Transformasi Artificial Intelligence dalam Sistem Pelayanan Kesehatan Primer-Sekunder Daerah

Kajian Pemodelan Value Organisasi, Sumber Daya Manusia Kesehatan dan Sistem Kesehatan Daerah

Authors

  • Rafialdo Arifian Departemen Kebijakan dan Manajemen Kesehatan, Universitas Gadjah Mada, Yogyakarta, Indonesia

DOI:

https://doi.org/10.70260/nij.v3i2.66

Keywords:

Artificial Intelligence, Digital Health Transformation, Health Centers, Health Workers, Regional Health Systems

Abstract

Artificial Intelligence (AI) transformation in primary and secondary health care systems in regions presents significant potential for enhancing efficiency, accessibility, and quality of services. This study examines the strategic transformation of artificial intelligence (AI) in primary and secondary health care systems in various regions through a multidisciplinary approach that encompasses organizational values, health human resources, and regional health policies and systems. A systematic literature review method, guided by the PRISMA approach and thematic-inductive analysis, is employed to assess the impact of AI on institutional readiness, health worker capacity, and policy formulation from the district/city to provincial levels. Literature from 2018 to 2024 is analyzed using VOSviewer software to visualize the relationships between concepts and develop an integrative conceptual framework. The study’s results indicate that effective AI transformation requires strategic leadership, organizational digital maturity, and a roadmap aligned with the institution’s vision. In primary care (Puskesmas), AI contributes to improved early detection, supports clinical decisions, and automates administrative services. In secondary care (RSUD), AI facilitates medical imaging diagnosis, optimizes referral systems, and manages chronic diseases. Nevertheless, challenges such as limited digital infrastructure, a shortage of skilled human resources, and institutional resistance pose significant obstacles. Successful adoption necessitates leadership capable of managing change, fostering cross-sector collaboration, and formulating contextual policies. Regarding human resources, digital literacy and technology acceptance are crucial factors. Structured training tailored to local needs, ongoing education, and digital competency certification are essential for cultivating adaptive human resources. Meanwhile, policy interventions should ensure the provision of infrastructure, data interoperability, and sustainable financing schemes, including public-private partnerships. AI is more than just a technological tool; it serves as a strategic lever to create more equitable, efficient, and data-driven health services at the local level. A holistic and adaptive approach is essential for the success of this transformation

References

Achoki, T., & Lesego, A. (2017). The imperative for systems thinking to promote access to medicines, efficient delivery, and cost-effectiveness when implementing health financing reforms: a qualitative study. International Journal for Equity in Health, 16(1), 53. https://doi.org/10.1186/s12939-017-0550-x

Adel, H. M., Khaled, M., Yehya, M. A., Elsayed, R., Ali, R. S., & Ahmed, F. E. (2024). Nexus among artificial intelligence implementation, healthcare social innovation, and green image of hospitals’ operations management in Egypt. Cleaner Logistics and Supply Chain, 11. https://doi.org/10.1016/j.clscn.2024.100156

Alfi, M., Yundari, N. P., & Tsaqif, A. (2023). Analisis Risiko Keamanan Siber dalam Transformasi Digital Pelayanan Publik di Indonesia. Jurnal Kajian Stratejik Ketahanan Nasional, 6(2), 5.

Androulakis, I. P. (2019). The quest for digital health: From diseases to patients. Computers and Chemical Engineering, 127, 247–253. https://doi.org/10.1016/j.compchemeng.2019.05.030

Arruda, H., Silva, E. R., Lessa, M., Proença Jr., D., & Bartholo, R. (2022). VOSviewer and Bibliometrix. Journal of the Medical Library Association, 110(3), 392–395. https://doi.org/10.5195/jmla.2022.1434

Atmaja, S. (2024). Pemanfaatan artificial intelligence (AI) dalam transformasi digital untuk pelayanan publik. Jurnal Manajemen Dan Bisnis, 6(1), 9–21.

