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TRUVACE RECORD VERSION
record: TRV-2026-0316
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-07-20T08:46:27.559400Z
status: published
lens: p_space
sector: health
headline: Beyond the algorithm: health technology assessment frameworks for AI in cardiology under the European Union Health Technology Assessment Regulation: a systematic review
dek: Background: Artificial intelligence (AI) is increasingly used in cardiovascular care to support diagnosis, monitoring and clinical decision-making. However, its dynamic and adaptive nature challenges conventional health technology assessment (HTA) frameworks, which are typically designed for static interventions. This review aims to assess how existing literature supports HTA-relevant evaluation of AI-based cardiovascular technologies and examine their alignment with the evidentiary requirements outlined in the…
gain_title: (none)
problem_title: Adaptive AI tools for cardiovascular care challenge conventional HTA frameworks designed for static interventions, resulting in indirect alignment with EU HTAR requirements and inconsistent engagement of cardiologists in evaluation.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: Adaptive AI tools for cardiovascular care challenge conventional HTA frameworks designed for static interventions, resulting in indirect alignment with EU HTAR requirements and inconsistent engagement of cardiologists in evaluation.
problem_evidence: its dynamic and adaptive nature challenges conventional health technology assessment (HTA) frameworks, which are typically designed for static interventions | stakeholder engagement, particularly with cardiologists, was inconsistently reported
quick_read: A systematic review published June 30, 2026 searched PubMed, Scopus and ScienceDirect for 2020-2025 literature on AI in cardiology and HTA. After screening 223 records, six studies were included, covering stroke outcome prediction, atrial fibrillation screening and wearable-based monitoring, supported by 17 documents, and compared against three HTA frameworks for EU HTAR alignment.

The synthesis matters because it documents a mismatch between increasing clinical use of cardiovascular AI and the capacity of existing HTA processes to evaluate dynamic, adaptive tools under new EU regulation. It remains uncertain how to operationalize lifecycle adaptability, post-deployment evaluation and consistent cardiologist engagement within HTA for these technologies.
limitation: Evidence base is limited to six studies meeting inclusion criteria after screening 223 records, and lifecycle considerations were underreported, limiting generalizability to broader cardiology AI deployment.
tag: Model-prefilled problem
key_points: Search covered PubMed, Scopus, and ScienceDirect for January 2020 to December 2025 and screened 223 records to include six studies. | Included studies covered stroke outcome prediction, atrial fibrillation screening and wearable-based monitoring and were supported by 17 documents. | Four studies incorporated real-world data, but most focused on clinical or economic performance without referencing formal HTA frameworks. | Comparative analysis examined three HTA frameworks for alignment with EU HTAR evidentiary requirements.
rundown: The review synthesized six studies identified from 223 records, covering applications such as stroke outcome prediction, atrial fibrillation screening and wearable-based monitoring, with four studies incorporating real-world data.

Authors performed narrative synthesis and comparative analysis of three HTA frameworks against EU HTAR requirements, finding most studies focused on clinical or economic performance without referencing formal HTA frameworks and noting stakeholder engagement was inconsistently reported.
sources:
- peer_reviewed | Annals of Translational Medicine | https://doi.org/10.21037/atm-2026-0052 | 2026-06-30
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