ArticleHuman resources for health2024
Forecast accuracy of demand for registered nurses and its determinants in South Korea.
Article in Human resources for health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Utilizing and Optimizing Forecasting Models for Nursing Demand: A Narrative Review.Health science reports · 2026Article
- Comparison of basic and specialized care between nursing assistants and professional nurses.Revista CuidarteArticle
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDespite the significance of demand forecasting accuracy for the registered nurse (RN) workforce, few studies have evaluated past forecasts. PURPOSE: 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.
methodsData 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.
resultsA 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.
conclusionsTo improve demand forecast accuracy, future studies need to accurately measure RN workload and productivity in a manner consistent with the real world.
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