Azzopardi-Muscat, N., & Sørensen, K. (2019). Towards an equitable digital public health era: promoting equity through a health literacy perspective. European Journal of Public Health, 29(Supplement_3), 13–17. https://doi.org/10.1093/eurpub/ckz166

Back, D. A., Scherer, J., Osterhoff, G., Rigamonti, L., & Pförringer, D. (2022). Digital implications for human resource management in surgical departments. European Surgery - Acta Chirurgica Austriaca, 54(1), 17–23. https://doi.org/10.1007/s10353-021-00709-9

Bellucci, B., & Michele, E. (2023). Focusing on the integration of AI in healthcare sector of USA: Focusing on the roles of AI adoption and innovative capabilities. Journal of Commercial Biotechnology, 28(5), 205–216. https://doi.org/10.5912/jcb2142

Bhattacharyya, D. S., Dutta, G. K., Nowrin, I., Shafique, S., Islam, M. Z., Riazul Islam, B. M., & Anwar, I. (2021). Implementing a digital human resources management tool in the government health sector in Bangladesh: a policy content analysis. BMC Health Services Research, 21(1). https://doi.org/10.1186/s12913-021-07304-4

Bhattacharyya, D. S., Shafique, S., Akhter, S., Rahman, A., Islam, M. Z., Rahman, N., & Anwar, I. (2020). Challenges and facilitators of implementation of an information communication and technology (ICT)-based human resources management tool in the government health sector in Bangladesh: Protocol for an exploratory qualitative research study. BMJ Open, 10(12). https://doi.org/10.1136/bmjopen-2020-043939

Bhuyan, S. S., Sateesh, V., Mukul, N., Galvankar, A., Mahmood, A., Nauman, M., Rai, A., Bordoloi, K., Basu, U., & Samuel, J. (2025). Generative Artificial Intelligence Use in Healthcare: Opportunities for Clinical Excellence and Administrative Efficiency. Journal of Medical Systems, 49(1). https://doi.org/10.1007/s10916-024-02136-1

Bywall, K. S., Norgren, T., Avagnina, B., Gonzalez, M. P., & Andersson, S. W. (2024). Calling for allied efforts to strengthen digital health literacy in Sweden: perspectives of policy makers. BMC Public Health, 24(1). https://doi.org/10.1186/s12889-024-20174-9

Cahyarini, F. D. (2021). Implementasi digital leadership dalam pengembangan kompetensi digital pada pelayanan publik. Jurnal Studi Komunikasi Dan Media, 25(1), 47–60.

Carse, J., Süveges, T., Chin, G., Muthiah, S., Morton, C., Proby, C., Trucco, E., Fleming, C., & McKenna, S. (2024). Classifying real-world macroscopic images in the primary-secondary care interface using transfer learning: implications for development of artificial intelligence solutions using nondermoscopic images. Clinical and Experimental Dermatology, 49(7), 699– 706. https://doi.org/10.1093/ced/llad400

Chatterjee, S., Chaudhuri, R., Thrassou, A., & Vrontis, D. (2022). Technology disruption in healthcare: artificial intelligence application, challenges, and policy recommendations in India. International Journal of Internet Marketing and Advertising, 17(3–4), 394–414. https://doi.org/10.1504/IJIMA.2022.126716

Cheng, M., Li, X., & Xu, J. (2022). Promoting Healthcare Workers’ Adoption Intention of Artificial- Intelligence-Assisted Diagnosis and Treatment: The Chain Mediation of Social Influence and Human–Computer Trust. International Journal of Environmental Research and Public Health,19(20). https://doi.org/10.3390/ijerph192013311

Choi, K.-S. (2020). Integrating artificial intelligence into healthcare research. Journal of Nursing, 67(5), 12–18. https://doi.org/10.6224/JN.202010_67(5).03

Chung, Y., Shin, H., Kim, H., & Kim, J.-S. (2024). The Role of Health Empowerment on Digital Health Technology Literacy by Generation. American Journal of Health Behavior, 48(4), 91–102. https://doi.org/10.5993/AJHB.48.4.8

Clement, N. D., & Simpson, A. H. R. W. (2023). Artificial intelligence in orthopaedics. Bone and Joint Research, 12(8), 494–496. https://doi.org/10.1302/2046-3758.128.BJR2023-0199

Clifford, K. L., & Zaman, M. H. (2016). Engineering, global health, and inclusive innovation: Focus on partnership, system strengthening, and local impact for SDGs. Global Health Action, 9(1). https://doi.org/10.3402/gha.v9.30175

Cobianchi, L., Verde, J. M., Loftus, T. J., Piccolo, D., Dal Mas, F., Mascagni, P., Garcia Vazquez, A., Ansaloni, L., Marseglia, G. R., Massaro, M., Gallix, B., Padoy, N., Peter, A., & Kaafarani, H. M. (2022). Artificial Intelligence and Surgery: Ethical Dilemmas and Open Issues. Journal of the American College of Surgeons, 235(2), 268–275. https://doi.org/10.1097/XCS.0000000000000242

