{Reference Type}: Journal Article
{Title}: Forecast accuracy of demand for registered nurses and its determinants in South Korea.
{Author}: Jeong S;
{Journal}: Hum Resour Health
{Volume}: 22
{Issue}: 1
{Year}: 2024 Jun 25
{Factor}: 4.837
{DOI}: 10.1186/s12960-024-00910-3
{Abstract}: <B>BACKGROUND: </B>Despite the significance of demand forecasting accuracy for the registered nurse (RN) workforce, few studies have evaluated past forecasts.<BR><B>OBJECTIVE: </B>This paper examined the ex post accuracy of past forecasting studies focusing on RN demand and explored its determinants on the accuracy of demand forecasts.<BR><B>METHODS: </B>Data were collected by systematically reviewing national reports or articles on RN demand forecasts. The mean absolute percentage error (MAPE) was measured for forecasting error by comparing the forecast with the actual demand (employed RNs). Nonparametric tests, the Mann‒Whitney test, and the Kruskal‒Wallis test were used to analyze the differences in the MAPE according to the variables, which are methodological and researcher factors.<BR><B>RESULTS: </B>A total of 105 forecast horizons and 196 forecasts were analyzed. The average MAPE of the total forecast horizon was 34.8%. Among the methodological factors, the most common determinant affecting forecast accuracy was the RN productivity assumption. The longer the length of the forecast horizon was, the greater the MAPE was. The longer the length of the data period was, the greater the MAPE was. Moreover, there was no significant difference among the researchers' factors.<BR><B>CONCLUSIONS: </B>To improve demand forecast accuracy, future studies need to accurately measure RN workload and productivity in a manner consistent with the real world.