A New Dynamic Nursing Workforce Planning Considering Skills Required at the Different Organizational Hierarchy: An Optimal Control Method

Subject Areas : Business Strategy

Shila Monazam Ebrahimpour ¹ , Fariborz Rahimnia ² , Alireza pooya ³ , Mohammad Mahdi Farahi ⁴ , Morteza Pakdaman ⁵

1 - Ph.D. Graduated from Department of Management, Faculty of Economics & Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran
2 - Professor of Department of Management, Faculty of Economics & Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran
3 - Professor of Department of Management, Faculty of Economics & Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran
4 - Assistant Professor of Department of Management, Faculty of Economics & Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran
5 - Assistant Professor of Atmospheric Science and Meteorological Research Center (ASMERC), Atmospheric Science and Meteorological Research Center (ASMERC), Mashhad, Iran

Received: 2022-05-28 Accepted : 2022-09-11 Published : 2022-09-01

Keywords: Workforce’s flows, Hospital ward, Skill audit, Nursing workforce dynamic planning, Optimal Control,

Abstract :

As a vital practice in human resources management, workforce planning determines that the organization is needed how many workforces, when, and which position. Workforce planning is not formed in a vacuity, and job variables such as skill, ability, and knowledge affect the planning. This study examines workforce planning in the health sector concerning the workforce's flows such as recruitment, promotion, degradation, fired, retention, and termination of the contract according to the skill audit and the role of performance appraisal results in this program. For this purpose, a dynamic model has been applied that can provide optimal answers to the number of workforces required and the workforce's flows at any time during the planning periods. This model has been implemented in a hospital ward with two levels of hierarchy: nurses, supervisors, and nursing directors. The results show that the designed system can converge the existing values to the optimal values by noting delays by the optimal control model.

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