Narrative Review: Optimization of AI-Based HR Management System for Remuneration and Performance Equity in Hospitals
Abstract
Human resource management (HRM) in Indonesian hospitals faces significant challenges in ensuring fairness, transparency and objectivity in performance evaluation and remuneration systems. These issues contribute to income disparities between medical and managerial staff, leading to lowered morale and reduced quality of healthcare services. This study aims to provide an existing performance appraisal system, identify remuneration inequities, and propose an AI-based meritocracy model to improve transparency and accountability. Through a systematic literature review of global and local sources, the study identifies objective key performance indicators (KPIs) and develops an AI-based conceptual framework for equitable distribution of remuneration, drawing on successful practices from countries such as the UK and Singapore. The proposed model integrates AI technologies such as machine learning and predictive analytics to optimize recruitment, performance monitoring and incentive allocation while addressing ethical concerns such as algorithmic bias and data privacy. This AI-based approach aims to increase healthcare worker motivation, reduce turnover, and improve service quality in Indonesian hospitals, with recommendations for phased implementation and strong governance to ensure ethical implementation.
References
Abu Jaber, A. A., & Nashwan, A. J. (2022). Balanced Scorecard-Based Hospital Performance Measurement Framework: A Performance Construct Development Approach. Cureus, 14(5). https://doi.org/10.7759/cureus.24866
Agrawal, A., Gans, J. S., & Goldfarb, A. (2023). Do we want less automation? Science, 381, 155–158. https://doi.org/https://doi.org/10.1126/science.adh9429
Aini, Q., Rusilowati, U., Asfi, M., Sunarya, P. A., Putra, S. N. W., & Zahra, A. R. A. (2024). Aini, Q., Rusilowati, U., Asfi, M., Sunarya, P. A., Putra, S. N. W., & Zahra, A. R. A. Assessing the Influence of Artificial Intelligence on Human Resource Management Practices., 1–. https://doi.org/https://doi.org/10.1109/iccit62134.2024.10701
Budiarto, S. W., & Ridwan, S. (2024). Pengembangan Remunerasi Berbasis Aplikasidalam Upaya Meningkatkan Kinerja Pegawai ( Studi Kasus Pada Pusat Mata Nasional Rumah Sakit Mata Cicendo Bandung ). 2(3), 203–210.
Carayon P, Wetterneck TB, Rivera-Rodriguez AJ, Hundt AS, Hoonakker P, Holden R, G. A. (2014). Human factors systems approach to healthcare quality and patient safety. 45(1), 14–25. https://doi.org/https://doi.org/10.1016/j.apergo.2013.04.023
Chen, Q., Chen, J., Li, Y., & Xu, F. (2010). Design and implement of performance management system for hospital staff based on BSC. International Conference on Networking, 1, 530–533. https://doi.org/https://doi.org/10.1109/ICNDS.2010.5479261
Cheng, C., Luo, J., Zhu, C., & Zhang, S. (2024). Artificial intelligence and the skill premium: A numerical analysis of theoretical models. Technological Forecasting and Social Change, 200(January), 123140. https://doi.org/10.1016/j.techfore.2023.123140
Darmizal, T. (2024). Design and Development Performance Assessment System for Medical Staff Implementing the Regulations of the Indonesian Ministry of Health ( Case Study : Arifin Achmad General Hospital , Riau Province ). 09(12), 5805–5810. https://doi.org/10.47191/etj/v9i12.32
Dwianto, A. S., & Kusuma, S. (2024). Artificial Intelligence in Performance Evaluation ( Case Study of PT . Pos Indonesia Employees ). 7(2). https://doi.org/10.32877/bt.v7i2.1817
Greatavia Meanda Leslie, Afrah Monirah Zebua, Sintha Abilia Puji Winata, D., & Herryanto, M. Alif Zayyan, V. P. (2025). Analisis Strategi Pengelolaan Sumber Daya Manusia Di Rumah Sakit Untuk Meningkatkan Kinerja Pelayanan Kesehatan. 4(4), 116–124.
Hendryani, A. (2017). Rancang Bangun Sistem Informasi Remunerasi Jasa Pelayanan RSUD Kepahiang Bengkulu Menggunakan Metode FAST. Jurnal Sistem Informasi Bisnis, 7(1), 9. https://doi.org/10.21456/vol7iss1pp9-16
Joshi, A., Singh, R., & Rani, S. (2024). Strategic Adoption of Artificial Intelligence for Human Resource Management Practices Transforming Healthcare Sector. The International Journal of Education Management and Sociology, 3(3), 151–163. https://doi.org/10.58818/ijems.v3i3.133
Koleangan, P. J. ., Robert, Purwadhi, & Restiani Widjaja, Y. (2024). Penerapan Artificial Intelligence dalam Manajemen SDM di Rumah Sakit: Tinjauan Literatur tentang Inovasi dan Etika. Mufakat: Jurnal Ekonomi, Manajemen Dan Akuntansi , 3(1), 435–438. http://jurnal.anfa.co.id/index.php/mufakat
Kuźniarska, A., & Stańczyk, P. (2024). Artificial intelligence in recruitment: Reducing human bias through automated screening. Journal of Human Resource Analytics, 15(1), 34–48.
