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Predicting the effect of nurse-patient ratio on nurse workload and care quality using discrete event simulation
Sadeem Munawar Qureshi1, Nancy Purdy2, Asad Mohani1
1Human Factors Engineering Lab, Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, Ontario, Canada.
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.
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