The State of Digital Medicine in Viet Nam 2026: A Landscape Review of Regulation, Infrastructure, Evidence and Implementation Readiness
REPORTS & LANDSCAPE ANALYSIS
The State of Digital Medicine in Viet Nam 2026: A Landscape Review of Regulation, Infrastructure, Evidence and Implementation Readiness
Last reviewed: 10 October 2026
Viet Nam has made substantial progress in healthcare digitalization. Electronic medical records are being introduced across hospitals, personal health information is increasingly connected with national digital infrastructure, and artificial intelligence is being developed, evaluated and used in selected clinical settings. At the same time, the legal environment governing health data, AI, cybersecurity and digital transformation has changed considerably during 2025 and 2026.
The scale of this transition is becoming more visible. As of 10 October 2026, the Ministry of Health's public electronic medical record implementation database listed 1,275 hospitals [1]. In August 2026, the Ministry reported that more than 34 million electronic health books, known as Sổ Sức khỏe điện tử, had been connected and integrated with the VNeID national digital identity application [2]. Earlier in April, the Ministry approved a nationwide plan aiming for electronic medical records without paper medical records at all healthcare facilities by 2030 [3].
These developments provide an increasingly important foundation for data-enabled healthcare. However, they should not be interpreted as evidence that Viet Nam already has a mature Digital Medicine ecosystem. The number of hospitals listed as implementing electronic medical records does not establish how consistently those systems are used, how effectively information moves between organizations or whether the resulting data can reliably support clinical decisions. Similarly, the number of electronic health books connected with VNeID does not demonstrate that every record contains complete, current and clinically usable information.
Digital health encompasses a broad range of technologies and activities, including electronic medical records, hospital information systems, telemedicine, mobile health applications, connected medical devices and artificial intelligence. Digital Medicine is a more specific field within this broader landscape. The Digital Medicine Society describes it as concerned with using technologies for measurement, intervention and improving human health, with particular attention to generating evidence that supports their appropriate use [4].
This distinction matters. Digitalization can make information available electronically and create opportunities for new models of care. Digital Medicine requires additional questions to be answered: Does a technology measure or intervene reliably? Is the evidence appropriate for its intended clinical use? Can it be integrated safely into care, and does it deliver meaningful benefits under real-world conditions?
For Viet Nam in 2026, the next stage is therefore not simply about introducing more digital systems. It is about building the evidence, governance and implementation capabilities needed to turn digital infrastructure into measurable improvements in healthcare quality, patient safety and health outcomes.
Viet Nam's regulatory environment has changed substantially
There is no single comprehensive Digital Medicine law in Viet Nam. The legal pathway for a digital health technology depends on what it does, how it is intended to be used, which information it processes and whether it falls within existing regulatory categories.
A clinical AI application, for example, may involve healthcare practice, medical-device regulation, artificial intelligence law, personal-data protection and cybersecurity requirements. These frameworks may apply simultaneously, but their obligations are not identical.
The Law on Medical Examination and Treatment No. 15/2023/QH15 provides the underlying legal framework for clinical services and professional responsibilities. For electronic medical records, Circular No. 13/2025/TT-BYT took effect on 21 July 2025, replacing the earlier electronic medical record guidance issued in 2018 [5].
The Circular establishes requirements for electronic medical record implementation and sets out a phased timetable. Hospitals were required to implement electronic medical records no later than 30 September 2025. Other healthcare establishments providing relevant inpatient, day-treatment or outpatient services have an implementation deadline of 31 December 2026, within the scope specified by the Circular.
The Ministry's subsequent Decision No. 965/QĐ-BYT, issued on 10 April 2026, approved a national implementation plan for 2026–2030, with the goal of deploying electronic medical records without paper medical records across all healthcare facilities by 2030 [3].
These provisions should be read together, while distinguishing regulatory implementation deadlines from the broader policy objective of comprehensive, paperless electronic medical records and connected health information across the country.
The wider data governance framework has also developed. The Law on Data No. 60/2024/QH15 came into effect on 1 July 2025, alongside Decree No. 102/2025/NĐ-CP on the management of digital health data and the National Health Database [6,7]. The Law on Personal Data Protection No. 91/2025/QH15 and Decree No. 356/2025/NĐ-CP subsequently took effect on 1 January 2026 [8,9].
