Development of a Methodology for Healthcare System Simulations to Quantify Nurse Workload and Quality of Care

OCCUPATIONAL APPLICATIONS Intensive workload for nurses due to high demands directly impacts the quality of care and nurses' health. To better manage workload, it is necessary to understand the drivers of workload. This report provides an adaptable modeling approach that can isolate and quantify the effects of changing technical design and operational policies in terms of nurse workload and quality of care. A demonstrator model is presented that tested two known drivers of workload: nurse-patient ratio and patient acuity. The results revealed that when nurse-patient ratios and patient acuity levels increased, nurse workload increased and quality of care deteriorated. This adaptable modeling approach can assist policymakers in quantifying the consequences of technical design and policy tradeoffs; architects in better designing inpatient unit-layouts; and hospital managers in creating safer work environments for nurses by quantifying their workload demands proactively. This modeling tool also offers a cost effective and safer alternative to trial-and-error methodologies. TECHNICAL ABSTRACT Background: Nursing is a high-risk job that is associated with high workload. Evidence suggests that increased workload compromises the wellbeing of nurses and the safety of patients. A tool is needed that can better manage workload, by proactively assessing polices before they are implemented. Purpose: An adaptable, nurse-focused approach to Discrete Event Simulation (DES) modeling was tested to create a demonstration model (Simulated Care-Delivery Unit) that can quantify the effects of varying patient acuity and nurse-patient ratios on nurse workload and quality of care. Methods: Inputs to this demonstration model included: historical patient care data, an inpatient unit floor plan, and the operating logic. The model was run on a combination of seven different nurse-patient ratios and five patient-acuity levels. Outputs for care quality included: missed-care, missed-care delivery time, care-delivery time. Nurse-Workload was quantified using cumulative walking distance and number of tasks-in-queue. Results: As nurse-patient ratios and patient acuity increased, nurse workload increased and care quality deteriorated. Compared to a baseline case, cumulative walking distance increased up to 22%; task in queue up to 439%, missed care up-to 323%; missed-care delivery time up to 386%, and care delivery time up to 40%. Statistically significant differences were found for all indicators of nurse workload and quality of care. Further, regression equations are presented for the each of the indicators of nurse workload and quality of care. Conclusion: A nurse-focused approach to DES modeling successfully quantified the effects of changing nurse-patient ratio and patient acuity on nurse workload and quality of care. This adaptable approach can assist decision makers by providing proactive insights into the potential impact of these decisions on nurse workload and quality of care, thereby assisting decision makers in creating technical design and operational policies for hospital units that do not compromise patient safety and nurse health.