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

27 de maio de 2026 atualizado por: 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

Visão geral do estudo

Status

Recrutamento

Condições

Intervenção / Tratamento

Tipo de estudo

Intervencional

Inscrição (Estimado)

1180

Estágio

  • Não aplicável

Contactos e Locais

Esta seção fornece os detalhes de contato para aqueles que conduzem o estudo e informações sobre onde este estudo está sendo realizado.

Contato de estudo

Locais de estudo

      • Changhua, Taiwan
        • Recrutamento
        • Show Chwan Memorial Hospital
        • Contato:
      • Kaohsiung City, Taiwan
        • Recrutamento
        • Kaohsiung Medical University Chung-Ho Memorial Hospital
        • Contato:
      • Taichung, Taiwan
        • Recrutamento
        • Taichung Veterans General Hospital
        • Contato:
          • Kun Hui Chen, MD
          • Número de telefone: 04-23592525#5100
          • E-mail: khc@vghtc.gov.tw

Critérios de participação

Os pesquisadores procuram pessoas que se encaixem em uma determinada descrição, chamada de critérios de elegibilidade. Alguns exemplos desses critérios são a condição geral de saúde de uma pessoa ou tratamentos anteriores.

Critérios de elegibilidade

Idades elegíveis para estudo

  • Adulto
  • Adulto mais velho

Aceita Voluntários Saudáveis

Sim

Descrição

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

Plano de estudo

Esta seção fornece detalhes do plano de estudo, incluindo como o estudo é projetado e o que o estudo está medindo.

Como o estudo é projetado?

Detalhes do projeto

  • Finalidade Principal: Diagnóstico
  • Alocação: Randomizado
  • Modelo Intervencional: Atribuição Paralela
  • Mascaramento: Solteiro

Armas e Intervenções

Grupo de Participantes / Braço
Intervenção / Tratamento
Experimental: 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.
Sem intervenção: Control Group
Participants will receive standard-of-care (routine diagnosis) for osteoporosis assessment.

O que o estudo está medindo?

Medidas de resultados primários

Medida de resultado
Descrição da medida
Prazo
The primary objective is to evaluate the clinical effectiveness in terms of the improvement of BMD, of AI-guided diagnosis (VeriOsteo OP)
Prazo: 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)

Medidas de resultados secundários

Medida de resultado
Descrição da medida
Prazo
Incidence of Bone Fractures
Prazo: 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
Prazo: 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

Outras medidas de resultado

Medida de resultado
Descrição da medida
Prazo
Osteoporosis-related healthcare resource utilization
Prazo: 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
Prazo: 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

Colaboradores e Investigadores

É aqui que você encontrará pessoas e organizações envolvidas com este estudo.

Investigadores

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

Publicações e links úteis

A pessoa responsável por inserir informações sobre o estudo fornece voluntariamente essas publicações. Estes podem ser sobre qualquer coisa relacionada ao estudo.

Links úteis

Datas de registro do estudo

Essas datas acompanham o progresso do registro do estudo e os envios de resumo dos resultados para ClinicalTrials.gov. Os registros do estudo e os resultados relatados são revisados ​​pela National Library of Medicine (NLM) para garantir que atendam aos padrões específicos de controle de qualidade antes de serem publicados no site público.

Datas Principais do Estudo

Início do estudo (Real)

13 de março de 2026

Conclusão Primária (Estimado)

17 de junho de 2026

Conclusão do estudo (Estimado)

12 de novembro de 2026

Datas de inscrição no estudo

Enviado pela primeira vez

14 de maio de 2026

Enviado pela primeira vez que atendeu aos critérios de CQ

27 de maio de 2026

Primeira postagem (Real)

2 de junho de 2026

Atualizações de registro de estudo

Última Atualização Postada (Real)

2 de junho de 2026

Última atualização enviada que atendeu aos critérios de controle de qualidade

27 de maio de 2026

Última verificação

1 de maio de 2026

Mais Informações

Termos relacionados a este estudo

Plano para dados de participantes individuais (IPD)

Planeja compartilhar dados de participantes individuais (IPD)?

NÃO

Descrição do plano 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.

Informações sobre medicamentos e dispositivos, documentos de estudo

Estuda um medicamento regulamentado pela FDA dos EUA

Não

Estuda um produto de dispositivo regulamentado pela FDA dos EUA

Não

Essas informações foram obtidas diretamente do site clinicaltrials.gov sem nenhuma alteração. Se você tiver alguma solicitação para alterar, remover ou atualizar os detalhes do seu estudo, entre em contato com register@clinicaltrials.gov. Assim que uma alteração for implementada em clinicaltrials.gov, ela também será atualizada automaticamente em nosso site .

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