Viet Nam's Law on Artificial Intelligence No. 134/2025/QH15 became effective on 1 March 2026, followed by Decree No. 142/2026/NĐ-CP on 1 May 2026 [10,11].
The new Law on Cybersecurity No. 116/2025/QH15 and Law on Digital Transformation No. 148/2025/QH15 both took effect on 1 July 2026. Decree No. 224/2026/NĐ-CP, detailing certain provisions and implementation measures under the Digital Transformation Law, also became effective on that date [12–14].
Medical-device regulation remains another important consideration. Under Decree No. 98/2021/NĐ-CP, as amended, software may fall within the medical-device framework when its intended medical purpose and functions meet the relevant regulatory definition [15]. Circular No. 24/2026/TT-BYT, effective from 1 July 2026, provides further provisions concerning risk determination and management measures for products and goods classified as medical devices [16].
For healthcare organizations and technology companies, the practical implication is that regulatory status cannot be determined from a product's marketing description alone. Calling software an AI assistant, wellness application, clinical support platform or digital health solution does not establish which legal requirements apply.
The organization needs to examine the product's actual intended purpose, functions, clinical use, processing of information and the responsibilities of the parties involved.
AI now operates within a formal risk-based regulatory framework
The introduction of Viet Nam's AI Law is an important development for Digital Medicine because AI systems may influence clinical decisions with consequences for patient safety.
The Law on Artificial Intelligence and its implementing Decree establish a broader framework for AI activities, including risk classification and obligations that depend on the nature and use of the system [10,11].
Decision No. 33/2026/QĐ-TTg, effective from 15 August 2026, introduced Viet Nam's official list of high-risk AI systems [17].
The healthcare-specific portion of the current list contains two entries relating to AI-assisted surgery and robotic-surgery systems under defined conditions. These concern AI integrated into systems directly participating in surgical interventions or guiding procedures, and certain systems capable of automatically performing therapeutic actions without requiring healthcare personnel to confirm each relevant change in operating parameters.
This relatively narrow list is important to understand, but it should not be interpreted as a comprehensive assessment of clinical AI risk.
An AI application used to prioritize radiology examinations, highlight abnormalities during endoscopy, estimate patient deterioration or generate clinical recommendations may not fall within those two healthcare-specific entries. That does not establish that its clinical risk is low, that its performance has been validated or that the application is exempt from other legal obligations.
The Decision also maintains the principle that AI use does not transfer or eliminate the legal responsibilities of competent organizations and individuals, and that human supervision, control and intervention must remain possible [17].
The distinction between legal classification and clinical safety is therefore essential. Legal classification determines particular regulatory obligations, while clinical risk assessment considers how a system can affect actual patient care, including the consequences of incorrect outputs, limitations in the evidence and safeguards available during use.
Both questions matter, but they are not interchangeable.
The broader national policy environment has also evolved. Decision No. 804/QĐ-TTg, issued in May 2026, identified datasets serving AI development in essential sectors, including health-related areas [18]. Decision No. 1671/QĐ-TTg, issued in August 2026, approved the National Strategy on Artificial Intelligence to 2030, with a vision to 2045 [19].
These measures reinforce Viet Nam's direction toward wider AI development and adoption. However, national strategic priorities do not replace the legal, professional and patient-safety requirements applicable to individual healthcare technologies.
Digital infrastructure is expanding, but interoperability remains uneven
Viet Nam's expanding electronic medical record infrastructure provides a stronger foundation for Digital Medicine than existed only a few years ago.
The Ministry of Health reported in February 2026 that 12 specialized health-sector databases had been upgraded, developed and connected at a basic level with national data infrastructure [20]. These cover areas including healthcare delivery, workforce information, immunization, maternal and child health, preventive health and other related services.
Work has continued on improving the quality and consistency of these datasets. In July 2026, the Ministry launched a nationwide 90-day campaign to review, clean, enrich and standardize information across 12 specialized databases, alongside efforts to expand electronic health information connected with VNeID [28].
This is an important development because establishing a database is not the same as making its contents reliable for clinical use. Incomplete identifiers, inconsistent coding, duplicate records and outdated information can undermine clinical decision support even when the underlying systems are technically connected.
