Taiwan's National Health Insurance Research Database (NHIRD): in the Era of Artificial Intelligence, Causal Inference, and Data Security

Cheng-Yang Hsieh; Shih-Chieh Shao; Sheng-Feng Sung; Miyuki Hsing-Chun Hsieh; Daniel Hsiang-Te Tsai; Swu-Jane Lin; Edward Chia-Cheng Lai

doi:10.2147/CLEP.S553894

Taiwan's National Health Insurance Research Database (NHIRD): in the Era of Artificial Intelligence, Causal Inference, and Data Security

Clin Epidemiol. 2025 Nov 25:17:967-981. doi: 10.2147/CLEP.S553894. eCollection 2025.

Authors

Cheng-Yang Hsieh^{1

2}, Shih-Chieh Shao^{2

3

4}, Sheng-Feng Sung^{5

6}, Miyuki Hsing-Chun Hsieh^{2

3}, Daniel Hsiang-Te Tsai^{2

3}, Swu-Jane Lin⁷, Edward Chia-Cheng Lai^{2

3}

Affiliations

¹ Department of Neurology, Tainan Sin Lau Hospital, Tainan, Taiwan.
² School of Pharmacy, Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
³ Population Health Data Center, National Cheng Kung University, Tainan, Taiwan.
⁴ Department of Pharmacy, Keelung Chang Gung Memorial Hospital, Keelung, Taiwan.
⁵ Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan.
⁶ Department of Nursing, Fooyin University, Kaohsiung, Taiwan.
⁷ Department of Pharmacy Systems, Outcomes and Policy, University of Illinois Chicago, Chicago, IL, USA.

Abstract

Background: Taiwan's National Health Insurance Research Database (NHIRD) has evolved into a cornerstone of real-world evidence generation. As Taiwan's National Health Insurance program reaches its 30th anniversary, a comprehensive reassessment of the NHIRD's development, challenges and future directions is warranted.

Objective: To provide an updated review of the NHIRD.

Methods: We conducted a narrative review of Taiwan's NHIRD, synthesizing published studies, government reports, and policy documents from 2019 through 2024. We summarized developments related to database infrastructure, data collection, validation studies, linkage strategies, governance reforms and interoperability initiatives, with a particular focus on their implications for real-world evidence generation and AI-driven research.

Results: The NHIRD has additionally incorporated structured laboratory results and medical imaging data, significantly broadening its research capabilities. Validation studies have demonstrated the reliability of International Classification of Diseases, 10th Revision, Clinical Modification codes across various conditions, reinforcing the database's applicability for epidemiological research. Integration efforts with national registries, surveys and electronic medical records have further enhanced the depth and accuracy of clinical outcome measurements. Nonetheless, critical challenges persist, including data standardization inconsistencies, cybersecurity vulnerabilities, and heightened scrutiny following constitutional court rulings on data governance and privacy rights. In response, Taiwan's Ministry of Health and Welfare has launched initiatives to address these concerns, notably through the development of a Fast Healthcare Interoperability Resources (FHIR)-based data infrastructure aimed at improving interoperability, data security, and artificial intelligence (AI)-readiness to balance ethical governance with scientific innovation.

Conclusion: The NHIRD's transformation over three decades underscores the importance of continuous investment in data quality, privacy protection, and interoperability. With sustained reforms, the NHIRD will be poised to remain a leading resource for real-world evidence generation and to contribute meaningfully to global health and digital medicine.

Keywords: ICD-10 validation; National Health Insurance Research Database; data linkage; health claims data; laboratory data; medical imaging; real-world evidence.

Publication types

Review