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Artificial Intelligence-Guided Diagnosis for High-Risk Osteoporosis Populations: A Pragmatic Randomized Clinical Trial

27 mai 2026 mis à jour par: Kun-Hui Chen, Taichung Veterans General Hospital

Project Summary

I. Project Objectives

With the rapid advancement of medical technology, smart medical devices have become one of the key components of modern healthcare. However, integrating these emerging technologies into the national health insurance (NHI) reimbursement system while ensuring their clinical value and economic benefits remains a major challenge worldwide.

The primary goal of this project is to assist commercialized smart medical device products-those that have passed TFDA review and seek NHI reimbursement-in conducting comprehensive evaluations of their clinical effectiveness and medical economic impact. Through scientific data and standardized impact assessment procedures, the project aims to provide localized evidence to support reimbursement policy decisions and facilitate the market adoption of smart medical technologies. Ultimately, this project seeks to balance therapeutic efficacy and cost control, offering a scientific foundation for NHI decision-making and paving the way for the sustainable development of AI-driven healthcare innovations.

II. Implementation Methods

  1. Multi-center Collaborative Network

    This project will be led by Taichung Veterans General Hospital (TCVGH) as the principal site, with collaboration from Kaohsiung Medical University Chung-Ho Memorial Hospital and Changhua Show Chwan Memorial Hospital. This cross-institutional, cross-regional alliance ensures diverse clinical samples, enhances the representativeness of study results, and allows evaluation of AI medical devices across different healthcare systems and environments.

  2. Clinical Trial Design and Implementation for Smart Medical Devices

    The project will design and execute systematic clinical trials for smart medical devices using methodologies such as randomized controlled trials (RCTs), before-and-after studies, pragmatic RCTs (PCTs), cluster RCTs, and stepped-wedge RCTs. These rigorous designs will ensure scientific validity, reproducibility, and practical feasibility in real-world clinical settings.

  3. Health Economic Evaluation

    A key component of this project is the medical economic assessment, conducted by experienced health economists through cost-effectiveness analysis. The evaluation will focus on how smart medical devices reduce healthcare costs, improve diagnostic efficiency, and enhance treatment outcomes, quantifying their economic value within the NHI system. This evidence will guide policy makers in making data-driven reimbursement decisions.

  4. Standardized Impact Assessment Process

    To ensure high-quality research, the project will establish a comprehensive standardized impact assessment framework covering trial design, data collection, statistical analysis, economic evaluation, and ethical review. This standardized approach not only improves the precision of the study but also accelerates the clinical translation of AI medical devices through streamlined application and review processes.

  5. Research Case Study and Clinical Application

    The featured case study in this project is "VeriOsteo OP® Smart Bone Screening System," which targets early osteoporosis screening among adults aged 40 to 80 years in high-risk groups. This study will evaluate the clinical accuracy of AI-based osteoporosis screening and assess its economic contribution to healthcare cost reduction. The findings will directly inform the Ministry of Health and Welfare's NHI Administration in formulating reimbursement standards for AI medical devices.

  6. Data Sharing and Information Security

    Throughout the project, all research data collection, exchange, and sharing will strictly adhere to cybersecurity and privacy regulations. The AI models involved will undergo validation to ensure the reliability and scientific rigor of the results. Furthermore, the project will promote collaboration between manufacturers and healthcare institutions to support the adoption of smart medical technologies.

  7. Final Outcomes and Future Development

The final deliverables will include a comprehensive evaluation report on the clinical and economic performance of the AI medical device, along with recommendations for NHI reimbursement application. The results will provide a reference model for future AI medical devices entering the reimbursement system and further advance the field of smart healthcare. In the long term, the center aims to expand its research to other disease domains while strengthening data security and ethical oversight to ensure the feasibility and credibility of AI applications in clinical practice.

