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Objective:To explore the effect of healthcare failure mode and effect analysis (HFMEA) in reducing the incidence of nursing interruption with negative outcome in operating room, so as to maximize the smooth progress of the surgical process.Methods:This was a quasi experimental study. The gastrointestinal surgery room of Shandong Provincial Hospital Affiliated to Shandong First Medical University was selected for the study. According to the surgical sequence, 38 surgeries performed in the gastrointestinal surgery suite from August 15-30, 2021 were set as the control group, and the conventional healthcare cooperation model process was implemented; 42 surgeries performed from September 15-30, 2021 were set as the intervention group, and the operating room under the HFMEA model was implemented negative outcome care disruption event management process.A video tracking method combined with a surgical care disruption event register was used to investigate the occurrence of negative outcome care disruption events in the operating room, comparing the number, duration, source of disruption events and the incidence of near miss events in the operating room between the control group and the intervention group.Results:In the control group, there were 38 observed surgeries, 190 negative outcome care interruptions, negative outcome interruptions of (5.26 ± 1.02) min duration, and no near misses; in the intervention group, there were 42 observed surgeries, 84 negative outcome care interruptions, negative outcome interruptions of (2.06 ± 0.08) min duration, and no near misses. There were statistically significant differences in the number, duration of negative outcome care interruptions between the intervention group and the control group ( χ2 = - 18.71, t = - 20.28; all P<0.01). There was statistically significant difference in the source of negative outcome care interruptions between the intervention group and the control group ( χ2 = - 12.71, P<0.01). Conclusions:HFMEA model can effectively reduce the number of negative nursing interruptions in the operating room, shorten the duration of interruptions, and minimize potential safety hazards caused by nursing interruptions, which is conducive to ensuring the safety of patients.
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Objective:To explore the application of effect of healthcare failure mode and effect analysis (HFMEA) in emergency waiting risk management.Methods:From May 2020 to April 2021, totally 87 902 emergency waiting patients from the First Affiliated Hospital of Anhui Medical University were assigned to control group by cluster sampling method. From May 2021 to April 2022, 80 594 emergency waiting patients were assigned to observed group. The patients in the control group received routine emergency waiting of itinerant management mode. In contrast, the patients in the observed group received emergency waiting risk management mode based on HFMEA. The process risk priority number (RPN) and waiting risk management index between two groups were compared.Results:The mean RPN of the observed group was (98.48 ± 8.27) points, significantly lower than that of the control group (251.27 ± 16.95) points. The nurses′ pre-identification rates of changes in the condition and adverse reaction in the observed group were 10.77%(8680/80 594) and 13.37%(10 775/80 594), which were higher than those in the control group, 5.77%(5072/87 902) and 8.12%(7134/87 902), the differences were statistically significant ( χ2 values were 1402.32 and 1221.66, all P<0.05). Conclusions:The application of HFMEA to optimize the emergency waiting management process can effectively reduce the risk of emergency waiting and improve the quality of emergency waiting management.
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ABSTRACT Objectives: to identify, classify, and analyze modes of failure in the medication process. Methods: evaluative research that used the Healthcare Failure Mode and Effect Analysis (HFMEA) in a service of bone marrow transplant from June to September 2018, with the participation of 35 health workers. Results: 207 modes of failure were identified and classified as mistakes in verification (14%), scheduling (25.6%), administration (29%), dilution (16.4%), prescription (2.4%), and identification (12.6%). The analysis of risk showed a moderate (51.7%) and high (30.9%) need of intervention, leading to the creation of an internal quality assurance group and of continued education activities. Conclusions: the Healthcare Failure Mode and Effect Analysis showed itself to be a tool to actively identify, classify, and analyze failures in the process of medication, contributing for the proposal of actions aimed at patient safety.
RESUMEN Objetivos: identificar, clasificar y analizar modos de fallos en el proceso de medicación. Métodos: investigación evaluativa que utilizó el Healthcare Failure Mode and Effect Analysis (HFMEA) en Servicio de Trasplante de Médula Ósea, de junio a septiembre de 2018, con la participación de 35 profesionales de salud. Resultados: han sido identificados 207 modos de fallos, clasificados en errores de chequeo (14%); aplazamiento (25,6%); administración (29%); dilución (16,4%); prescripción (2,4%) e identificación (12,6%). El análisis del riesgo evidenció la necesidad de intervención moderada (51,7%) y alta (30,9%), resultando en la creación del equipo interno de calidad y actividades de educación continua. Conclusiones: el Healthcare Failure Mode and Effect Analysis demostró ser herramienta para identificar, clasificar y analizar, activamente, fallos en el proceso de medicación, contribuyendo para la proposición de acciones con objetivo de seguridad del paciente.
