In China, HTA is increasingly used to inform decisions relating to healthcare reimbursement, the assessment of innovative medicines and medical technologies, and the allocation of healthcare resources. However, HTA capacity and access to specialist expertise remain uneven across institutions and regions. Against this background, the workshop provided an opportunity to examine whether AI-assisted approaches could improve efficiency and capacity while maintaining methodological quality and expert accountability.
On 10 July 2026, ECHORA Global and the Zhongwei Institute of Health Technology Assessment (Zhongwei Institute of HTA) successfully co-hosted the AI-assisted HTA Workshop. Held in a hybrid format, the workshop brought together professionals from health economics, health technology assessment (HTA), medicine, academia, industry and related sectors to explore the application of artificial intelligence (AI) in HTA.
Recent advances in large language models (LLMs) and AI agents have created new opportunities for biomedical research and evidence-informed decision-making. At the same time, HTA continues to face challenges associated with labour-intensive evidence retrieval, systematic reviews, quality appraisal and report development. How AI can be effectively integrated into HTA while maintaining scientific rigour, transparency and traceability has become an increasingly important topic for the international HTA community.
ECHORA Global: AI is Creating New Opportunities for HTA
The workshop opened with welcome remarks from Dr Huajie Jin, Chair of ECHORA Global, Associate Professor and Deputy Director of the Health Economics Research Centre at King’s College London.
Dr Jin introduced the mission and recent development of ECHORA Global, which is committed to connecting Chinese-speaking and China-facing professionals working in Health Economics, Outcomes Research (HEOR), Health Technology Assessment (HTA) and Market Access, while promoting collaboration between China and the international HTA community. Since its establishment, ECHORA Global has received over 1,100 membership applications and organised more than ten international academic events, gradually becoming an important platform connecting academia, industry, healthcare organisations and policy makers.
Reflecting on recent developments in artificial intelligence, Dr Jin highlighted that AI is rapidly transforming the way evidence is generated and synthesised—from systematic reviews and evidence synthesis to HTA report development. However, in the highly specialised field of HTA, the successful application of AI depends on robust methodological frameworks, expert governance, and transparent and traceable evidence systems. This workshop therefore aimed to promote international dialogue on the future direction, practical applications and collaborative opportunities of AI-assisted HTA.
Exploring a AI-Assisted HTA in a Non-profit Setting
The second presentation was delivered by Xiaoyu Tian, Project Manager at the Zhongwei Institute of Health Technology Assessment, who introduced the institute’s development journey together with the overall design concept of the HTA Agent.
As China’s first non-profit HTA organisation, the institute has long been committed to promoting the standardised application of HTA and supporting evidence-informed healthcare decision-making. In recent years, the institute has conducted extensive work in innovative drug assessment, real-world evidence studies, and value assessment for healthcare reimbursement, while actively exploring the integration of AI into HTA practice.
Tian introduced the overall architecture of the HTA Agent, which is built around “Two Databases and a Full Workflow.” By integrating literature databases, expert databases and standardised HTA workflows, the platform supports AI-assisted PICOS design, literature retrieval, screening, quality appraisal, data extraction and report generation throughout the HTA process.
A particular focus of the presentation was the Human-in-the-loop approach, under which AI is responsible for improving efficiency while experts remain responsible for methodological review, quality assurance and final judgement. This collaborative model aims to ensure scientific rigour, transparency and traceability throughout the assessment process.
The presentation also introduced future development plans covering Meta-analysis, Network Meta-analysis, health economic modelling and an openly accessible repository of non-commercial HTA reports, with the goal of further strengthening AI-assisted HTA capability and international collaboration.
SmartHTA: Building a New Paradigm for AI-assisted, Expert-governed HTA
The third presentation was delivered by Jiankai Wang, Senior Technical Research Expert at ZTE, who introduced SmartHTA.
