Using data to drive programmatic change: Recalculating NCLEX-RN success

Nursing schools admit students who are highly qualified using a variety of admission criteria. Even when picking top achievers, it does not guarantee NCLEX-RN success. Nursing programs too often maintain outdated or unvalidated admission processes. Using data to drive decision-making takes time, but improvement processes like the Plan-Do-Study-Act model can make it more achievable.

The purpose of the quality improvement project was to examine a variety of variables readily available to most programs and examine which variables correlated with and predicted the outcome of interest, first-time NCLEX-RN pass success.

The quality improvement project used a retrospective quantitative descriptive design to compare pre-admission criteria, demographic variables, Kaplan exam scores, and nursing program course failures with NCLEX-RN first attempt pass rates for four cohorts of traditional BSN students at a public, regional university of approximately 10,000 students situated in the western U.S. serving largely rural counties.

Course failure while in nursing school was the strongest predictor of NCLEX-RN first-time failure. Pre-nursing school GPA and pre-admission overall Kaplan scores were statistically significant predictors, with pre-nursing school GPA accounting for greater variance in NCLEX-RN first-time failure rates.

A full review of program data is needed for transformational action and changes to occur, moving programs past fleeting change that does not essentially "move the needle."