Developing a simulation tool to quantify biomechanical load and quality of care in nursing.

Nursing is a high musculoskeletal disorder (MSD) risk job with high workload demands. This study combines Digital Human Modelling (DHM) and Discrete Event Simulation (DES) to address the need for tools to better manage MSD risk. This novel approach quantifies physical-workload, work-performance, and quality-of-care, in response to varying geographical patient-bed assignments, patient-acuity levels, and nurse-patient ratios. Lumbar loads for 86 care-delivery tasks in an acute care hospital unit were used as inputs in a DES model of the care-delivery process, creating a shift-long time trace of the biomechanical load. Peak L4/L5 compression and moment were 3574 N and 111.58 Nm, respectively. This study reports trade-offs in all three experiments: (i) increasing geographical patient-bed assignment distance decreased L4/L5 compression (8.8%); (ii) increased patient-acuity decreased L4/L5 moment (4%); (iii) Increased nurse-patient ratio decreased L4/L5 compression (10%) and moment (17%). However, in all experiments, Quality of care indicators deteriorated (20, 19, and 29%, respectively).Practitioner Summary: This research has the potential to support decision-makers by developing a simulation tool that quantifies the impact of varying operational and design-policies in terms of biomechanical-load and quality of care. The demonstrator-model reports: as geographical patient-bed distance, patient-acuity levels, and nurse-patient ratios increase, biomechanical-load reduces, and quality of care deteriorates.

The barriers and opportunities to support the early career academics and professionals in human factors/ergonomics - revisiting reflections from IEA2015, IEA2018 & IEA2021.

BACKGROUND: The Early-Career Community (ECC) comprises researchers, practitioners, and professionals in their "early-career" stages in the Human Factors/Ergonomics (HFE) profession. Early-career HFE professionals are essential to both current industry decision making and future growth of our profession. OBJECTIVE: This paper provides detailed insights into the barriers and suggestions to support engagement with ECC within the International Ergonomics Association (IEA) and its Federated Societies. METHODS: This report integrates key findings from the formal and informal discussions that occurred with diverse groups of stakeholders (n > 100) at IEA2015, IEA2018 and IEA2021 guided by the participatory inquiry paradigm, cooperative action-inquiry and participatory ergonomics approaches. RESULTS: Barriers to support ECC include: a lack of employment opportunities, poor general awareness and integration of HFE in existing university-courses, financial constraints, inclusivity challenges and a lack of Influence in decision-making. While some of the more systemic challenges are context-specific and cannot be overcome, ECCs suggested that: the IEA and its Federated Societies include ECC members as part of their boards; a Standing Committee for the ECCs be established as part of the IEA; make use of social-media more effectively to engage the ECC. More mentorship, networking, knowledge sharing, training and education, combined with financial-support will ensure that the ECC can participate. CONCLUSION: ECC members experience complex and dynamic challenges that affect their development and involvement in the broader HFE profession. It is therefore critical that appropriate, global, national and local strategies are developed to continue to support and develop the ECC to ensure the continued growth of and demand for HFE.

Modelling the impacts of COVID-19 on nurse workload and quality of care using process simulation.

Higher acuity levels in COVID-19 patients and increased infection prevention and control routines have increased the work demands on nurses. To understand and quantify these changes, discrete event simulation (DES) was used to quantify the effects of varying the number of COVID-19 patient assignments on nurse workload and quality of care. Model testing was based on the usual nurse-patient ratio of 1:5 while varying the number of COVID-19 positive patients from 0 to 5. The model was validated by comparing outcomes to a step counter field study test with eight nurses. The DES model showed that nurse workload increased, and the quality of care deteriorated as nurses were assigned more COVID-19 positive patients. With five COVID-19 positive patients, the most demanding condition, the simulant-nurse donned and doffed personal protective equipment (PPE) 106 times a shift, totaling 6.1 hours. Direct care time was reduced to 3.4 hours (-64% change from baseline pre-pandemic case). In addition, nurses walked 10.5km (+46% increase from base pre-pandemic conditions) per shift while 75 care tasks (+242%), on average, were in the task queue. This contributed to 143 missed care tasks (+353% increase from base pre-pandemic conditions), equivalent to 9.6 hours (+311%) of missed care time and care task waiting time increased to 1.2 hours (+70%), in comparison to baseline (pre-pandemic) conditions. This process simulation approach may be used as potential decision support tools in the design and management of hospitals in-patient care settings, including pandemic planning scenarios.

Predicting the effect of nurse-patient ratio on nurse workload and care quality using discrete event simulation.

AIM: A novel nurse-focused discrete event simulation modelling approach was tested to predict nurse workload and care quality. BACKGROUND: It can be challenging for hospital managers to quantify the impact of changing operational policy and technical design such as nurse-patient ratios on nurse workload and care quality. Planning tools are needed-discrete event simulation is a potential solution. METHOD: Using discrete event simulation, a demonstrator "Simulated Care Delivery Unit" model was created to predict the effects of varying nurse-patient ratios. Modelling inputs included the following: patient care data (GRASP systems data), inpatient unit floor plan and operating logic. Model outputs included the following: nurse workload in terms of task-in-queue, cumulative distance walked and Care quality in terms of task in queue time, missed care. RESULTS: The model demonstrated that as NPR increases, care quality deteriorated (120% missed care; 20% task-in-queue time) and nursing workload increased (120% task-in-queue; 110% cumulative walking distance). CONCLUSIONS: DES has the potential to be used to inform operational policy and technical design decisions, in terms of impacts on nurse workload and care quality. IMPLICATIONS FOR NURSING MANAGEMENT: This research offers the ability to quantify the impacts of proposed policy changes and technical design decisions, and provide a more cost-effective and safe alternative to the current trial and error methodologies.