Interoperability remains a particular challenge.
An electronic medical record can support documentation within one hospital without allowing information to be exchanged reliably with other systems. A hospital may have functioning laboratory, radiology and administrative software but still struggle to combine the resulting information into a sufficiently complete clinical record for advanced analytics or AI.
A cross-sectional study published in JMIR Formative Research in February 2025 examined digital health technology adoption in five major public hospitals in Viet Nam [21].
All five hospitals reported using core hospital information, laboratory and radiology information systems or picture archiving and communication systems. However, advanced digital capabilities were uneven. Two hospitals did not have an electronic medical record system, clinical data repository or clinical decision support system at the time of assessment.
Although some participating hospitals used international standards within their information systems, none reported exchanging clinical data with other organizations using HL7-based clinical information-sharing standards.
The study involved only five hospitals, and the underlying assessment preceded much of the national implementation activity during 2025 and 2026. It should not be treated as a representative measure of the country's current digital maturity.
Nevertheless, it illustrates an important distinction: digitization and interoperability are not the same thing.
For Digital Medicine, what matters is not simply whether information is stored electronically, but whether the relevant information is accurate, consistently interpreted, available when needed and appropriately connected to the patient's clinical context.
An AI application may perform well during development but become unreliable when deployed using incomplete clinical records, inconsistent coding or information that cannot be associated correctly with the relevant patient, encounter or examination.
The next stage of infrastructure development therefore needs to address the reliability and clinical usability of connected information, not only the number of systems that have been deployed.
Personal health data and cybersecurity require careful governance
Digital Medicine often involves information that is particularly sensitive, including symptoms, diagnoses, medication use, physiological measurements, behavioral information and predictions about future health risks.
The Law on Personal Data Protection and Decree No. 356/2025/NĐ-CP therefore have direct implications for many Digital Medicine applications [8,9].
Article 26 of the Law specifically addresses the protection of personal data relating to health information and insurance activities. It establishes requirements concerning consent for collecting and processing relevant personal data, subject to specified statutory exceptions, and places restrictions on certain disclosures of personal data by organizations and individuals operating in the health sector.
These provisions need to be considered alongside the Law's wider requirements and other applicable healthcare legislation. It would be incorrect to assume that every health-data processing activity always requires an identical form of consent or that one general consent automatically authorizes all subsequent uses.
For healthcare organizations, the practical questions concern what information is collected, the purposes and lawful basis for processing it, who can access it, where it is stored, how long it is retained and whether it may be used for purposes beyond the patient's immediate care.
These issues become more complex when external vendors, cloud services or AI developers are involved.
A healthcare organization may need to determine whether information collected during routine clinical care can lawfully be reused for model training, performance evaluation, research or commercial product improvement. Such uses may raise different legal, ethical and contractual questions from those involved in ordinary clinical documentation.
Cybersecurity must also be considered alongside privacy.
Connected medical devices, cloud services, application programming interfaces and AI applications can increase the number of systems and organizations involved in processing clinical information. A cybersecurity failure may therefore affect not only confidentiality but also the availability, accuracy and reliability of information used in patient care.
The Law on Cybersecurity No. 116/2025/QH15, effective from 1 July 2026, is part of the broader legal environment relevant to these developments [12].
The practical issue for healthcare organizations is not simply whether technology complies with a security checklist. It is whether essential clinical services can continue safely when systems are unavailable, information is compromised or connected technologies behave unexpectedly.
Patient safety, data protection and cybersecurity need to be considered together, while recognizing that they involve different responsibilities and legal requirements.
Telemedicine has a legal foundation, but Digital Medicine extends beyond remote consultation
Viet Nam's Law on Medical Examination and Treatment recognizes remote medical examination and treatment, while Circular No. 30/2023/TT-BYT establishes the list of diseases and conditions for which remote examination and treatment may be conducted [22,23].
This provides an important legal foundation for technology-enabled healthcare delivery.
However, telemedicine and Digital Medicine are not synonymous.
A video consultation primarily provides a digital channel through which healthcare professionals and patients can communicate. Digital Medicine may involve additional technologies that generate measurements, support interventions or influence clinical decisions.
Examples include connected devices measuring blood pressure, wearable technologies monitoring cardiac rhythm, software supporting disease management or algorithms identifying possible clinical deterioration.