Daeli, S. M. S., Girsang, E., & Ramadhani, S. L. (2023). Evaluation of government sourcing health financing with district health account (DHA) approach in the health office of West Nias. 080015. https://doi.org/10.1063/5.0144396

Dal Mas, F., Massaro, M., Rippa, P., & Secundo, G. (2023). The challenges of digital transformation in healthcare: An interdisciplinary literature review, framework, and future research agenda. Technovation, 123. https://doi.org/10.1016/j.technovation.2023.102716

Darwiesh, A., El-Baz, A. H., Abualkishik, A. Z., & Elhoseny, M. (2023). Artificial Intelligence Model for Risk Management in Healthcare Institutions: Towards Sustainable Development. Sustainability (Switzerland), 15(1). https://doi.org/10.3390/su15010420

De Foo, C., Verma, M., Tan, S. Y., Hamer, J., van der Mark, N., Pholpark, A., Hanvoravongchai, P., Cheh, P. L. J., Marthias, T., Mahendradhata, Y., Putri, L. P., Hafidz, F., Giang, K. B., Khuc, T. H. H., Van Minh, H., Wu, S., Caamal-Olvera, C. G., Orive, G., Wang, H., … Legido-Quigley, H. (2023). Health financing policies during the COVID-19 pandemic and implications for universal health care: a case study of 15 countries. The Lancet Global Health, 11(12), e1964– e1977. https://doi.org/10.1016/S2214-109X(23)00448-5

Denicolai, S., & Previtali, P. (2023). Innovation strategy and digital transformation execution in healthcare: The role of the general manager. Technovation, 121. https://doi.org/10.1016/j.technovation.2022.102555

Dicuonzo, G., Donofrio, F., Fusco, A., & Shini, M. (2023). Healthcare system: Moving forward with artificial intelligence. Technovation, 120. https://doi.org/10.1016/j.technovation.2022.102510

Ejaz, H., McGrath, H., Wong, B. L. H., Guise, A., Vercauteren, T., & Shapey, J. (2022). Artificial intelligence and medical education: A global mixed-methods study of medical students’ perspectives. Digital Health, 8. https://doi.org/10.1177/20552076221089099

Farooqui, M. O., Qureshi, T., Kisswani, N., & Mishra, D. K. (2024). Artificial Intelligence: Legal and Ethical Perspectives in the Health Care Sector. Science of Law, 2024(4), 8–14. https://doi.org/10.55284/sol.v2024i4.152

Gastaldi, L., Appio, F. P., Corso, M., & Pistorio, A. (2018). Managing the exploration-exploitation paradox in healthcare: Three complementary paths to leverage on the digital transformation. Business Process Management Journal, 24(5), 1200–1234. https://doi.org/10.1108/BPMJ-04-2017-0092

Ghazal, H., Alshammari, A., Taweel, A., ElBokl, A., Nejjari, C., Alhuwail, D., Al-Thani, D., Al-Jafar, E., Wahba, H., Alrishidi, M., Hamdi, M., Househ, M., El-Hassan, O., Alnafrani, S., Kalhori, S. R. N., Emara, T., Alam, T., El Otmani Dehbi, Z., & Al-Shorbaji, N. (2022). Middle East and North African Health Informatics Association (MENAHIA). Yearbook of Medical Informatics, 31(01), 354–364. https://doi.org/10.1055/s-0042-1742495

Goirand, M., Austin, E., & Clay-Williams, R. (2021). Implementing Ethics in Healthcare AI-Based Applications: A Scoping Review. Science and Engineering Ethics, 27(5). https://doi.org/10.1007/s11948-021-00336-3

Gotsadze, G., Zoidze, A., Gabunia, T., & Chin, B. (2024). Advancing governance for digital transformation in health: insights from Georgia’s experience. BMJ Global Health, 9(10). https://doi.org/10.1136/bmjgh-2024-015589

Guarcello, C., & de Vargas, E. R. (2020). Service Innovation in Healthcare: A Systematic Literature Review. Latin American Business Review, 21(4), 353–369. https://doi.org/10.1080/10978526.2020.1802286

