Simulation-Based Evaluation of the Effects of Patient Load on Mental Workload of Healthcare Staff

Rusnock, Christina F.; Maxheimer, Erich W; Oyama, Kyle F.; Valencia, Vhance V.

doi:10.1097/sih.0000000000000248

Cited by 7 publications

(4 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…By using DES to evaluate different scenarios, they quantitatively demonstrated that advanced preparation has the strongest potential for improving patient waiting times [32]. In addition, Rusnock et al (2017) used DES to quantitatively model the mental workload of healthcare staff in an inpatient unit at a medical center [33]. The model was deployed to find the optimal idle time, average workload, and overload time of healthcare staff under different patient loads.…”

Section: Plos Onementioning

confidence: 99%

Designing optimal COVID-19 testing stations locally: A discrete event simulation model applied on a university campus

Saidani

Kim

2021

PLoS ONE

View full text Add to dashboard Cite

Providing sufficient testing capacities and accurate results in a time-efficient way are essential to prevent the spread and lower the curve of a health crisis, such as the COVID-19 pandemic. In line with recent research investigating how simulation-based models and tools could contribute to mitigating the impact of COVID-19, a discrete event simulation model is developed to design optimal saliva-based COVID-19 testing stations performing sensitive, non-invasive, and rapid-result RT-qPCR tests processing. This model aims to determine the adequate number of machines and operators required, as well as their allocation at different workstations, according to the resources available and the rate of samples to be tested per day. The model has been built and experienced using actual data and processes implemented on-campus at the University of Illinois at Urbana-Champaign, where an average of around 10,000 samples needed to be processed on a daily basis, representing at the end of August 2020 more than 2% of all the COVID-19 tests performed per day in the USA. It helped identify specific bottlenecks and associated areas of improvement in the process to save human resources and time. Practically, the overall approach, including the proposed modular discrete event simulation model, can easily be reused or modified to fit other contexts where local COVID-19 testing stations have to be implemented or optimized. It could notably support on-site managers and decision-makers in dimensioning testing stations by allocating the appropriate type and quantity of resources.

show abstract

Section: Plos Onementioning

confidence: 99%

Designing optimal COVID-19 testing stations locally: A discrete event simulation model applied on a university campus

Saidani

Kim

2021

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…Así mismo, los autores analizados coinciden en reafirmar que la carga mental es una construcción compleja, con múltiples dimensiones (8,18), que involucra: aspectos o demandas cognitivas y características de las tareas; situación y capacidad de las personas para procesar información y tomar decisiones para cumplir con las demandas físicas, temporales y ambientales (18); carga externa que incluye la carga cognitiva causada por el exceso de información o actividad (8); relación percibida entre la capacidad de recursos mentales y de procesamiento de información con procesos neurofisiológicos, perceptuales y cognitivos requeridos para realizar una tarea (19); esfuerzo cognitivo en un tiempo concreto para hacer frente a tareas (20); relación entre la información procesada y las dificultades para tomar decisiones bajo presión temporal; carga atencional necesaria para mantener un nivel de ejecución adecuado (10); desequilibrio entre las demandas de la tarea, las habilidades y características de los trabajadores (10,21).…”

Section: Categorías De Análisisunclassified

Carga mental en personal de enfermería: Una revisión integradora

Vargas-Cruz

Coral-Ibarra

Barreto-Osorio

2020

Rev. cienc. cuidad.

View full text Add to dashboard Cite

Introducción: Los profesionales de enfermería están expuestos constantemente a situaciones que generan carga como consecuencia del esfuerzo físico, mental, emocional y económico del cuidado. Objetivo: Identificar a través de la literatura científica el concepto de “Carga Mental en enfermeras”, los instrumentos de medición y las estrategias para mitigarla o prevenirla. Medotología: Se realizó una revisión integradora de literatura durante los años 2017 a 2019 sobre artículos publicados desde el año 2000. Se utilizaron las palabras clave DeCS en Español, Inglés y Portugués de: Carga de Trabajo-Workload-Carga de Trabalho, Fatiga Mental- Mental Fatigue- Fadiga Mental, Atención a la Salud Mental-Mental Health Assistance- Assistência à Saùde Mental, Enfermeras-Nurses-Enfermeiras. Las bases de datos consultadas fueron: ProQuest, Scielo, ScienceDirect, Ovid Nursing, Wiley Online Library, EBSCO, ClinicalKey, PubMed, SCOPUS. Se analizaron 39 artículos que cumplieron con los criterios de inclusión. Resultados: Las categorías de análisis fueron: Concepto de carga mental, instrumentos de medición de carga mental en enfermeras y estrategias para mitigarla o prevenirla. Conclusiones: La carga mental es un constructo complejo sin consenso en su definición, incluye varias dimensiones, implica realizar mediciones e intervenciones cognitivas de la función mental, estrés, asertividad y percepción. Se valora a través de medidas fisiológicas de rendimiento y subjetivas. Las últimas han sido las más utilizadas aplicando el método NASA TLX. Las estrategias para mitigarla son: uso de tecnologías, potenciación de capacidades individuales, justicia distributiva y comunicación asertiva

