Building a Better Staffing Model: Using Predictive Workload Analysis for Biomedical Technician Staffing

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Abstract

A model was built using data from the Department of Veterans Affairs (VA), to predict frontline staffing using predictive workload analysis. This model attempts to improve on previous models that utilized the number of medical devices and medical equipment asset value. The predictive workload model is, on average, within 0.6 full-time equivalent of the ideal staffing levels obtained from experienced clinical engineers at 5 VA medical centers. This average deviation is an improvement over the deviations resulting from previous staffing models. There are still limitations to this model, including applicability to facilities outside the VA and scalability at small facilities.

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