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Forecasting models for human resources in health care
Author(s) -
O’BrienPallas Linda,
Baumann Andrea,
Donner Gail,
Murphy Gail Tomblin,
LochhaasGerlach Jacquelyn,
Luba Marcia
Publication year - 2001
Publication title -
journal of advanced nursing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.948
H-Index - 155
eISSN - 1365-2648
pISSN - 0309-2402
DOI - 10.1046/j.1365-2648.2001.01645.x
Subject(s) - work (physics) , health care , demand forecasting , population , resource (disambiguation) , operations research , human resources , computer science , risk analysis (engineering) , actuarial science , economics , business , medicine , engineering , environmental health , mechanical engineering , computer network , management , economic growth
Forecasting models for human resources in health care This article is a review of the approaches published between 1996 and 1999 that have been used to forecast human resource requirements for nursing. Much of the work to date generally does not consider the complex factors that influence health human resources (HHR). They also do not consider the effect of HHR decisions on population health, provider outcomes such as stress, and the cost of a decision made. Supply and demand approaches have dominated. Forecasting is limited, too, by the availability of reliable and valid data bases for examining supply and use of nursing personnel across sectors. Three models – needs based, utilization based, and effective demand based – provide substantially different estimates of future HHR need. The methods of analysis employed for forecasting range from descriptive to predictive and are borrowed from demography, epidemiology, economics, and industrial engineering. Simulation models offer the most promise for the future. The forecasting methods described have demonstrated their accuracy and usefulness for specific situations, but none has proven accurate for long‐term forecasting or for estimating needs for large geographical areas or populations.