ReviewValue in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research2025
Generative Artificial Intelligence for Health Technology Assessment: Opportunities, Challenges, and Policy Considerations: An ISPOR Working Group Report.
Review in Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Faster but Not Truer, Part 1: A Systematic Scoping Review of Artificial Intelligence in Health Economics and Outcomes Research.Journal of health economics and outcomes research · 2026Pooled it
- Faster but Not Truer, Part 2: The Regulatory Record, the Economics, and the TRACE-HEOR Reporting Standard.Journal of health economics and outcomes research · 2026Pooled it
- Artificial intelligence in rehabilitation: a living systematic mapping review - first release.European journal of physical and rehabilitation medicine · 2025Pooled it
- Recommendations for the use of clinical outcome assessments in rare disease drug development.EClinicalMedicine · 2026Review
- Reporting the use of AI in horizon scanning: a brief communication on methodological standards.International journal of technology assessment in health care · 2026Article
- Leveraging generative artificial intelligence for the development of non-interventional research study protocols: a proof-of-concept feasibility study.BMC medical research methodology · 2026Article
- From API to Action: A Multi-Model Comparison of OpenAI, Anthropic, Google, and Meta LLMs for Clinical Trial Data Extraction.Bioengineering (Basel, Switzerland) · 2026Article
- Using full agreement across multiple large language models for title-and-abstract screening in systematic reviews: a proof-of-concept.Systematic reviews · 2026Article
- Competencies for health technology assessment professionals: a scoping review and content analysis.International journal of technology assessment in health care · 2026Article
- Exploring the challenges of developing hospital-based health technology assessment in Iran: a qualitative study.Health research policy and systems · 2026Article
- Beyond efficiency: reimagining health technology assessment in the age of artificial intelligence.International journal of technology assessment in health care · 2026Article
- Ontology-driven generation of parameters for health technology assessment models: a prompt engineering study.International journal of technology assessment in health care · 2026Article
- Article
- Trust, validation, and accountability: implementing uses of generative artificial intelligence into Health Technology Assessment practice.International journal of technology assessment in health care · 2026Article
- Advancing the science of qualitative patient preference assessment using large language models.PLOS digital health · 2026Article
- Applications of artificial intelligence for real-world evidence generation: a protocol for a living scoping review.BMJ open · 2026Article
- Mapping the integration of artificial intelligence and digital technologies in health technology assessment: a scoping review protocol of global knowledge and practices.Systematic reviews · 2026Article
- Advancing the use of artificial intelligence in health technology assessment activities: insights and next steps from the 2025 HTAi Global Policy Forum.International journal of technology assessment in health care · 2026Article
- Bridging the patient gap: exploring generative AI to support meaningful patient involvement in health technology assessment.Journal of comparative effectiveness research · 2025Review
- Human-in-the-Loop Artificial Intelligence System for Systematic Literature Review: Methods and Validations for the AutoLit Review Software.Cochrane evidence synthesis and methods · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
objectivesTo provide an introduction to the uses of generative artificial intelligence (AI) and foundation models, including large language models, in the field of health technology assessment (HTA).
methodsWe reviewed applications of generative AI in 3 areas: systematic literature reviews, real-world evidence, and health economic modeling.
results(1) Literature reviews: generative AI has the potential to assist in automating aspects of systematic literature reviews by proposing search terms, screening abstracts, extracting data, and generating code for meta-analyses; (2) real-world evidence: generative AI can facilitate automating processes and analyze large collections of real-world data, including unstructured clinical notes and imaging; (3) health economic modeling: generative AI can aid in the development of health economic models, from conceptualization to validation. Limitations in the use of foundation models and large language models include challenges surrounding their scientific rigor and reliability, the potential for bias, implications for equity, as well as nontrivial concerns regarding adherence to regulatory and ethical standards, particularly in terms of data privacy and security. Additionally, we survey the current policy landscape and provide suggestions for HTA agencies on responsibly integrating generative AI into their workflows, emphasizing the importance of human oversight and the fast-evolving nature of these tools.
conclusionsAlthough generative AI technology holds promise with respect to HTA applications, it is still undergoing rapid developments and improvements. Continued careful evaluation of their applications to HTA is required. Both developers and users of research incorporating these tools, should familiarize themselves with their current capabilities and limitations.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.