In these situations, safe implementation depends on more than the availability of a digital connection.
Healthcare organizations need to determine who receives and reviews incoming information, which findings require a response, how quickly action should occur, what happens when data are missing and how relevant information becomes part of the patient's clinical record.
The distinction is particularly important for remote patient monitoring.
A system may successfully collect physiological information without improving care if abnormal results are not reviewed, responsibilities are unclear or patients cannot access timely follow-up.
Conversely, a relatively simple technology may provide meaningful value when it is integrated into an effective care pathway with clear clinical responsibilities.
Digital Medicine therefore depends on operational arrangements that connect information to appropriate clinical action.
Evidence generation is becoming increasingly important
Viet Nam is beginning to accumulate locally generated evidence for selected Digital Medicine applications, including AI-assisted gastrointestinal endoscopy.
A narrative review published in Therapeutic Advances in Gastrointestinal Endoscopy in December 2024 described research on AI applications in gastrointestinal endoscopy in Viet Nam dating from 2019. The review identified encouraging early findings from several locally developed lesion-detection and classification approaches, alongside limitations and challenges for wider clinical implementation [24].
More recent research provides an example of evaluation within a Vietnamese clinical setting.
A study by Lee and colleagues, published in Clinical Endoscopy in 2026, assessed real-time AI assistance during routine upper gastrointestinal endoscopy at University Medical Center Ho Chi Minh City [25].
The exploratory before-and-after study included 2,329 patients, with 1,491 examined before AI implementation and 838 afterward.
Following implementation, the average number of detected lesions per patient increased modestly from 1.15 to 1.20. The reported detection of lesions measuring 0.5 cm or smaller increased from 18.0% to 19.8%, while the biopsy rate decreased from 13.8% to 8.5%.
These results are relevant because they demonstrate the feasibility of studying AI within actual Vietnamese clinical workflows rather than relying exclusively on performance data generated elsewhere.
However, the study was conducted at a single center using a before-and-after design, with examinations performed by one experienced endoscopist. The findings may have been influenced by factors other than AI implementation, and the design does not establish that comparable effects would occur across other hospitals or patient populations.
The findings also concern particular detection and procedural measures. They should not automatically be interpreted as proof of improved long-term patient outcomes.
This distinction matters across Digital Medicine.
A technology may perform well in a technical evaluation but produce different results after deployment. An application developed using data from another country may encounter differences in disease prevalence, patient characteristics, equipment, clinical practice or information quality when used in Viet Nam.
Similarly, improved detection, more alerts or greater predictive accuracy do not necessarily establish that patients receive better care.
Evidence needs to be relevant to the technology's intended purpose and the clinical consequences of its use.
International assessment approaches can help healthcare organizations examine these questions systematically. The Evidence DEFINED framework, published in npj Digital Medicine in 2023, was developed to support rigorous but relatively rapid assessment of evidence for digital health interventions [26].
Such approaches can help organizations move beyond a narrow focus on published accuracy figures or vendor demonstrations.
For Viet Nam, an important next step is to improve the quality of local evaluations. This includes identifying meaningful comparison groups, measuring safety and unintended consequences, examining clinical workflow effects and assessing whether the technology delivers benefits that matter to patients.
More pilots alone will not necessarily produce stronger evidence. The design, relevance and quality of evaluation are what determine how useful the findings become.
Implementation readiness differs across healthcare organizations
There is no single national answer to whether Viet Nam is ready for Digital Medicine.
Readiness depends on the technology, clinical use case and capabilities of the organization expected to use it.
Some hospitals have advanced imaging equipment, established digital infrastructure, specialist teams and experience implementing complex technologies. Others continue to face challenges involving infrastructure, workforce capacity, procurement, data standardization and the integration of existing information systems.
These differences matter because purchasing a validated product does not automatically establish organizational readiness.
A hospital may acquire a technically strong AI application but lack a clearly designated clinical owner, an appropriate process for reviewing important errors or the resources needed to monitor its performance.
Another organization may implement a less technologically complex application more effectively because the clinical problem is well defined, responsibilities are clear and the workflow has been designed around actual patient needs.
A practical readiness assessment should therefore examine several dimensions together.
