Why Causal Inference Matters to Nurses: The Case of Nurse Staffing and Patient Outcomes

Abstract

Since the early 1990s researchers have steadily built a broad evidence base for the association between nurse staffing and patient outcomes. However, the majority of the studies in the literature employ designs that are unable to robustly examine causal pathways to meaningful improvement in patient outcomes. A focus on causal inference is essential to moving the field of nursing research forward, and as part of the essential skill-set for all nurses as consumers of research. In this article, we aim to describe the importance of causal inference in nursing research and discuss study designs that are more likely to produce causal findings. We first review the conceptual framework supporting this discussion and then use selected examples from the literature, typifying three key study designs – cross-sectional, longitudinal, and randomized control trials (RCTs). The discussion will illustrate strengths and limitation of existing evidence, focusing on the causal pathway between nurse staffing and outcomes. The article conclusion considers implications for future research.