RESUMO Objetivos: identificar, classificar e analisar modos de falhas no processo de medicação. Métodos: pesquisa avaliativa que utilizou o Healthcare Failure Mode and Effect Analysis (HFMEA) em Serviço de Transplante de Medula Óssea, de junho a setembro de 2018, com a participação de 35 profissionais de saúde. Resultados: foram identificados 207 modos de falhas, classificados em erros de checagem (14%); aprazamento (25,6%); administração (29%); diluição (16,4%); prescrição (2,4%) e identificação (12,6%). A análise do risco evidenciou a necessidade de intervenção moderada (51,7%) e alta (30,9%), resultando na criação do grupo interno de qualidade e atividades de educação continuada. Conclusões: o Healthcare Failure Mode and Effect Analysis demonstrou ser ferramenta para identificar, classificar e analisar, ativamente, falhas no processo de medicação, contribuindo para a proposição de ações com vistas à segurança do paciente.
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【Objective】 To analyze the root causes of adverse events to insufficient plasma transfusion, so as to explore improvement measures, optimize the transfusion strategy and avoid such adverse events. 【Methods】 The root causes of insufficient plasma transfusion were analyzed by health care failure mode and effect analysis, the targeted improvement measures were formulated and the effect was evaluated. 【Results】 After the improvement, the incidence of adverse events to insufficient plasma transfusion decreased significantly.The risk priority value affecting the safety of blood transfusion decreased from 70 to 8, and the proportion of coagulation function test after blood transfusion increased from 44.61%(1 309/2 934)in 2012 to 80.55% (2 187/2 715)in 2019, and plasma transfusion volume per capital increased from 300 mL to 528 mL. PT and APTT values after plasma transfusion in 2019 significantly increased compared with those in 2012. Meanwhile, the proportion of plasma transfusion in hospitalized patients decreased from 3.16% (2 934/92 838)to 2.12%(2 715/128 352). 【Conclusion】 Risk management of quality and safety of blood transfusion by combing healthcare failure mode, effect analysis and root cause analysis(RCA) can improve the risk awareness of clinical blood transfusion, optimize the proportion of plasma transfusion, and is essential to ensure the safety and effectiveness of blood transfusion and improve the prognosis of transfused patients.
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RESUMO Objetivo discutir acerca da utilização das ferramentas de Análise de Modo e Efeitos de Falha e sua aplicação na assistência à saúde. Método trata-se de um artigo de reflexão visando à apresentação do formato próprio de aplicação de ambas as ferramentas seguida das suas diferenças de execução nos processos de trabalho. Resultados ambos os modelos possuem a mesma finalidade, sendo direcionados para a detecção de falhas antes mesmo da sua manifestação, auxiliando diretamente na promoção da segurança. A análise do erro, com a participação das equipes e a geração de índices de falhas, repercute no planejamento e na implementação de ações práticas voltadas à segurança do paciente. Conclusão e implicações para a prática embora semelhantes, existem, entre eles, distinções quanto à priorização das falhas para elencar ações práticas corretivas, principalmente no cálculo do Índice de Prioridade de Risco relacionado à gravidade, na probabilidade de ocorrência e na detecção das falhas. Ambas as ferramentas se mostram como importantes aliadas dos gestores de saúde para a detecção de falhas graves que colocam em risco a assistência livre de eventos adversos.