The first is regulatory fit: whether the technology's intended use, legal status and applicable obligations have been adequately established.
The second is the evidence supporting its use. This includes technical performance, clinical validity, effectiveness, safety and relevance to the intended patient population and care environment.
The third is data and infrastructure readiness. Healthcare organizations need sufficiently reliable information, appropriate system integration and adequate cybersecurity and data-protection arrangements.
Clinical workflow readiness is equally important. An AI application should have a clear place in the care pathway, with defined responsibilities for reviewing results, making decisions and responding to important findings.
Organizational capability also matters. Staff need appropriate training, leadership support and realistic arrangements for change management, procurement and ongoing financial sustainability.
Finally, organizations need the ability to evaluate what happens after implementation. This includes identifying errors, monitoring performance changes, reviewing staff feedback and assessing actual clinical and operational outcomes.
These dimensions are interconnected. Strong technology cannot compensate indefinitely for unreliable information or poorly defined clinical responsibilities. Equally, good governance cannot turn an ineffective intervention into a clinically beneficial one.
The World Health Organization's Global Strategy on Digital Health 2020–2027 similarly emphasizes that sustainable digital health transformation requires the integration of financial, organizational, human and technological resources [27].
Readiness is therefore not simply a technology assessment. It is an assessment of whether the healthcare organization can use the technology safely, effectively and sustainably.
Which Digital Medicine applications appear most feasible?
Under current conditions, some of the more practical near-term opportunities in Viet Nam are likely to involve technologies that support existing clinical services while maintaining clearly defined professional responsibilities.
Examples include appropriately validated digital measurement technologies, clinician-supervised remote monitoring, AI used as a second reader or decision-support tool, digital systems supporting follow-up and continuity of care, and applications that help healthcare organizations identify clinically relevant risks or variation.
These applications may be easier to integrate into existing care structures than systems that independently make high-consequence clinical decisions.
However, they should not automatically be regarded as low risk.
An AI application used to prioritize examinations can still create patient-safety problems if important cases are delayed. A remote monitoring system may be ineffective if alerts do not reach the responsible clinician. A digital assessment tool may perform differently across patient groups or generate unnecessary investigations.
Suitability therefore depends on the clinical purpose, strength of evidence, expected consequences of error and the organization's ability to maintain appropriate controls.
Higher-consequence applications require correspondingly stronger evidence and safeguards. These may include systems with substantial autonomy over diagnosis or treatment, applications generating high-stakes clinical recommendations and predictive technologies used across large patient populations without adequate local evaluation.
The relevant issue is not whether a technology appears advanced, innovative or commercially attractive.
It is whether its intended use is justified by a genuine healthcare need, whether the supporting evidence is sufficient and whether the organization can implement and monitor it reliably.
Regulatory authorization or clearance in another country may provide useful information. However, it should not be interpreted as unrestricted readiness for use in Viet Nam. Local legal requirements, patient characteristics, language, workflows and data environments still need to be considered.
Viet Nam should measure impact, not adoption alone
Healthcare digitalization is often described through adoption figures: the number of hospitals using electronic records, applications downloaded, devices connected or AI systems deployed.
These indicators are useful for understanding the spread of technology. They are less informative about whether patients or healthcare organizations are benefiting.
For Digital Medicine, some of the most important questions arise after implementation.
Did a diagnostic application improve clinically important detection without creating an unacceptable increase in false positives? Did remote monitoring identify deterioration earlier or reduce avoidable healthcare use? Did staff actually save time once reviewing and responding to digital information was included? Did the intervention remain accessible to patients with different levels of digital literacy?
Other questions concern safety, equity and sustainability. Were unintended consequences identified? Did performance remain acceptable across relevant patient groups? Did the technology reduce or increase unnecessary clinical workload? Did its benefits justify the costs of implementation and maintenance?
These questions require appropriate evaluation methods and an understanding of the outcomes being measured.
Some technologies may improve a process measure without demonstrating a direct improvement in patient health. Others may provide value through better access, timelier communication or more reliable follow-up, even when immediate changes in clinical outcomes are difficult to measure.
Healthcare organizations should therefore define what meaningful value looks like before introducing a technology and establish how that value will be evaluated afterward.
Viet Nam's expanding electronic health infrastructure could increasingly support this work.
