Digital Training Recommendations for Enhancing Healthcare Human Resource Competence Using the Simple Additive Weighting Algorithm
DOI:
https://doi.org/10.47701/hr24wj75Keywords:
Digital Readiness, Healthcare Human Resources, Simple Additive Weighting (SAW), Digital Transformation, Training RecommendationsAbstract
The main challenge in digital transformation within the healthcare sector lies in the limited mapping of human resources’ (HR) readiness toward information technology.
This study aims to evaluate the digital readiness level of healthcare human resources using a data-driven approach. The Simple Additive Weighting (SAW) method was applied, utilizing six variables whose weights were determined through expert discussions.
The results show that respondents’ digital readiness scores range from 0.800 to 0.858. The highest score was achieved by R011 (Doctor, Outpatient Department) with a score of 0.858, indicating excellent digital literacy and effective utilization of information systems. A score of 0.828 was obtained by R032 (Medical Records Administration, ICU), R035 (Midwife, Polyclinic), and R025 (Doctor, Outpatient Department), suggesting relatively even readiness levels.
The lowest score, 0.800, belonged to R026 (Laboratory Analyst, Polyclinic), which still falls within the high-readiness category but indicates the need for improvement in health data analysis skills. The overall average score was 0.828, confirming that the majority of healthcare personnel demonstrate good digital readiness.
These findings highlight the effectiveness of the SAW method in providing data-driven recommendations for digital capacity development. Moreover, the results can serve as a foundation for designing more targeted and efficient training programs. Overall, this study demonstrates that SAW-based mapping can effectively support strategic decision-making in the digital transformation of healthcare services.
References
Aldhi, I. F., Suhariadi, F., Rahmawati, E., Supriharyanti, E., Hardaningtyas, D., Sugiarti, R., & Abbas, A. (2025). Bridging Digital Gaps in Smart City Governance: The Mediating Role of Managerial Digital Readiness and the Moderating Role of Digital Leadership. Smart Cities, 8(4), 117. https://doi.org/10.3390/smartcities8040117
Amri, M. M., & Abed, S. A. (2023). The Data-Driven Future of Healthcare: A Review. In Mesopotamian Journal of Big Data (Vol. 2023, pp. 68–74). Mesopotamian Academic Press. https://doi.org/10.58496/MJBD/2023/010
Bekele, T. A., Gezie, L. D., Willems, H., Metzger, J., Abere, B., Seyoum, B., Abraham, L., Wendrad, N., Meressa, S., Desta, B., & Bogale, T. N. (2024). Barriers and facilitators of the electronic medical record adoption among healthcare providers in Addis Ababa, Ethiopia. Digital Health, 10. https://doi.org/10.1177/20552076241301946
Feroz, A. S., Khoja, A., & Saleem, S. (2021). Equipping community health workers with digital tools for pandemic response in LMICs. In Archives of Public Health (Vol. 79, Issue 1). BioMed Central Ltd. https://doi.org/10.1186/s13690-020-00513-z
Ferreira, J. C., Elvas, L. B., Correia, R., & Mascarenhas, M. (2025). Empowering Health Professionals with Digital Skills to Improve Patient Care and Daily Workflows. Healthcare (Switzerland), 13(3). https://doi.org/10.3390/healthcare13030329
Galih Adi Nugraha, Wiji Lestari, & Agustina Srirahayu. (2025). Decision Support System for Selecting the Best Employee Using the Simple Additive Weighting Method. Bit-Tech, 8(1), 964–975. https://doi.org/10.32877/bt.v8i1.2788
Haakenstad, A., Irvine, C. M. S., Knight, M., Bintz, C., Aravkin, A. Y., Zheng, P., Gupta, V., Abrigo, M. R. M., Abushouk, A. I., Adebayo, O. M., Agarwal, G., Alahdab, F., Al-Aly, Z., Alam, K., Alanzi, T. M., Alcalde-Rabanal, J. E., Alipour, V., Alvis-Guzman, N., Amit, A. M. L., … Lozano, R. (2022). Measuring the availability of human resources for health and its relationship to universal health coverage for 204 countries and territories from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 399(10341), 2129–2154. https://doi.org/10.1016/S0140-6736(22)00532-3
