ABSTRACT
@#Introduction: Maternity wards are of the highly sensitive wards in hospital. Errors in midwifery tasks can lead to life threatening risks for the mother and infant and higher medical costs. The present study is an attempt to qualitatively and quantitatively assess human errors in midwife staff using preventive human error analysis and engineering approach. Methods: The study was carried out as a case study in the maternity ward of Shoushtar Women Hospital. The participants were selected through convenient sampling and seven midwifery experts took part in the study. The work process in maternity ward was categorized into four categories of admittance, pre-labor, labor, and post-labor and the tasks and sub-tasks were determined based on hierarchical task analysis (HTA). Afterwards, human errors were quantified using EA technique and then, using PHEA technique a description of error in each tasks and error control solutions were provided. Results: The results clarified that the highest risks of human errors were in the tasks like cervix check, serum therapy, infant’s body check, preparing delivery equipment, and wearing personal protective equipment. Conclusion: Since, midwifery tasks are rule base and regulations and they are performed at a higher level of awareness and cognition, preventing errors entails continuous presence of a midwife next to patient’s bed along with an assistant midwife and codification of an infant examination checklist. Programming empowerment education including safety education to midwives is also recommended.
ABSTRACT
Introducción: la no disponibilidad e insuficiente flexibilidad de las herramientas de estudio de percepción de riesgo es limitante para alcanzar su generalización en diferentes ámbitos. Objetivo: diseñar un sistema informático para evaluación de percepción de riesgo flexible y demostrar su capacidad a través de aplicaciones a varios casos de estudio. Métodos: a partir del método de evaluación de percepción de riesgo ocupacional (EPRO), se elaboró el algoritmo base del código RISKPERCEP. Resultados: el método EPRO, informatizado a través de RISKPERCEP, se aplicó a escenarios diversos con peligro biológico asociado, como una empresa de producción de productos biológicos, un banco de sangre y las labores de las brigadas de vigilancia y lucha antivectorial. Se obtuvo en general, un perfil de subestimación de los peligros entre el personal ocupacionalmente expuesto. Conclusiones: la herramienta computarizada identificada como RISKPERCEP facilita la evaluación de percepción de riesgo, de manera que flexibiliza el análisis y permite su extensión a diferentes escenarios con riesgo biológico(AU)
Introduction: the unavailability and the inadequate flexibility of the risk perception analysis tools hinder their general use in different contexts. Objective: to design a flexible software system to evaluate the flexibility of risk perception and to prove its capacity in various case studies. Methods: the basic algorithm of the RISKPERCEP code was created on the basis of the evaluation method of the occupational perception risk (EPRO). Result: the ORPE method through the RISKPERCEP software was applied in different scenarios with associated biological hazards, for example, in a manufacturing company of biologicals, a blood bank or to the work of the surveillance and vector control units. Conclusion: the RISKPERCEP software facilitates the risk perception analysis and allows the extension of such method to different scenarios with biological hazards(AU)
Subject(s)
Humans , Risk Assessment/methods , SoftwareABSTRACT
Human errors are errors found in planning or implementation, and those found in medical practice are often major causes of mishaps.To name a few, wrong-site surgery, medication error, wrong treatment, and inadvertent equipment operation.Errors of this category can be prevented by learning from experiences and achievement worldwide.Preventive measures include those taken in human aspect and system aspect, reinforced education and training, process optimization, and hardware redesign.These measures can be aided by multiple safety steps in risky technical operations, in an effort to break the accident chain.For example, pre-operative surgical site marking, multi-department co-operated patient identification, bar-coded medication delivery, read-back during verbal communication, and observation of clinical pathway.Continuous quality improvement may be achieved when both the management and staff see medical errors in the correct sense, and frontline staff are willing to report their errors.