If data quality, interoperability and governance continue to improve, electronic medical records and connected health information may help organizations conduct prospective evaluations, assess real-world performance and identify opportunities for continuous improvement.
The ability to measure what happens after implementation may ultimately become more important to the maturity of Digital Medicine than simply increasing the number of technologies available.
The next phase should prioritize evidence-led implementation
The state of Digital Medicine in Viet Nam in 2026 is best understood as a developing ecosystem with increasingly strong digital and regulatory foundations, but uneven evidence and implementation maturity.
The country has made important progress in electronic medical records, national digital health infrastructure and the legal frameworks governing health data, artificial intelligence and cybersecurity.
At the same time, interoperability remains a work in progress. Evidence generated within Vietnamese clinical settings is still limited for many technologies, and the capabilities required for safe implementation vary considerably among healthcare organizations.
These limitations do not mean Viet Nam should delay the adoption of promising technologies until every part of its digital infrastructure is mature. They mean adoption should be selective, proportionate to risk and supported by appropriate evaluation.
The next phase should begin with a healthcare need rather than a technology looking for a use case.
A healthcare organization should first define the clinical or operational problem it intends to address, establish the technology's intended purpose and evaluate whether the available evidence supports that purpose.
It should then identify the applicable regulatory requirements, assess organizational readiness, determine how the technology will fit into clinical care and establish appropriate responsibilities for its use.
Once implementation begins, attention should shift toward whether the technology performs as expected, whether important risks are being managed and whether patients and the health system are receiving measurable value.
This approach also creates opportunities for local learning. Not every successful pilot should lead immediately to wider deployment, and not every unsuccessful pilot represents wasted effort. Carefully evaluated implementation can help organizations understand which technologies work, for whom, under what conditions and at what cost.
For Viet Nam, the central question is no longer simply how quickly Digital Medicine can be adopted.
A more useful question is how healthcare organizations can select, govern, implement, monitor and scale technologies in ways that maintain patient safety and improve actual healthcare delivery.
Viet Nam increasingly has the digital foundation to pursue this next stage.
The opportunity now is not simply to adopt more technology, but to build the evidence, governance and implementation capabilities needed to turn digital adoption into better healthcare.
References and further reading
Ministry of Health of Viet Nam. Electronic Medical Record Implementation Dashboard and List of Hospitals. Accessed 10 October 2026.
Sức khỏe & Đời sống, Ministry of Health of Viet Nam. Tăng tốc triển khai Bệnh án, Sổ sức khỏe điện tử, không để chậm tiến độ chuyển đổi số y tế. 25 August 2026.
Ministry of Health of Viet Nam. Decision No. 965/QĐ-BYT Approving the Nationwide Electronic Medical Record Implementation Plan for 2026–2030. Issued 10 April 2026.
Digital Medicine Society. Defining Digital Medicine.
Ministry of Health of Viet Nam. Circular No. 13/2025/TT-BYT Providing Guidance on Electronic Medical Record Implementation. Issued 6 June 2025; effective 21 July 2025.
National Assembly of Viet Nam. Law No. 60/2024/QH15 on Data. Adopted 30 November 2024; effective 1 July 2025.
Government of Viet Nam. Decree No. 102/2025/NĐ-CP on the Management of Health Data. Issued 13 May 2025; effective 1 July 2025.
National Assembly of Viet Nam. Law No. 91/2025/QH15 on Personal Data Protection. Adopted 26 June 2025; effective 1 January 2026.
Government of Viet Nam. Decree No. 356/2025/NĐ-CP Detailing Provisions and Implementation Measures under the Law on Personal Data Protection. Issued 31 December 2025; effective 1 January 2026.
National Assembly of Viet Nam. Law No. 134/2025/QH15 on Artificial Intelligence. Adopted 10 December 2025; effective 1 March 2026.
Government of Viet Nam. Decree No. 142/2026/NĐ-CP Detailing Provisions and Implementation Measures under the Law on Artificial Intelligence. Issued 30 April 2026; effective 1 May 2026.
National Assembly of Viet Nam. Law No. 116/2025/QH15 on Cybersecurity. Adopted 10 December 2025; effective 1 July 2026.