RESUMEN Objetivo discutir el uso de las herramientas de Análisis de Modos y Efectos de Falla y su aplicación en la atención médica. Método este es un artículo de reflexión, con el objetivo de presentar el formato propio de aplicación adecuado para ambas herramientas, seguido de sus diferencias de ejecución en los procesos de trabajo. Resultados ambos modelos tienen el mismo propósito, dirigidos a la detección de fallas incluso antes de su manifestación, ayudando directamente en la promoción de la seguridad. El análisis del error con la participación de los equipos y la generación de tasas de fracaso tiene repercusiones en la planificación e implementación de acciones prácticas dirigidas a la seguridad del paciente. Conclusión e implicaciones para la práctica aunque son similares, existen distinciones con respecto a la priorización de fallas para enumerar acciones correctivas prácticas, principalmente en el cálculo del Índice de Prioridad de Riesgo relacionado con la gravedad, la probabilidad de ocurrencia y la detección de fallas. Se ha demostrado que ambas herramientas son aliadas importantes para los gerentes de salud para la detección de fallas graves que ponen en riesgo la atención libre de eventos adversos.
ABSTRACT Objective to discuss the use of Failure Mode and Effects Analysis tools and their application in health care. Method this is a reflection article, aiming at presenting the proper application format for both tools, followed by their differences in execution in the work processes. Results both models have the same purpose, being directed to the detection of failures even before their manifestation, directly assisting in the promotion of safety. The analysis of the error with the participation of the teams and the generation of failure rates has repercussions on the planning and implementation of practical actions aimed at patient safety. Conclusion and implications for the practice although similar, there are distinctions regarding the prioritization of failures to list practical corrective actions, mainly in the calculation of the Risk Priority Index related to severity, probability of occurrence and failure detection. Both tools are shown to be important allies to health managers for the detection of serious failures that put care free from adverse events at risk.
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Humanos , Evaluación de Procesos, Atención de Salud/métodos , Seguridad del Paciente , Análisis de Modo y Efecto de Fallas en la Atención de la SaludRESUMEN
Abstract Introduction: Patient safety has become a core value in health organizations, requiring the use of significant resources in order to avoid accidents during hospital stay. Health care can create risks, and patient safety is the most important objective in care quality. Failure Mode and Effects Analysis (FMEA) is a preventive tool that helps anticipate potential errors and adverse events, setting up barriers to prevent them from happening, or mitigating their effects or, in the event they do happen, mitigating their impact on the most vulnerable link in health care, namely, the patient. Objectives: To analyze, using the FMEA tool, mobilization of intubated critical ill patients in the Intensive Care Unit. Method: A brainstorming session was held within the service to identify the most frequent potential errors in the process. Subsequently, the FMEA method with its different phases was applied, prioritizing risk according to the RPN (Risk Priority Number) index and selecting improvement actions for those with an RPN greater than 300. Results: The result was the identification of 101 failure modes, of which 46 exceeded the RPN of 300. As a result of this work, 63 improvement actions have been proposed for those failure modes with NPR scores above 300. Conclusion: The conclusion of the study is that FMEA was a useful tool for anticipating potential failures in the process and proposing improvement actions for those that exceeded an RPN of 300.
Resumen Introducción: La seguridad del paciente ha adquirido un valor estratégico en las organizaciones sanitarias, empleando numerosos recursos para evitar accidentes durante la estancia hospitalaria. La asistencia sanitaria puede generar un riesgo y la seguridad del paciente es el objetivo más importante de la calidad asistencial. AMFE es una herramienta preventiva, lo que supone una anticipación a los posibles errores y eventos adversos, poniendo barreras para que no sucedan o si lo hacen mitigar sus efectos sobre la parte más vulnerable de la atención sanitaria, el paciente. Objetivos: Analizar, a través de la herramienta AMFE (Análisis Modal de Fallos y Efectos), la movilización del paciente crítico intubado en la Unidad de Cuidados Intensivos. Método: Para ello se realizó una tormenta de ideas dentro del servicio para decidir los posibles errores más frecuentes en el proceso. Posteriormente, se aplicó el método AMFE, con sus fases, priorizando el riesgo conforme al índice NPR (Numero de Priorización de Riesgo), seleccionando acciones de mejora en los que tienen un NPR mayor de 300. Resultados: Como resultado hemos obtenido 101 modos de fallo de los cuales 46 superaban el NPR de 300. Tras nuestro resultado, se han propuesto 63 acciones de mejora en aquellos modos de fallo con puntuaciones NPR superiores a 300. Conclusiones: La conclusión del estudio es que AMFE permite anticiparnos a los posibles fallos del proceso para proponer acciones de mejora en aquellos que superan un NPR de 300.