Liang, Y. (2024). The Impact of Artificial Intelligence on Employment and Income Distribution. Journal of Education, Humanities and Social Sciences. https://doi.org/https://doi.org/10.54097/2a7a8830
Liu, Y. (2024). Exploring The Impact Path of Artificial Intelligence Development on Income Distribution Equity. 45, 590–596.
Manoharan, T., & Rajoli, R. (2024). ). Artificial intelligence in human resource practices: Fostering transparency and fairness in compensation systems. Journal of Human Resource Technology, 12(1), 45–59.
Monica, M., Patel, S., Ramanaiah, G., Manoharan, S. K., & Taufiq-Hail, G. A.-M. (2024). Promoting Fairness and Ethical Practices in AI-Based Performance Management Systems. Advances in Computational Intelligence and Robotics Book Series, 155–178. https://doi.org/https://doi.org/10.4018/979-8-3693-5380-6
Niaksu, O., & Zaptorius, J. (2014). Applying operational research and data mining to performance based medical personnel motivation system. Studies in Health Technology and Informatics, 198, 63–70. https://doi.org/10.3233/978-1-61499-397-1-63
Nyathani, R. (2023). AI in Performance Management: Redefining Performance Appraisals in the Digital Age. Journal of Artificial Intelligence & Cloud Computing, 2023(December), 1–5. https://doi.org/10.47363/jaicc/2023(2)134
Pourmohammadi, K., Hatam, N., Shojaei, P., & Bastani, P. (2018). A comprehensive map of the evidence on the performance evaluation indicators of public hospitals: A scoping study and best fit framework synthesis. Cost Effectiveness and Resource Allocation, 16(1). https://doi.org/10.1186/s12962-018-0166-z
Rahmadani, R., Safitri, D., & Hartono, B. (2024). Pengaruh Remunerasi terhadap Motivasi Kerja Pegawai Rumah Sakit : Literatur Review. 4.
Repullo Labrador, J. R., & Freire Campo, J. M. (2024). Pay for performance in public directly managed healthcare centers. Part 1: General framework. SESPAS Report 2024. Gaceta Sanitaria, 38, 102367. https://doi.org/10.1016/j.gaceta.2024.102367
Sampath, K., Devi, K., Ambuli, T. V., & Venkatesan, S. (2024). AI-Powered Employee Performance Evaluation Systems in HR Management. Proceedings of International Conference on Circuit Power and Computing Technologies, ICCPCT 2024, 1(November), 703–708. https://doi.org/10.1109/ICCPCT61902.2024.10673159
Shah, S. K. A., Ali, Z., & Tariq, M. (2024). The Impact of Unfair Compensation on Employee Morale, Job Satisfaction, and Performance: A Quantitative Analysis in Pakistan’s Health Sector. Global Management Sciences Review, IX(III), 65–76. https://doi.org/https://doi.org/10.31703/gmsr.2024(ix-iii).06
Shouran, Z., & Ali, D. A. (2024). The Implementation of Artificial Intelligence in Human Resources Management. Journal of International Conference Proceedings, 7(1), 244–258. https://doi.org/10.32535/jicp.v7i1.2993
Suhrab, M., Pinglu, C., Rădulescu, M., Soomro, J. A., & Dalal, S. (2024). No Title. Chapter 10 The Impact of AI and Automation on Income Inequality in BRICS Countries and the Role of Structural Factors and Women’s Empowerment., 155–176. https://doi.org/https://doi.org/10.1515/9783111354842-010/
Law of the Republic of Indonesia Number 27 of 2022 concerning Personal Data Protection. (2022). State Gazette of the Republic of Indonesia Year 2022, Number 196.
Venugopal, R., Sharma, N., & Iyer, P. (2024). Enhancing recruitment decisions with AI-driven candidate screening tools. International Journal of Recruitment Technology, 9(2), 112–128.
Zhao, S., Gu, Y., & Huang, Z. (2022). Building a Performance Management System for Hospitals Based on Diagnosis-Related Group (DRG) Payment. Journal of Sensors, 2022, 1–10. https://doi.org/10.1155/2022/7001423
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