III. Expected Outcomes and Future Vision

By implementing a multi-center collaborative framework, this project aims to promote clinical adoption and economic evaluation of smart medical devices, offering concrete data to support NHI policy-making. Over time, the project is expected to establish a robust evaluation system for AI medical devices, facilitate broader market adoption, and enhance patient outcomes whi

Aperçu de l'étude

Statut

Recrutement

Les conditions

Intervention / Traitement

Type d'étude

Interventionnel

Inscription (Estimé)

1180

Phase

  • N'est pas applicable

Contacts et emplacements

Cette section fournit les coordonnées de ceux qui mènent l'étude et des informations sur le lieu où cette étude est menée.

Coordonnées de l'étude

Lieux d'étude

      • Changhua, Taïwan
        • Recrutement
        • Show Chwan Memorial Hospital
        • Contact:
      • Kaohsiung City, Taïwan
        • Recrutement
        • Kaohsiung Medical University Chung-Ho Memorial Hospital
        • Contact:
      • Taichung, Taïwan
        • Recrutement
        • Taichung Veterans General Hospital
        • Contact:
          • Kun Hui Chen, MD
          • Numéro de téléphone: 04-23592525#5100
          • E-mail: khc@vghtc.gov.tw

Critères de participation

Les chercheurs recherchent des personnes qui correspondent à une certaine description, appelée critères d'éligibilité. Certains exemples de ces critères sont l'état de santé général d'une personne ou des traitements antérieurs.

Critère d'éligibilité

Âges éligibles pour étudier

  • Adulte
  • Adulte plus âgé

Accepte les volontaires sains

Oui

La description

Inclusion Criteria:

  • Aged between 40 to 80 years old
  • Identified as high-risk by the Osteoporosis Self-Assessment Tool for Taiwan Postmenopausal Women (OSTAi) <-1 or Male Osteoporosis Self-Assessment Tool for Taiwan (MOSTAi) ≦11 based on the individual's age and weight (kg)
  • Had chest x-ray within one year

Exclusion Criteria:

  • Age < 40 years old
  • Age >80 years old
  • BMI< 18 kg/m2or >30 kg/m2
  • Pregnant in prior one year
  • Recorded diagnosis of osteoporosis within the past two years
  • History of prior DXA imaging (prior quantification of BMD) within 2 years
  • History of metabolic bone disease

Plan d'étude

Cette section fournit des détails sur le plan d'étude, y compris la façon dont l'étude est conçue et ce que l'étude mesure.

Comment l'étude est-elle conçue ?

Détails de conception

  • Objectif principal: Diagnostique
  • Répartition: Randomisé
  • Modèle interventionnel: Affectation parallèle
  • Masquage: Seul

Armes et Interventions

Groupe de participants / Bras
Intervention / Traitement
Expérimental: Intervention Group
Participants will receive AI-guided diagnosis for osteoporosis risk assessment. This group follows a 2:1 randomization ratio.
Participants in the intervention group undergo VeriOsteo OP AI assessment followed by DXA confirmation. The AI system generates a diagnostic report identifying individuals at high risk for osteoporosis. Results are used to guide clinical decision-making and evaluate the diagnostic consistency between the AI-guided system and the gold-standard DXA assessment.
Aucune intervention: Control Group
Participants will receive standard-of-care (routine diagnosis) for osteoporosis assessment.

Que mesure l'étude ?

Principaux critères de jugement

Mesure des résultats
Description de la mesure
Délai
The primary objective is to evaluate the clinical effectiveness in terms of the improvement of BMD, of AI-guided diagnosis (VeriOsteo OP)
Délai: Up to the end of follow-up (average 18 months)
The primary endpoint of this study is the change in Bone Mineral Density (BMD) expressed as a T-score, measured by Dual-energy X-ray Absorptiometry (DXA). The T-score is a standardized metric comparing bone density to a healthy young adult. While there is no theoretical absolute minimum or maximum value, typical clinical values range from -5.0 to +2.0. According to the International Osteoporosis Foundation (IOF) and Taiwan 2020 guidelines, a T-score of -1.0 or higher is normal, between -1.0 and -2.5 indicates osteopenia, and a T-score of -2.5 or lower (≤ -2.5) indicates osteoporosis. Therefore, a higher (more positive) T-score represents a better outcome (higher bone density). To avoid inflating the detection rate for osteoporosis based on the protocolized DXA at baseline in the intervention arm, a positive AI screen was required to be present to count the chest X-ray findings for the purpose of the primary end point.
Up to the end of follow-up (average 18 months)

