Chief Nurse Executive and VP Clinical Operations, Spectrum Health Hospitals

Dissertation Title

Difference in recommended-to-actual nurse staffing and patient falls

Dissertation Abstract

Patient falls are a serious safety concern in hospitals. Injuries from falls can be devastating to patients and are now subject to reimbursement penalties from the Center for Medicare and Medicaid Services. Patient falls have been identified by the American Nurses Association as a nursing sensitive indictor suggesting that improvements in the quality or quantity of nurses may impact this outcome. Moreover, the literature suggests that nurse staffing levels have an impact on various patient outcomes such as patient falls. Therefore, identifying appropriate nurse staffing levels to minimize patient falls is critically important to hospitals.

A variety of staffing metrics have been used to examine nurse staffing levels, however, they are often criticized because of the level of measurement. This study utilized a novel measure that examined the difference between recommended staffing and actual staffing levels, at the shift level, and its association with patient falls. The resource-based view of the firm served as the conceptual framework.

The hypotheses for this study posited that differences between recommended-to-actual staffing differences will increase the likelihood of patient falls. More specifically, understaffing will increase the likelihood of patient falls.

Two hospitals within a large health system in the Midwest served as the study sites, and all staffing and patient fall data were obtained from these organizations. Results demonstrated no statistical significance between understaffing, and patient falls when measured at the shift level.

This study is the first to examine nurse staffing and patient falls using the recommended-to-actual staffing metric at the shift level. As such, it provides a foundation on which subsequent research can be built. Additionally, nurses and nurse leaders may want to consider alternative interventions to reduce patient falls.