Wang began by outlining several major challenges facing conventional HTA, including lengthy assessment timelines, substantial resource requirements, uneven distribution of HTA expertise and limited transparency. SmartHTA has been developed around the concept of AI-assisted, Expert-governed HTA, allowing AI to undertake repetitive tasks such as literature retrieval, screening, information extraction and draft report generation, while ensuring that experts remain responsible for methodological design, quality assurance and final decision-making.
Addressing one of the most frequently discussed challenges in AI applications, Wang presented SmartHTA’s approach to evidence traceability and quality control. The platform establishes a complete evidence chain management system, enabling every inclusion or exclusion decision, every extracted data point and every key conclusion within an HTA report to be traced back to its original source. Combined with structured information extraction, automated quality checking, human-AI collaborative review and comprehensive audit records, these mechanisms are designed to minimise AI hallucinations while ensuring scientific credibility, transparency and explainability.
The presentation also introduced SmartHTA’s systematic benchmarking framework covering six core HTA tasks, including literature classification, study selection, quality appraisal, data extraction, report generation and evidence traceability. Internal benchmarking has demonstrated encouraging performance across multiple tasks, while the team emphasised that further external validation involving independent HTA experts will be essential for continuously improving both model performance and methodological reliability.
Finally, Wang presented a live demonstration of the SmartHTA platform, showcasing its end-to-end AI-assisted HTA workflow and introducing future development plans covering Meta-analysis, Real-World Data (RWD) analysis and automated health economic modelling.
Expert Panel: Validation, Governance and Implementation of AI-Assisted HTA
The workshop continued with an expert panel discussion, during which invited experts exchanged perspectives on several key topics in AI-assisted HTA, including:
• Validation methodologies for AI-assisted evidence assessment
• Integration of AI into health economic evaluation
• HTA quality assurance and expert governance
• Applications of Real-World Data (RWD) in AI-assisted HTA
• AI-supported HTA capacity building in developing countries
Drawing upon their respective research and practical experience, panel members shared insights from methodological, technical and implementation perspectives while discussing the future direction of AI-assisted HTA.
A clear consensus emerged throughout the discussion: although AI has enormous potential to improve the efficiency of HTA, scientific rigour, transparency, explainability and expert oversight must remain the fundamental principles guiding its future development. Rather than replacing HTA professionals, AI should serve as a collaborative tool that reduces repetitive tasks and enables experts to devote more time to methodological judgement, evidence interpretation and value-based decision-making. This AI-assisted, Expert-governed model was recognised as a promising direction for the future development of HTA.
Interactive Q&A: In-depth Discussions on AI-assisted HTA
Following the expert panel, the workshop concluded with both online and in-person Q&A sessions.
Participants from universities, healthcare institutions, industry and HTA organisations actively raised questions covering SmartHTA implementation, AI-assisted evidence assessment, multi-source evidence integration, Real-World Data applications, health economic modelling and future methodological development.
The discussion remained highly interactive throughout the session, with many questions leading to further exchanges among speakers and experts. The enthusiastic participation reflected the rapidly growing international interest in AI-assisted HTA and generated valuable ideas for future methodological innovation and international collaboration.
ECHORA Global Continues to Promote International Collaboration
As an international platform for professionals working in HEOR, HTA and Market Access, ECHORA Global remains committed to strengthening collaboration between China and the global health economics and HTA community.
This workshop not only showcased emerging approaches to AI-assisted HTA, but also provided an international forum for experts from different countries and sectors to exchange ideas, share practical experience and explore future collaborations.
ECHORA Global looks forward to continuing its collaboration with partners worldwide by organising more academic activities on HTA, HEOR, health policy and AI-enabled healthcare, contributing to methodological innovation and the future development of evidence-informed healthcare decision-making.
ECHORA Global provides an independent forum for professional and academic exchange. The tools, performance results and views presented during the workshop were those of the respective speakers and organisations and should not be interpreted as endorsement or independent validation by ECHORA Global.