Mesures de résultats secondaires

Mesure des résultats
Description de la mesure
Délai
Incidence of Bone Fractures
Délai: Every 6 months up to 18 months
he incidence of bone fractures, including hip fracture, vertebral fracture, wrist fracture, and other fractures. Bone fractures will be identified from the participant interviews and confirmed by International Classification of Diseases (ICD) codes extracted from electronic health records (EHRs) across the three study sites.
Every 6 months up to 18 months
All-Cause Mortality
Délai: Every 6 months up to 18 months
The incidence of all-cause death. Participant status will be followed by telephone and verified through electronic health records (EHRs) from the three study sites.
Every 6 months up to 18 months

Autres mesures de résultats

Mesure des résultats
Description de la mesure
Délai
Osteoporosis-related healthcare resource utilization
Délai: 12th month
To analyze the total number of healthcare resource utilizations related to osteoporosis, including the combined counts of outpatient visits, emergency department visits, and hospitalizations. Data will be collected through a structured questionnaire via telephone interview.
12th month
Osteoporosis-related medical costs
Délai: 12th month
To evaluate the direct medical costs associated with osteoporosis healthcare resource utilization (expressed in New Taiwan Dollars (TWD ). Data will be collected through a structured questionnaire via telephone interview.
12th month

Collaborateurs et enquêteurs

C'est ici que vous trouverez les personnes et les organisations impliquées dans cette étude.

Les enquêteurs

  • Chercheur principal: Kun Hui Chen, MD, Taichung Veterans General Hospital

Publications et liens utiles

La personne responsable de la saisie des informations sur l'étude fournit volontairement ces publications. Il peut s'agir de tout ce qui concerne l'étude.

Liens utiles

Dates d'enregistrement des études

Ces dates suivent la progression des dossiers d'étude et des soumissions de résultats sommaires à ClinicalTrials.gov. Les dossiers d'étude et les résultats rapportés sont examinés par la Bibliothèque nationale de médecine (NLM) pour s'assurer qu'ils répondent à des normes de contrôle de qualité spécifiques avant d'être publiés sur le site Web public.

Dates principales de l'étude

Début de l'étude (Réel)

13 mars 2026

Achèvement primaire (Estimé)

17 juin 2026

Achèvement de l'étude (Estimé)

12 novembre 2026

Dates d'inscription aux études

Première soumission

14 mai 2026

Première soumission répondant aux critères de contrôle qualité

27 mai 2026

Première publication (Réel)

2 juin 2026

Mises à jour des dossiers d'étude

Dernière mise à jour publiée (Réel)

2 juin 2026

Dernière mise à jour soumise répondant aux critères de contrôle qualité

27 mai 2026

Dernière vérification

1 mai 2026

Plus d'information

Termes liés à cette étude

Plan pour les données individuelles des participants (IPD)

Prévoyez-vous de partager les données individuelles des participants (DPI) ?

NON

Description du régime IPD

As this is a multi-center study, the sharing of individual participant data (IPD) would require joint approval from the Institutional Review Boards (IRBs) of all three participating hospitals. Given the complex regulatory procedures and strict privacy protocols involved, the data will not be made publicly available at this time.

Informations sur les médicaments et les dispositifs, documents d'étude

Étudie un produit pharmaceutique réglementé par la FDA américaine

Non

Étudie un produit d'appareil réglementé par la FDA américaine

Non

Ces informations ont été extraites directement du site Web clinicaltrials.gov sans aucune modification. Si vous avez des demandes de modification, de suppression ou de mise à jour des détails de votre étude, veuillez contacter register@clinicaltrials.gov. Dès qu'un changement est mis en œuvre sur clinicaltrials.gov, il sera également mis à jour automatiquement sur notre site Web .

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