Gullslett, M. K., Ronchi, E., Lundberg, L., Larbi, D., Lind, K. F., Tayefi, M., Ngo, P. D., Sy, T. R., Adib, K., & Hamilton, C. (2024). Telehealth development in the WHO European region: Results from a quantitative survey and insights from Norway. International Journal of Medical Informatics, 191, 105558. https://doi.org/10.1016/j.ijmedinf.2024.105558

Gupta, A. K., & Srivastava, M. K. (2024). Framework for AI Adoption in Healthcare Sector: Integrated DELPHI, ISM-MICMAC Approach. IEEE Transactions on Engineering Management, 71, 8116–8131. https://doi.org/10.1109/TEM.2024.3386580

Hameed, B. M. Z., Naik, N., Ibrahim, S., Tatkar, N. S., Shah, M. J., Prasad, D., Hegde, P., Chlosta, P., Rai, B. P., & Somani, B. K. (2023). Breaking Barriers: Unveiling Factors Influencing the Adoption of Artificial Intelligence by Healthcare Providers. Big Data and Cognitive Computing, 7(2). https://doi.org/10.3390/bdcc7020105

Hee Lee, D., & Yoon, S. N. (2021). Application of artificial intelligence-based technologies in the healthcare industry: Opportunities and challenges. International Journal of Environmental Research and Public Health, 18(1), 1–18. https://doi.org/10.3390/ijerph18010271

Hofmann, P., Lämmermann, L., & Urbach, N. (2024). Managing artificial intelligence applications in healthcare: Promoting information processing among stakeholders. International Journal of Information Management, 75. https://doi.org/10.1016/j.ijinfomgt.2023.102728

Houfani, D., Slatnia, S., Kazar, O., Saouli, H., & Merizig, A. (2022). Artificial intelligence in healthcare: a review on predicting clinical needs. International Journal of Healthcare Management, 15(3), 267–275. https://doi.org/10.1080/20479700.2021.1886478

Houngbo, P. T., Zweekhorst, M., Bunders, J., Coleman, H. L. S., Medenou, D., Dakpanon, L., & De Cock Buning, T. (2017). The root causes of ineffective and inefficient healthcare technology management in Benin public health sector. Health Policy and Technology, 6(4), 446–456. https://doi.org/10.1016/j.hlpt.2017.06.004

Hsu, J. (2022). Personalized Digital Health Beyond the Pandemic. Journal for Nurse Practitioners, 18(7), 709–714. https://doi.org/10.1016/j.nurpra.2022.04.022

Huber, C., & Gärtner, C. (2018). Digital transformations in healthcare professionals’ work: Dynamics of autonomy, control and accountability. Management Revue, 29(2), 139–161. https://doi.org/10.5771/0935-9915-2018-2-139

Irfan, B., & Anirwan, A. (2023). Pelayanan Publik Era Digital: Studi Literatur. Indonesian Journal of Intellectual Publication, 4(1), 23–31.

Ivanova, A. A., Zavaleva, E. V, Shuvalov, S. S., & Andruzskaya, A. G. (2023). Health human resources. Medical Technologies. Assessment and Choice, 45(2), 59–66. https://doi.org/10.17116/medtech20234502159

Iyamu, I., Xu, A. X. T., Gómez-Ramírez, O., Ablona, A., Chang, H.-J., Mckee, G., & Gilbert, M. (2021). Defining digital public health and the role of digitization, digitalization, and digital transformation: Scoping review. JMIR Public Health and Surveillance, 7(11). https://doi.org/10.2196/30399

Jabarulla, M. Y., & Lee, H.-N. (2021). A blockchain and artificial intelligence-based, patient-centric healthcare system for combating the covid-19 pandemic: Opportunities and applications. Healthcare (Switzerland), 9(8). https://doi.org/10.3390/healthcare9081019

Jain, A., Vishwakarma, A., & Bhakta, D. (2025). Assessing the impact of artificial intelligence and circular economy on the healthcare sector: An empirical evidence from the Indian context. Journal of Cleaner Production, 486. https://doi.org/10.1016/j.jclepro.2024.144315

Jain, A., Way, D., Gupta, V., Gao, Y., De Oliveira Marinho, G., Hartford, J., Sayres, R., Kanada, K., Eng, C., Nagpal, K., Desalvo, K. B., Corrado, G. S., Peng, L., Webster, D. R., Dunn, R. C., Coz, D., Huang, S. J., Liu, Y., Bui, P., & Liu, Y. (2021). Development and Assessment of an Artificial Intelligence-Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners in Teledermatology Practices. JAMA Network Open, 4(4). https://doi.org/10.1001/jamanetworkopen.2021.7249

