Background and Objectives: Human resources analytics in the health system is one of the key factors in improving the quality of health care services. Considering the complexities of this field and the need to optimize the processes, the validation of the analytical model can be an effective tool in improving the performance of the health system. Therefore, the present research was conducted with the aim of validating this model.
Materials and Methods: In this study, a descriptive survey method was used through a survey using a researcher-made questionnaire to validate the model of human resources analytics in the health system. Data were collected from 10 management and human resources specialists of Kerman University of Medical Sciences in 2024 and analyzed using content validity ratio (CVR) and content validity index (CVI).
Results: The findings indicated that the model of human resources analytics in the health system, which includes 24 sub-components in six components (central phenomenon, causal conditions, contextual conditions, intervening conditions, strategies, and consequences), is valid with average reliability ratio of 0.726 and reliability index of 0.848, and can be used in the design of the final model.
Conclusion: The results showed that the model of human resources analytics in the health system has a good content validity. This model helps to improve the efficiency and effectiveness of the health system, and its results can pave the way to enhance health system policies.
Keywords: Data analytics, Health workforce, Theoretical model, Validation study

Funding: This study did not have any funds.
Conflict of interest: None declared.
Ethical considerations: The Ethics Committee of Islamic Azad University, Kerman Branch, approved the study (IR.IAU.KERMAN.REC.1403.149).
Authors’ contributions:
- Conceptualization: Nahid Zarinsadaf, Mojgan Derakhshan, Amin Nikpour, Hamid Reza Mollaei
- Methodology: Mojgan Derakhshan, Nahid Zarinsadaf
- Data collection: Nahid Zarinsadaf
- Formal analysis: Nahid Zarinsadaf
- Supervision: Mojgan Derakhshan, Amin Nikpour, Hamid Reza Mollaei
- Project administration: Mojgan Derakhshan
- Writing - original draft: Nahid Zarinsadaf
- Writing - review and editing: Nahid Zarinsadaf, Mojgan Derakhshan, Amin Nikpour, Hamid Reza Mollaei