Abstract
In clinical nursing practice, it is crucial to share data overviews simply and intuitively with all team members. Descriptive statistics, typically expressed as the arithmetic mean plus-minus the standard deviation (Mean ± SD), are commonly used for this purpose. However, this approach is inadequate for describing asymmetric, right-skewed distributions, commonly encountered in nursing. This study introduces an alternative-the times-divide expression (GMean (×)/GSD)-based on the geometric mean and geometric standard deviation. We present a data-driven study that examines the applicability of this expression using nursing demand data collected over four and a half years from a nurse call system. The results indicate that the times-divide expression outperforms conventional methods in representing distributional properties and providing suitable representative values and usable percentile range indicators. Applying the times-divide expression to the actual distribution of data is expected to improve nurses' clinical decision-making skills through data-driven insights, ultimately enhancing the quality of care.