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.

No abstract

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.

No abstract

No abstract