show abstract

“…1,2 Studies of anesthesiologists, obstetricians, and internists have demonstrated the utility of simulation-based CPD (SBCPD) to improve decision making and test protocols. [3][4][5] Cook et al 6 similarly explored the outcomes of SBCPD, concluding that physician participation has a positive impact on knowledge, skills, and behaviors with a significant improvement in patient-related outcomes. A recent systematic review of SBCPD articles demonstrated extensive variability in design, delivery, and evaluation of simulation across specialties, with several of the included studies highlighting the positive impact of simulation-based education (SBE) on physician learning and organizational performance.…”

mentioning

confidence: 99%

“…Simulation is becoming a popular educational modality for physician continuing professional development (CPD), with demands for its increased utilization 1,2 . Studies of anesthesiologists, obstetricians, and internists have demonstrated the utility of simulation-based CPD (SBCPD) to improve decision making and test protocols 3–5 . Cook et al 6 similarly explored the outcomes of SBCPD, concluding that physician participation has a positive impact on knowledge, skills, and behaviors with a significant improvement in patient-related outcomes.…”

mentioning

confidence: 99%

Simulation in the Continuing Professional Development of Academic Emergency Physicians

et al. 2021

View full text Add to dashboard Cite

Introduction: Simulation is becoming a popular educational modality for physician continuing professional development (CPD). This study sought to characterize how simulation-based CPD (SBCPD) is being used in Canada and what academic emergency physicians (AEPs) desire in an SBCPD program. Methods: Two national surveys were conducted from March to June 2018. First, the SBCPD Needs Assessment Survey was administered online to all full-time AEPs across 9 Canadian academic emergency medicine (EM) sites. Second, the SBCPD Status Survey was administered by telephone to the department representatives (DRs)-simulation directors or equivalent-at 20 Canadian academic EM sites. Results: Response rates for the SBCPD Needs Assessment and the SBCPD Status Survey were 40% (252/635) and 100% (20/20) respectively. Sixty percent of Canadian academic EM sites reported using SBCPD, although only 30% reported dedicated funding support. Academic emergency physician responses demonstrated a median annual SBCPD of 3 hours. Reported incentivization for SBCPD participation varied with AEPs reporting less incentivization than DRs. Academic emergency physicians identified time commitments outside of shift, lack of opportunities, and lack of departmental funding as their top barriers to participation, whereas DRs thought AEPs fear of peer judgment and inexperience with simulation were substantial barriers. Content areas of interest for SBCPD were as follows: rare procedures, pediatric resuscitation, and neonatal resuscitation. Lastly, interprofessional involvement in SBCPD was valued by both DRs and AEPs. Conclusions: Simulation-based CPD programs are becoming common in Canadian academic EM sites. Our findings will guide program coordinators in addressing barriers to participation, selecting content, and determining the frequency of SBCPD events.

show abstract

Simulation-Based Evaluation of the Effects of Patient Load on Mental Workload of Healthcare Staff

Abstract: Based on this study, the researchers found that the modeled inpatient unit can safely handle the expected patient load increases. The study provides the unit with information to proactively prepare and reduce healthcare staff overloading.

Cited by 7 publications

References 3 publications

Designing optimal COVID-19 testing stations locally: A discrete event simulation model applied on a university campus

Designing optimal COVID-19 testing stations locally: A discrete event simulation model applied on a university campus

Carga mental en personal de enfermería: Una revisión integradora

Simulation in the Continuing Professional Development of Academic Emergency Physicians

Contact Info

Product

Resources

About