Assessing the Relationship Between Staffing Levels and Patient Mortality Rates in Critical Care Units

Posted: Feb 09, 2023

• Christian Evans
• Christopher Price
• Claire Cook

Abstract

The relationship between healthcare staffing levels and patient outcomes represents one of the most critical yet complex challenges in modern healthcare delivery. While numerous studies have established correlations between nurse-to-patient ratios and various quality indicators, the underlying mechanisms and precise nature of these relationships remain inadequately understood. Traditional statistical approaches have predominantly relied on linear models that assume straightforward, proportional relationships between staffing variables and patient outcomes. However, the dynamic, multi-faceted nature of critical care environments suggests that these relationships are likely characterized by non-linearities, threshold effects, and complex interactions that conventional methodologies fail to capture. Our research addresses these limitations through the development of a novel computational framework that integrates multiple methodological approaches to examine staffing-outcome relationships in critical care. We move beyond traditional correlation analyses by employing a hybrid methodology that combines temporal pattern recognition with multi-agent simulation modeling. This approach allows us to capture the dynamic interactions between staffing variables, care processes, and patient outcomes in ways that conventional statistical methods cannot.