Ji, H., Dong, J., Pan, W., & Yu, Y. (2024). Associations between digital literacy, health literacy, and digital health behaviors among rural residents: evidence from Zhejiang, China. International Journal for Equity in Health, 23(1). https://doi.org/10.1186/s12939-024-02150-2

Judijanto, L. (2025). TRANSFORMASI DIGITAL DALAM PELAYANAN PUBLIK: IMPLIKASI DAN TANTANGAN HUKUM ADMINISTRASI NEGARA. ADMIN: Jurnal Administrasi Negara, 3(2), 1– 7.

Jussupow, E., Spohrer, K., Heinzl, A., & Gawlitza, J. (2021). Augmenting medical diagnosis decisions? An investigation into physicians’ decision-making process with artificial intelligence. Information Systems Research, 32(3), 713–735. https://doi.org/10.1287/ISRE.2020.0980

Kannelønning, M. S. (2024). Navigating uncertainties of introducing artificial intelligence (AI) in healthcare: The role of a Norwegian network of professionals. Technology in Society, 76. https://doi.org/10.1016/j.techsoc.2023.102432

Katirai, A., Yamamoto, B. A., Kogetsu, A., & Kato, K. (2023). Perspectives on artificial intelligence in healthcare from a Patient and Public Involvement Panel in Japan: an exploratory study. Frontiers in Digital Health, 5. https://doi.org/10.3389/fdgth.2023.1229308

Kauppinen, K., Keikhosrokiani, P., & Khan, S. (2024). Human-Centered Design and Benefit Realization Management in Digital Health Care Solution Development: Protocol for a Systematic Review. JMIR Research Protocols, 13. https://doi.org/10.2196/56125

khan, Z. F., & Alotaibi, S. R. (2020). Applications of Artificial Intelligence and Big Data Analytics in m-Health: A Healthcare System Perspective. Journal of Healthcare Engineering, 2020(1), 8894694. https://doi.org/https://doi.org/10.1155/2020/8894694

Khodjamurodov, G., & Rechel, B. (2010). Health systems in transition. Health, 12(2).

Kleczka, B., Musiega, A., Rabut, G., Wekesa, P., Mwaniki, P., Marx, M., & Kumar, P. (2018). Rubber stamp templates for improving clinical documentation: A paper-based, m-Health approach for quality improvement in low-resource settings. International Journal of Medical Informatics, 114, 121–129. https://doi.org/10.1016/j.ijmedinf.2017.10.014

Kraus, S., Schiavone, F., Pluzhnikova, A., & Invernizzi, A. C. (2021). Digital transformation in healthcare: Analyzing the current state-of-research. Journal of Business Research, 123, 557– 567. https://doi.org/10.1016/j.jbusres.2020.10.030

Kulkov, I. (2023). Next-generation business models for artificial intelligence start-ups in the healthcare industry. International Journal of Entrepreneurial Behaviour and Research, 29(4), 860–885. https://doi.org/10.1108/IJEBR-04-2021-0304

Kwiatkowska, E. M., & Skórzewska-Amberg, M. (2019). Digitalisation of Healthcare and the Problem of Digital Exclusion. Journal of Management and Business Administration. Central Europe, 27(2), 48–63. https://doi.org/10.7206/jmba.ce.2450-7814.252

Lapina, M. A. (2022). Organizational, legal and Financial Aspects of Digitalization and Implementation of Artificial Intelligence Technologies in Healthcare. Finance: Theory and Practice, 26(3), 169–185. https://doi.org/10.26794/2587-5671-2022-26-3-169-185

Lastri, S., Fahlevi, H., & Diantimala, Y. (2022). Mediation role of management commitment on improving fraud prevention in primary healthcare: Empirical evidence from Indonesia. Problems and Perspectives in Management, 20(1), 488–500. https://doi.org/10.21511/ppm.20(1).2022.39

Lee, C.-H., Wang, D., Lyu, S., Evans, R. D., & Li, L. (2023). A digital transformation-enabled framework and strategies for public health risk response and governance: China’s experience. Industrial Management and Data Systems, 123(1), 133–154. https://doi.org/10.1108/IMDS-01-2022-0008

