyacentes, evaluando su gravedad, frecuencia y detección, y estableciendo prioridades de actuación (sistema de análisis modal de fallos y efectos [AMFE]). Métodos: Examen retrospectivo de las gráficas de diálisis de todas las sesiones practicadas durante un mes (octubre de 2015) en 97 pacientes, y análisis de las complicaciones registradas. La consideración de estas complicaciones como EA se basó en el consenso entre 13 profesionales y 2 pacientes. Se valoró la severidad, frecuencia y detección de cada fallo real o potencial mediante el sistema AMFE. Resultados: Se practicaron 1.303 sesiones de HD en 97 pacientes en las que se registraron un total de 383 complicaciones (1 cada 3,4 tratamientos). De ellas, el 87,9% fueron consideradas EA y el 23,7% complicaciones relacionadas con la enfermedad de base. Se detectó un EA cada 3,8 tratamientos. Los EA más frecuentes fueron la hipertensión y la hipotensión (42,7 y 27,5% del total de EA registrados, respectivamente). Los EA relacionados con el acceso vascular fueron uno de cada 68,5 tratamientos. Se registraron un total de 21 fallos en la asistencia (1 cada 62 tratamientos), los cuales estaban relacionados con fallos en la aplicación de la técnica y en la administración de la medicación. El mayor número de prioridad de riesgo lo obtuvieron los fallos relacionados con errores en el peso, disfunción o rotura del catéter y salida de agujas. Conclusiones: Las complicaciones en HD son frecuentes y la consideración de algunas de ellas como EA podría mejorar la seguridad en la asistencia, al poner en marcha medidas preventivas. La implementación del sistema AMFE permite estratificar y priorizar los posibles fallos de las unidades de diálisis, y actuar con mayor o menor premura, desarrollando las acciones de mejora necesarias (AU)

Background: Haemodialysis (HD) patients are a high-risk population group. For these patients, an error could have catastrophic consequences. Therefore, systems that ensure the safety of these patients in an environment with high technology and great interaction of the human factor is a requirement. Objectives: To show a systematic working approach, reproducible in any HD unit, which consists of recording the complications and errors that occurred during the HD session; defining which of those complications could be considered adverse event (AE), and therefore preventable; and carrying out a systematic analysis of them, as well as of underlying real or potential errors, evaluating their severity, frequency and detection; as well as establishing priorities for action (Failure Mode and Effects Analysis system [FMEA systems]). Methods: Retrospective analysis of the graphs of all HD sessions performed during one month (October 2015) on 97 patients, analysing all recorded complications. The consideration of these complications as AEs was based on a consensus among 13 health professionals and 2 patients. The severity, frequency and detection of each AE was evaluated by the FMEA system. Results: We analysed 1303 HD treatments in 97 patients. A total of 383 complications (1 every 3.4 HD treatments) were recorded. Approximately 87.9% of them was deemed AEs and 23.7% complications related with patients'underlying pathology. There was one AE every 3.8 HD treatments. Hypertension and hypotension were the most frequent AEs (42.7 and 27.5% of all AEs recorded, respectively). Vascular-access related AEs were one every 68.5 HD treatments. A total of 21 errors (1 every 62 HD treatments), mainly related to the HD technique and to the administration of prescribed medication, were registered. The highest risk priority number, according to the FMEA, corresponded to errors related to patient body weight; dysfunction/rupture of the catheter; and needle extravasation. Conclusions: HD complications are frequent. Consideration of some of them as AEs could improve safety by facilitating the implementation of preventive measures. The application of the FMEA system allows stratifying real and potential errors in dialysis units and acting with the appropriate degree of urgency, developing and implementing the necessary preventive and improvement measures (AU)

Análisis modal de fallos y efectos de la utilización de jeringas orales para administrar medicamentos líquidos / Failure mode and effects analysis applied to the administration of liquid medication by oral syringes

Objetivo: Realizar un análisis modal de fallos y efectos (AMFE) aplicado a la utilización de jeringas orales. Métodos: Un grupo multidisciplinar dentro del Comité de Seguridad analizó las etapas en la administración oral de los medicamentos líquidos, identificándose las más críticas y estableciendo modos potenciales de fallo que podrían producir un error. El riesgo asociado a cada modo de fallo se calculó utilizando el número de prioridad de riesgo (NPR). Se sugirieron acciones preventivas. Resultados: Se identificaron cinco modos de fallo, todos clasificados de alto riesgo (NPR>100). Siete de las ocho recomendaciones fueron implementadas. Conclusiones: La aplicación de la metodología AMFE ha sido una herramienta muy útil que ha permitido conocer los riesgos, analizar las causas que los pueden provocar y saber los efectos que tienen en la seguridad del paciente; todo ello con el fin de implantar acciones para reducirlos (AU)