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HumanosRESUMEN
OBJECTIVE: To prevent medication errors during drug subpackage and ensure patients' medication safety. METHODS: Healthcare failure mode and effect analysis (HFMEA) was applied to evaluate the potential failure modes and effects during drug repackaging and dispensing. Thereafter rectification measures was analyzed and carried out in order to prevent the recurrence of failure modes. Risk priority numbers (RPNs) before and after the implication of rectification measures were analyzed using paired t tests. RESULTS: After the application of healthcare failure mode and effect analysis, RPN was statistically significantly (P<0.05) reduced by 60% (P=0.000 2), which affecting the incidences of medication errors during drug unit-dose repackaging. CONCLUSION: The application of healthcare failure mode and effect analysis can effectively prevent medication errors during drug subpackage and improve patients' medication safety.
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Objective To optimize the process of hyperglycemia management in hospitalized diabetic patients,to standardize behaviors of medical staff and reduce the incidence of adverse events.Methods The team of hyperglycemia management was established to reformulate flowchart of hyperglycemia management for diabetic patients,and to design and implement the intervention scheme by applying Healthcare Failure Mode and Effect Analysis (HFMEA).Results After the application of HFMEA,the reporting rate of hyperglycemia was increased from 74.56％ to 77.98％,the rate of insulin injection was increased from 91.12％ to 94.08％;the qualification rate of theoretical knowledge among nurses was increased from 56.25％ to 93.75％,the qualification rate of insulin injection practice was increased from 43.75％ to 93.75％;the incidence of adverse events related to insulin injection was decreased from 7.31‰ to 1.9‰.The differences were statistically significant (P＜0.05).Conclusion Utilization of HFMEA to optimize the process of hyperglycemia management can effectively standardize behaviors of medical staff and reduce the incidence of adverse events associated with insulin injection.
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Objective To optimize the cerebral ischemia-reperfusion process for acute ischemic stroke patients,so as to reduce the time of in-hospital delays.Methods A multi-disciplinary management team was established to design the flowchart of the cerebral ischemia-reperfusion process for acute ischemic stroke patients.By applying Healthcare Failure Mode and Effect(HFMEA) management mode,intervention was conducted and its effect was analyzed.Results After implementation of the HFMEA intervention,the door to needle time(DNT)was reduced from 88 (42,140) minutes to 45 (37,59) minutes(P＜0.001);the ratio of patients with the DNT＜60 minutes increased from 20％ to 87.7％(P＜0.001);the door to cerebral ischemia-reperfusion time was shortened from 207(169,227) minutes to 165(155,185) minutes (P＜O.05).There was no significant difference in the incidence and mortality of symptomatic cerebral hemorrhage between before and after intervention (P＞0.05).Conclusion Utilization of HFMEA to optimize the emergency cerebral ischemia-reperfusion process can effectively reduce the in-hospital delays of acute ischemic stroke patients.
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Objective To evaluate the efficacy of healthcare failure mode and effect analysis in enhanced recovery after surgery(ERAS) in thoracic surgery. Methods Establish the healthcare failure mode and effect analysis group and evaluate the possible healthcare failure modes in implementation of ERAS.Calculate the odds ratio and make a decision tree in order to find out the failure modes and make safe schemes for bowel preparation, peri-operative pain monitoring and evaluation, vein thrombosis screening and management, early mobilization and food-taking after surgery and catheter removal for patients with benign prostate hyperplasia. Results Before and after the implementation of ERAS, 237 patients were selected.The risk priority number after the implementation of ERAS had been reduced,all less than 8 points. After the implementation of ERAS, the rate of initial pain score greater than 4 was 53.2%(126/237),the incidence of nausea and vomiting was 13.5%(32/237),and incidences of thrombosis and constipation were all 6.8%(16/237),the urinating patency rate after pulling-out the tube was 100.0%(237/237). Before the implementation of ERAS, the indicators was 96.6%(229/237), 43.0%(102/237), 30.0%(71/237), 36.7%(87/237),79.7%(189/237).There was significant difference before and after the implementation of ERAS (χ2=5.455-15.022, P<0.05). Conclusions The application of healthcare failure mode and effect analysis can reduce the incidence of adverse reaction and complications after thoracic surgery and ensure a secure and high-quality implementation of ERAS,which is worth using widely.