Levin-Zamir, D. (2023). Digital health literacy and health technology in health systems and beyond: The importance of measurement, planned action, and policy for readiness and sustainability1. Information Services and Use, 43(2), 143–150. https://doi.org/10.3233/ISU- 230192

Liu, D. S., Sawyer, J., Luna, A., Aoun, J., Wang, J., Boachie, L., Halabi, S., & Joe, B. (2022). Perceptions of US Medical Students on Artificial Intelligence in Medicine: Mixed Methods Survey Study. JMIR Medical Education, 8(4). https://doi.org/10.2196/38325

Liu, S., & Xu, M. (2024). The application of artificial intelligence in ophthalmology teaching. Journal of Chinese Physician, 26(5), 663-666and672. https://doi.org/10.3760/cma.j.cn431274-20240322-00485

López, D. M., Rico-Olarte, C., Blobel, B., & Hullin, C. (2022). Challenges and solutions for transforming health ecosystems in low- and middle-income countries through artificial intelligence. Frontiers in Medicine, 9. https://doi.org/10.3389/fmed.2022.958097

Mackert, M., Mabry-Flynn, A., Champlin, S., Donovan, E. E., & Pounders, K. (2016). Health literacy and health information technology adoption: The potential for a new digital divide. Journal of Medical Internet Research, 18(10), e6349. https://doi.org/10.2196/jmir.6349

Mahmud, A., Dwivedi, G., & Chow, B. J. W. (2024). Exploring the Integration of Artificial Intelligence in Cardiovascular Medical Education: Unveiling Opportunities and Advancements. Canadian Journal of Cardiology, 40(10), 1946–1949. https://doi.org/10.1016/j.cjca.2024.06.014

Marliani, L., & Assyahri, W. (2024). Dampak Sistem Keuangan Desa (Siskuesdes) Terhadap Transformasi Digital dalam meningkatkan Pelayanan Publik Pengelolaan Keuangan Desa. Jurnal Ilmu Sosial Dan Humaniora, 2(2), 233–243.

Meurs, M., Keuper, J., Sankatsing, V., Batenburg, R., & Van Tuyl, L. (2022). “Get Used to the Fact that Some of the Care Is Really Going to Take Place in a Different Way”: general practitioners’ experiences with e-health during the COVID-19 pandemic. International journal of environmental research and public health, 19(9), 5120. https://doi.org/10.3390/ijerph19095120

Moulaei, K., Akhlaghpour, S., & Fatehi, F. (2025). Patient consent for the secondary use of health data in artificial intelligence (AI) models: A scoping review. International Journal of Medical Informatics, 198. https://doi.org/10.1016/j.ijmedinf.2025.105872

Musamih, A., Yaqoob, I., Salah, K., Jayaraman, R., Omar, M., & Ellahham, S. (2024). Using NFTs for Product Management, Digital Certification, Trading, and Delivery in the Healthcare Supply Chain. IEEE Transactions on Engineering Management, 71, 4480–4501. https://doi.org/10.1109/TEM.2022.3215793

Natika, L. (2024). Transformasi pelayanan publik Di era digital: Menuju pelayanan masa depan Yang lebih Baik. The World of Public Administration Journal, 6(1), 1–11.

Non, L. R., Marra, A. R., & Ince, D. (2025). Rise of the Machines - Artificial Intelligence in Healthcare Epidemiology. Current Infectious Disease Reports, 27(1). https://doi.org/10.1007/s11908-024-00854-8

Palmer, D. (1990). Artificial intelligence in healthcare management Healthcare Informatics : The Business Magazine for Information and Communication Systems, 7(3), 54. https://www.scopus.com/inward/record.uri?eid=2-s2.0-0025390566&partnerID=40&md5=fed9bb81c72a3c7ad0673a2c8db069bc

Petersson, L., Larsson, I., Nygren, J. M., Nilsen, P., Neher, M., Reed, J. E., Tyskbo, D., & Svedberg, P. (2022). Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden. BMC Health Services Research, 22(1). https://doi.org/10.1186/s12913-022-08215-8

Pires, L. B., Lima, I. L. P., Alves, T. O. S., de Menezes Araújo, D., Santos, J., & da Silva, F. J. C. P. (2024). Health technologies for tackling client absenteeism in primary and secondary care services. Journal of Evaluation in Clinical Practice, 30(8), 1717–1727. https://doi.org/10.1111/jep.14066