National Assembly of Viet Nam. Law No. 148/2025/QH15 on Digital Transformation. Adopted 11 December 2025; effective 1 July 2026.
Government of Viet Nam. Decree No. 224/2026/NĐ-CP Detailing Provisions and Implementation Measures under the Law on Digital Transformation. Issued 24 June 2026; effective 1 July 2026.
Government of Viet Nam. Decree No. 98/2021/NĐ-CP on Medical Device Management, as Amended.
Ministry of Health of Viet Nam. Circular No. 24/2026/TT-BYT on Risk Determination and Management Measures for Medical-Device Products and Amendments to Circular No. 05/2022/TT-BYT. Issued 30 June 2026; effective 1 July 2026.
Prime Minister of Viet Nam. Decision No. 33/2026/QĐ-TTg Promulgating the List of High-Risk Artificial Intelligence Systems. Issued 30 June 2026; effective 15 August 2026.
Prime Minister of Viet Nam. Decision No. 804/QĐ-TTg Promulgating the List of Datasets for Artificial Intelligence Development in Essential Sectors. Issued 6 May 2026.
Prime Minister of Viet Nam. Decision No. 1671/QĐ-TTg Approving the National Strategy on Artificial Intelligence to 2030, with a Vision to 2045. Issued 28 August 2026.
Ministry of Health of Viet Nam. Tiếp tục định hình diện mạo y tế số, nâng cao hiệu quả phục vụ người dân. 21 February 2026.
Tran DM, Dung NT, Duc CM, et al. Status of Digital Health Technology Adoption in 5 Vietnamese Hospitals: Cross-Sectional Assessment. JMIR Formative Research. 2025;9. DOI: 10.2196/53483.
National Assembly of Viet Nam. Law No. 15/2023/QH15 on Medical Examination and Treatment, as amended. Adopted 9 January 2023; principally effective 1 January 2024.
Ministry of Health of Viet Nam. Circular No. 30/2023/TT-BYT Prescribing the List of Diseases and Medical Conditions Eligible for Remote Medical Examination and Treatment. Issued 30 December 2023; effective 1 January 2024.
Dao HV, Nguyen BP, Nguyen TT, et al. Application of Artificial Intelligence in Gastrointestinal Endoscopy in Vietnam: A Narrative Review. Therapeutic Advances in Gastrointestinal Endoscopy. 2024;17:26317745241306562. DOI: 10.1177/26317745241306562.
Lee H, Huynh CB, Cho S, et al. Impact of Real-Time Artificial Intelligence Integration on Detection of Gastric Lesions: An Exploratory Single-Center Before-and-After Study Using Low-Definition Routine Endoscopy. Clinical Endoscopy. 2026;59(3):408–416. DOI: 10.5946/ce.2025.272.
Silberman J, Wicks P, Patel S, et al. Rigorous and Rapid Evidence Assessment in Digital Health with the Evidence DEFINED Framework. npj Digital Medicine. 2023;6:101. DOI: 10.1038/s41746-023-00836-5.
World Health Organization. Global Strategy on Digital Health 2020–2027. Geneva: World Health Organization; 2025. ISBN: 978-92-4-011687-0.
Government News Portal of Viet Nam. Triển khai chiến dịch 90 ngày làm sạch, chuẩn hóa dữ liệu chuyên ngành y tế. 15 July 2026.
Professional education and regulatory notice
This article provides an educational landscape review of Digital Medicine in Viet Nam as of 10 October 2026. It examines developments in regulation, digital infrastructure, evidence generation and healthcare implementation readiness.
The regulatory status of any Digital Medicine technology depends on its intended use, actual functionality, clinical purpose, information-processing activities and implementation context. Depending on these characteristics, several legal frameworks may apply simultaneously, including healthcare, medical-device, artificial intelligence, personal-data-protection and cybersecurity legislation.
Implementation statistics and research findings cited in this article should be interpreted according to their original sources, reporting dates, study designs and limitations. National digitalization indicators do not necessarily establish clinical effectiveness, technical interoperability or organizational readiness, while results from individual healthcare organizations should not be generalized automatically to the wider Vietnamese health system.
This article is intended for professional education and knowledge exchange. It does not constitute individualized legal, regulatory, clinical, medical-device, cybersecurity, personal-data-protection or quality-management advice.