Objective: To carry out a Failure Mode and Effects Analysis (FMEA) to the use of oral syringes. Methods: A multidisciplinary team was assembled within the Safety Committee. The stages of oral administration process of liquid medication were analysed, identifying the most critical and establishing the potential modes of failure that can cause errors. The impact associated with each mode of failure was calculated using the Risk Priority Number (RPN). Preventive actions were proposed. Results: Five failure modes were identified, all classified as high risk (RPN> 100). Seven of the eight preventive actions were implemented. Conclusions: The FMEA methodology was a useful tool. It has allowed to know the risks, analyse the causes that cause them, their effects on patient safety and the measures to reduce them (AU)

Implementación de la sedación con propofol: utilidad del análisis modal de fallos y efectos. Calidad y seguridad centrada en el paciente / Propofol sedation Quality and safety. Failure mode and effects analysis

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[Actualization of methodological problems of reglamentation of chemical pollutions on the environment]

There has been demonstrated a sharp increase of chemical pressing on the environment and human health, detection of hundreds of chemical compounds in different environmental objects, most of such chemicals have no hygienic standards. There are presented main disadvantages oKikuworks on the risks assessment of the impact ofpolluted environment on human health. There are indicated priority directions of the improvement of the analysis methodology and risk management, based on modern international achievements, as well as evaluation of detriments to the environment and human health with taking into account world systems as follows: AirQ (WHO), IEHIA and APHEIS (EU), FERET and EPA (USA), EAHEAP and COMEAP (GreatBritain), ECOSENSE (Germany), AirPack (EU, France), AQVM (Canada), and also domestic of TERA 2,5 (module EpidRisk). The integral evaluation of the scientific disciplines "Human Ecology", "EnvironmentalHealth" and "EnvironmentalMedicine" is given. Comparative conceptual considertion of the terms "Environment", "Habitat" and their international application is given.

Can binary early warning scores perform as well as standard early warning scores for discriminating a patient's risk of cardiac arrest, death or unanticipated intensive care unit admission?

INTRODUCTION: Although the weightings to be summed in an early warning score (EWS) calculation are small, calculation and other errors occur frequently, potentially impacting on hospital efficiency and patient care. Use of a simpler EWS has the potential to reduce errors. METHODS: We truncated 36 published 'standard' EWSs so that, for each component, only two scores were possible: 0 when the standard EWS scored 0 and 1 when the standard EWS scored greater than 0. Using 1564,153 vital signs observation sets from 68,576 patient care episodes, we compared the discrimination (measured using the area under the receiver operator characteristic curve--AUROC) of each standard EWS and its truncated 'binary' equivalent. RESULTS: The binary EWSs had lower AUROCs than the standard EWSs in most cases, although for some the difference was not significant. One system, the binary form of the National Early Warning System (NEWS), had significantly better discrimination than all standard EWSs, except for NEWS. Overall, Binary NEWS at a trigger value of 3 would detect as many adverse outcomes as are detected by NEWS using a trigger of 5, but would require a 15% higher triggering rate. CONCLUSIONS: The performance of Binary NEWS is only exceeded by that of standard NEWS. It may be that Binary NEWS, as a simplified system, can be used with fewer errors. However, its introduction could lead to significant increases in workload for ward and rapid response team staff. The balance between fewer errors and a potentially greater workload needs further investigation.

Individualizing and optimizing the use of early warning scores in acute medical care for deteriorating hospitalized patients.

AIM: While early warning scores (EWS) have the potential to identify physiological deterioration in an acute care setting, the implementation of EWS in clinical practice has yet to be fully realized. The primary aim of this study is to identify optimal patient-centered rapid response team (RRT) activation rules using electronic medical records (EMR)-derived Markovian models. METHODS: The setting for the observational cohort study included 38,356 adult general floor patients hospitalized in 2011. The national early warning score (NEWS) was used to measure the patient health condition. Chi-square and Kruskal Wallis tests were used to identify statistically significant subpopulations as a function of the admission type (medical or surgical), frailty as measured by the Braden skin score, and history of prior clinical deterioration (RRT, cardiopulmonary arrest, or unscheduled ICU transfer). RESULTS: Statistical tests identified 12 statistically significant subpopulations which differed clinically, as measured by length of stay and time to re-admission (P < .001). The Chi-square test of independence results showed a dependency structure between subsequent states in the embedded Markov chains (P < .001). The SMDP models identified two sets of subpopulation-specific RRT activation rules for each statistically unique subpopulation. Clinical deterioration experience in prior hospitalizations did not change the RRT activation rules. The thresholds differed as a function of admission type and frailty. CONCLUSIONS: EWS were used to identify personalized thresholds for RRT activation for statistically significant Markovian patient subpopulations as a function of frailty and admission type. The full potential of EWS for personalizing acute care delivery is yet to be realized.