The evolution of digital technology within the healthcare sector has achieved significant milestones, notably through the implementation of digital twins. According to reports from the World Health Organization (WHO), the adoption of digital twin technology in global hospitals has increased by 45% since 2023. This growth is driven by the ability of the technology to accelerate diagnoses and mitigate the risk of medical errors. In the context of healthcare delivery, a digital twin serves as a virtual model of a patient’s physiological condition, facilitating the simulation of therapeutic responses and supporting high precision medical decision making. Such technology possesses the potential to enhance the quality of healthcare services, the efficacy of treatments, and the overall efficiency of the healthcare system.
Defining the Digital Twin as a Medical Transformation
A digital twin is a sophisticated system that integrates real-time patient data with intelligent simulation algorithms. Dr. Karen Liu, a medical technology expert from MIT Health Systems, observes that digital twins provide physicians with the capability to observe the internal workings of a patient’s body without resorting to invasive surgical procedures. Within the medical sector, digital twins are utilized to virtually simulate human organs, allowing practitioners to predict a patient’s response to a specific treatment without direct experimentation. The utilization of this technology is believed to improve patient safety while streamlining the diagnostic process and the determination of therapeutic pathways.
Digital twin technology synthesizes several advanced disciplines, including the Internet of Medical Things (IoMT), Artificial Intelligence (AI), machine learning, and big data analytics. Hospitals and laboratories utilize these virtual models to simulate physiological conditions, disease progression, and bodily responses to pharmacological interventions. This system functions through several critical phases:
- Real-time Data Acquisition
Data is collected through wearable devices, medical examinations, and electronic health records stored within digital systems.
- Virtual Modeling
Utilizing AI and machine learning, a detailed representation of the structure and function of the patient’s organs is constructed.
- Simulation of Diagnosis and Treatment
Physicians conduct virtual testing of various therapeutic options to observe potential outcomes.
- Automated Predictive Analysis
The system generates outputs including predictive recommendations regarding treatment efficacy, complication risks, and long-term physiological impacts.
The Legality of Digital Twin Implementation in Indonesia
Legal protection in the digital health sphere aims to provide certainty regarding the rights and obligations of all involved parties. Patients maintain the right to the protection of their personal data, access to accurate medical information, and healthcare services that meet established standards. Conversely, medical professionals require legal certainty to utilize advanced technologies in their practice without facing disproportionate legal risks.
Although Indonesia has not yet enacted a specific regulation exclusively governing digital twin practices, Law No. 17/2023 on Health (the Health Law) mandates the utilization of information technology within healthcare services. Article 25 of the Health Law provides the broad legislative basis for digital transformation in the sector.
Furthermore, Article 351 Paragraph 1 of the Health Law obligates providers of health information systems to guarantee the protection of individual health data and information. This implies that any party involved in storing, managing, processing, or distributing health data is legally bound to maintain the confidentiality, security, and integrity of such information.
Regarding the protection of patient data, reference must be made to Law No. 27/2022 concerning Personal Data Protection (the PDP Law). This statute serves as the primary legal foundation for data management, wherein medical data is categorized as sensitive personal data requiring specific safeguards. Consequently, digital healthcare providers must maintain system security, implement protective measures such as data encryption, and obtain explicit patient consent before utilizing or sharing medical information.
Benefits and Challenges of Digital Twin Integration
The application of digital twin technology in the medical field offers various advantages for both healthcare professionals and patients:
- Enhanced Diagnostic Precision
Digital twins enable the early identification of chronic diseases, such as heart failure, diabetes, and cancer, often before clinical symptoms manifest.
- Personalized Treatment Regimens
Given that every patient is unique, digital simulations allow physicians to calibrate medication dosages and therapeutic methods based on specific physiological responses.
- Risk-Free Clinical Trials
To minimize medical risks, pharmaceutical companies can utilize digital models to review the efficacy of a drug before it is tested on human subjects.
- Continuous Long-Term Monitoring
Digital twins can be updated using real-time data from health devices, facilitating the remote monitoring of patients with chronic conditions..
- Operational Efficiency
By predicting care requirements and resource allocation, digital twins assist hospitals in managing patient care systems more efficiently.
Despite these benefits, the implementation of digital twins faces significant hurdles. A primary concern is the protection of patient data, as the technology requires extensive access to genetic, biometric, and highly private medical information.
Although Indonesia has established regulations to mitigate these risks, the processing of sensitive medical data remains a central point of concern for regulators and ethicists. Any unauthorized use or data breach could lead to severe legal consequences and ethical dilemmas. In addition, the high cost of infrastructure remains a barrier, particularly for healthcare facilities in developing regions with limited technological resources.***
Also read: Precision Medicine: The Future of Personalised and Effective Healthcare in Indonesia
Regulations:.
- Undang-Undang Nomor 17 Tahun 2023 tentang Kesehatan (“UU Kesehatan”).
- Undang-Undang Nomor 27 Tahun 2022 tentang Pelindungan Data Pribadi (“UU PDP”)
References:
- Teknologi Digital Twin di Dunia Medis: Simulasi Tubuh untuk Diagnosis Tepat. History Labunas (Diakses pada tanggal 31 Desember 2025 pukul 15.04 WIB).
- Digital Twins Technology: Revolusi Baru dalam Dunia Digital dan Industri Modern. Publish Jurnal (Diakses pada tanggal 31 Desember 2025 pukul 15.54 WIB).
- Digital Twin di Dunia Medis: Simulasi Pasien untuk Pengobatan Akurat. IndoTech Insight (Diakses pada tanggal 31 Desember 2025 pukul 15.44 WIB).
- Perlindungan Hukum bagi Pasien dan Tenaga Medis dalam Inovasi Kesehatan Digital. Sinode GMIM (Diakses pada tanggal 31 Desember 2025 pukul 16.24 WIB).