Plummer, V., & Boyle, M. (2017). Healthcare System in Indonesia. Hospital Topics, 95(4), 82–89. https://doi.org/10.1080/00185868.2017.1333806

Raghunathan, K., Morris, M. E., Wani, T. A., Edvardsson, K., Peiris, C., Fowler-Davis, S., McKercher, J. P., Bourke, S., Danish, S., Johnston, J., Moyo, N., Gilmartin-Thomas, J., Heng, H. W. F., Ho, K., Joyce-Mccoach, J., & Thwaites, C. (2025). Using artificial intelligence to improve healthcare delivery in select allied health disciplines: A scoping review protocol. BMJ Open, 15(3). https://doi.org/10.1136/bmjopen-2024-098290

Rahimi, S. A., Légaré, F., Sharma, G., Archambault, P., Zomahoun, H. T. V, Chandavong, S., Rheault, N., Wong, S. T., Langlois, L., Couturier, Y., Salmeron, J. L., Gagnon, M.-P., & Légaré, J. (2021). Application of artificial intelligence in community-based primary health care: Systematic scoping review and critical appraisal. Journal of Medical Internet Research, 23(9). https://doi.org/10.2196/29839

Rahman, A. (2024). Ethical Implications of Bioethics in the Integration of Artificial Intelligence within the Healthcare Sector of the USA. Journal of Commercial Biotechnology, 29(3), 71– 84. https://doi.org/10.5912/jcb2382

Roppelt, J. S., Kanbach, D. K., & Kraus, S. (2024). Artificial intelligence in healthcare institutions: A systematic literature review on influencing factors. Technology in Society, 76. https://doi.org/10.1016/j.techsoc.2023.102443

Samadhiya, A., Yadav, S., Kumar, A., Majumdar, A., Luthra, S., Garza-Reyes, J. A., & Upadhyay, A. (2023). The influence of artificial intelligence techniques on disruption management: Does supply chain dynamism matter? Technology in Society, 75. https://doi.org/10.1016/j.techsoc.2023.102394

Sangaiah, A. K., Javadpour, A., Ja’fari, F., Pinto, P., & Chuang, H.-M. (2024). Privacy-Aware and AI Techniques for Healthcare Based on K-Anonymity Model in Internet of Things. IEEE Transactions on Engineering Management, 71, 12448–12462. https://doi.org/10.1109/TEM.2023.3271591

Santamato, V., Tricase, C., Faccilongo, N., Iacoviello, M., & Marengo, A. (2024). Exploring the Impact of Artificial Intelligence on Healthcare Management: A Combined Systematic Review and Machine-Learning Approach. Applied Sciences (Switzerland), 14(22). https://doi.org/10.3390/app142210144

Schmitter, P., Shahgholian, A., & Tucker, M. (2024). Towards an understanding of the digital transformation of facility management in healthcare: perspectives from practice. Digital Transformation and Society, 3(4), 395–409. https://doi.org/10.1108/DTS-10-2023-0098

Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021). The role of artificial intelligence in healthcare: a structured literature review. BMC Medical Informatics and Decision Making, 21(1). https://doi.org/10.1186/s12911-021-01488-9

Siddiqi, S., Aftab, W., Siddiqui, F. J., Huicho, L., Mogilevskii, R., Friberg, P., Lindgren-Garcia, J., Causevic, S., Khamis, A., Shah, M. M., & Bhutta, Z. A. (2020). Global strategies and local implementation of health and health-related SDGs: Lessons from consultation in countries across five regions. BMJ Global Health, 5(9). https://doi.org/10.1136/bmjgh-2020-002859

Sisilianingsih, S., Purwandari, B., Eitiveni, I., & Purwaningsih, M. (2024). Analisis faktor transformasi digital pelayanan publik pemerintah di era pandemi. Jurnal Teknologi Informasi Dan Ilmu Komputer, 10(4), 883–892.