Hannawa, A. F., Wu, A. W., Kolyada, A., Potemkina, A., & Donaldson, L. J. (2022). The aspects of healthcare quality that are important to health professionals and patients: A qualitative study. Patient Education and Counseling, 105(6), 1561–1570. https://doi.org/10.1016/j.pec.2021.10.016
Isidori, V., Diamanti, F., Gios, L., Malfatti, G., Perini, F., Nicolini, A., Longhini, J., Forti, S., Fraschini, F., Bizzarri, G., Brancorsini, S., & Gaudino, A. (2022). Digital Technologies and the Role of Health Care Professionals: Scoping Review Exploring Nurses’ Skills in the Digital Era and in the Light of the COVID-19 Pandemic. In JMIR Nursing (Vol. 5, Issue 1). JMIR Publications Inc. https://doi.org/10.2196/37631
Iyanna, S., Kaur, P., Ractham, P., Talwar, S., & Najmul Islam, A. K. M. (2022). Digital transformation of healthcare sector. What is impeding adoption and continued usage of technology-driven innovations by end-users? Journal of Business Research, 153, 150–161. https://doi.org/10.1016/j.jbusres.2022.08.007
Kaul, R., Ossai, C., Forkan, A. R. M., Jayaraman, P. P., Zelcer, J., Vaughan, S., & Wickramasinghe, N. (2023). The role of AI for developing digital twins in healthcare: The case of cancer care. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 13(1). https://doi.org/10.1002/widm.1480
Khan, R., Khan, S., Almohaimeed, H. M., Almars, A. I., & Pari, B. (2025). Utilization, challenges, and training needs of digital health technologies: Perspectives from healthcare professionals. International Journal of Medical Informatics, 197. https://doi.org/10.1016/j.ijmedinf.2025.105833
Månsson, J., Andersson, C., & Bonander, F. (2022). What lessons can be learned from cost efficiency? The case of Swedish district courts. European Journal of Law and Economics, 54(3), 431–451. https://doi.org/10.1007/s10657-022-09739-4
Martin-Sanchez, F., Lázaro, M., López-Otín, C., Andreu, A. L., Cigudosa, J. C., & Garcia-Barbero, M. (2023). Personalized Precision Medicine for Health Care Professionals: Development of a Competency Framework. JMIR Medical Education, 9. https://doi.org/10.2196/43656
Navarro-Martínez, O., Igual-García, J., & Traver-Salcedo, V. (2023). Bridging the educational gap in terms of digital competences between healthcare institutions’ demands and professionals’ needs. BMC Nursing, 22(1). https://doi.org/10.1186/s12912-023-01284-y
Poot, C. C., Meijer, E., Fokkema, M., Chavannes, N. H., Osborne, R. H., & Kayser, L. (2023). Translation, cultural adaptation and validity assessment of the Dutch version of the eHealth Literacy Questionnaire: a mixed-method approach. BMC Public Health, 23(1). https://doi.org/10.1186/s12889-023-15869-4
Sahal, R., Alsamhi, S. H., & Brown, K. N. (2022). Personal Digital Twin: A Close Look into the Present and a Step towards the Future of Personalised Healthcare Industry. Sensors, 22(15). https://doi.org/10.3390/s22155918
Seth, P., Hueppchen, N., Miller, S. D., Rudzicz, F., Ding, J., Parakh, K., & Record, J. D. (2023). Data Science as a Core Competency in Undergraduate Medical Education in the Age of Artificial Intelligence in Health Care. JMIR Medical Education, 9. https://doi.org/10.2196/46344
Van Dua, T. (2023). COMBINATION OF DESIGN OF EXPERIMENTS AND SIMPLE ADDITIVE WEIGHTING METHODS: A NEW METHOD FOR RAPID MULTI-CRITERIA DECISION MAKING. EUREKA, Physics and Engineering, 2023(1), 120–133. https://doi.org/10.21303/2461-4262.2023.002733
Zhang, M., & Wang, W. (2024). Research on the application effect of inter-professional training program for newly enrolled medical staff in operating room based on digital information technology. BMC Medical Education, 24(1). https://doi.org/10.1186/s12909-024-06256-7
