Journal List > Perspect Nurs Sci > v.13(2) > 1060423

Perspect Nurs Sci. 2016 Oct;13(2):81-87. Korean.
Published online October 31, 2016.  https://doi.org/10.16952/pns.2016.13.2.81
© 2016 The Research Institute of Nursing Science Seoul National University
A Critical Review of Nurse Demand Forecasting Methods in Empirical Studies 1991~2014
Suyong Jeong,1 and Jinhyun Kim2
1Graduate Student, College of Nursing, Seoul National University, Seoul, Korea.
2Professor, College of Nursing, Seoul National University, Seoul, Korea.

Corresponding author: Kim, Jinhyun. College of Nursing, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul 03080, Korea. Tel: +82-2-740-8818, Fax: +82-2-766-1852, Email: jinhyun@snu.ac.kr
Received August 11, 2016; Revised August 30, 2016; Accepted August 30, 2016.

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.


Abstract

Purpose

The aim of this study is to review the nurse demand forecasting methods in empirical studies published during 1991~2014 and suggest ideas to improve the validity in nurse demand forecasting.

Methods

Previous studies on nurse demand forecasting methodology were categorized into four groups: time series analysis, top-down approach of workforce requirement, bottom-up approach of workforce requirement, and labor market analysis. Major methodological properties of each group were summarized and compared.

Results

Time series analysis and top-down approach were the most frequently used forecasting methodologies.

Conclusion

To improve decision-making in nursing workforce planning, stakeholders should consider a variety of demand forecasting methods and appraise the validity of forecasting nurse demand.

Keywords: Nurse demand; Nursing workforce; Nurse demand forecasting; Demand for nurse

Tables


Table 1
Methodological Characteristics in Nurse Demand Forecasting Studies
Click for larger image

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