Stoumpos, A. I., Kitsios, F., & Talias, M. A. (2023). Digital Transformation in Healthcare: Technology Acceptance and Its Applications. International Journal of Environmental Research and Public Health, 20(4). https://doi.org/10.3390/ijerph20043407

Swan, E. L., Peltier, J. W., & Dahl, A. J. (2024). Artificial intelligence in healthcare: the value co- creation process and influence of other digital health transformations. Journal of Research in Interactive Marketing, 18(1), 109–126. https://doi.org/10.1108/JRIM-09-2022-0293

Terry, A., Lizotte, D., Brown, J., Ryan, B., Kueper, J., Meredith, L., Dang, J., Stewart, M., Zwarenstein, M., Leger, D., McKay, S., & Beleno, R. (2022). Is primary health care ready for artificial intelligence? Stakeholder perspectives: Worth the risk as long as you do it well. Annals of Family Medicine, 20. https://doi.org/10.1370/afm.20.s1.2905

Tripathi, S., & Musiolik, T. H. (2022). Fairness and ethics in artificial intelligence-based medical imaging. In Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention (pp. 79–90). IGI Global. https://doi.org/10.4018/978-1-6684-7544-7.ch005

Tursunbayeva, A., & Renkema, M. (2023). Artificial intelligence in health-care: implications for the job design of healthcare professionals. Asia Pacific Journal of Human Resources, 61(4), 845–887. https://doi.org/10.1111/1744-7941.12325

Walkinshaw, L. P., Mason, C., Allen, C. L., Vu, T., Nandi, P., Santiago, P. M., & Hannon, P. A. (2015). Process evaluation of a regional public health model to reduce chronic disease through policy and systems changes, Washington State, 2010-2014. Preventing Chronic Disease, 12, E37. https://doi.org/10.5888/pcd12.140446

Wamala-Andersson, S., Richardson, M. X., Stridsberg, S. L., Ryan, J., Sukums, F., & Goh, Y.-S. (2023). Artificial Intelligence and Precision Health Through Lenses of Ethics and Social Determinants of Health: Protocol for a State-of-the-Art Literature Review. JMIR Research Protocols, 12. https://doi.org/10.2196/40565

Wang, L., & Qin, J. (2022). Robotic and artificial intelligence in health care during the COVID-19 pandemic. Journal of Commercial Biotechnology, 27(3), 169–179. https://doi.org/10.5912/JCB1107

Wang, Y.-C., Chen, T.-C. T., & Chiu, M.-C. (2023). An improved explainable artificial intelligence tool in healthcare for hospital recommendation. Healthcare Analytics, 3. https://doi.org/10.1016/j.health.2023.100147

Wani, D., & Malhotra, M. (2018). Does the meaningful use of electronic health records improve patient outcomes? Journal of Operations Management, 60, 1–18. https://doi.org/10.1016/j.jom.2018.06.003

Xie, Y., Lu, L., Gao, F., He, S.-J., Zhao, H.-J., Fang, Y., Yang, J.-M., An, Y., Ye, Z.-W., & Dong, Z. (2021). Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare. Current Medical Science, 41(6), 1123–1133. https://doi.org/10.1007/s11596-021-2485-0

Yeates, N., & Surender, R. (2021). Southern social world-regionalisms: The place of health in nine African regional economic communities. Global Social Policy, 21(2), 191–214. https://doi.org/10.1177/1468018120961850

Yulanda, A., & Adnan, M. F. (2023). Transformasi Digital: Meningkatkan Efisiensi Pelayanan Publik Ditinjau dari Perspektif Administrasi Publik. Jurnal Ilmu Sosial Dan Humaniora, 1(3), 103– 110.

Zahlan, A., Ranjan, R. P., & Hayes, D. (2023). Artificial intelligence innovation in healthcare: Literature review, exploratory analysis, and future research. Technology in Society, 74. https://doi.org/10.1016/j.techsoc.2023.102321

Zaman, T. U., Alharbi, E. K., Bawazeer, A. S., Algethami, G. A., Almehmadi, L. A., Alshareef, T. M., Alotaibi, Y. A., & Karar, H. M. O. (2023). Artificial intelligence: the major role it played in the management of healthcare during COVID-19 pandemic. IAES International Journal of Artificial Intelligence, 12(2), 505–513. https://doi.org/10.11591/ijai.v12.i2.pp505-513

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2025-06-22

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Arifian, R. (2025). Transformasi Artificial Intelligence dalam Sistem Pelayanan Kesehatan Primer-Sekunder Daerah: Kajian Pemodelan Value Organisasi, Sumber Daya Manusia Kesehatan dan Sistem Kesehatan Daerah. Nusantara Innovation Journal, 3(2), 152–175. https://doi.org/10.70260/nij.v3i2.66

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