Outflow model of nurses in Iran and the intention to leave among Iranian nurses

Neurological Disorders

ISSN: 2329-6895

Open Access

Outflow model of nurses in Iran and the intention to leave among Iranian nurses

Samira Alirezaei

Ministry of Health and Medical Education, Iran

Posters & Accepted Abstracts: J Neurol Disord

Abstract :

Introduction & Objective: Nurses are the biggest professional workforce at a hospital and they have become a key factor in improving productivity and competitiveness of hospitals. In healthcare industry, the attrition rate of nurses has been the highest among all employee categories. The objective of this study is to estimate the rate of nurses’ loss in Iran and to provide a model for representing the types of nursing outflows and the probability of occurrence of each of these currents in nurses according to the desired conditions and characteristics.

Method: Data mining was used for research purposes. In order to assess the status of nurses in Iran, the Nursing graduates were used by the Ministry of Health for the last five years. Sampling from this bank was done using Cochran's formula of 500 students randomly. It should be noted that at this stage, the research sample was examined for persistence in nursing or abandoned work also, from the sample. The amount of inclination to quit was questioned. Finally, using Clementine software analysis and modeling was done.

Results: The findings of this study showed that most of the nurses were female (63.6%), married (63.1%), undergraduate education (56.6%). Of the 500 nurses, 352 nurses left their job and 148 nurses were engaged in their work. Immigration of nurses (33.1%) had the highest outflow rate among Iranian nurses and after that; the change of field with the frequency of 15% was the highest nurses’ abandonment rate.

Conclusion: Interventions to enhance participation in hospital affairs, adequacy of staffing and resources and enabling and supporting behaviors and creating opportunities for growth and professional development could be beneficial for a stable nursing workforce. It is essential at to promote nurses’ motivation for work, such as the law on productivity promotion and the law on tariffs for nursing services.

Biography :



Google Scholar citation report
Citations: 1253

Neurological Disorders received 1253 citations as per Google Scholar report

Neurological Disorders peer review process verified at publons

Indexed In

arrow_upward arrow_upward