ReviewJournal of pharmacopuncture2025
National Health Insurance Data as a Research Tool in Korean Medicine: a guide to database utilization and methodological approaches.
Review in Journal of pharmacopuncture, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Impact of traditional Korean medicine on suicide prevention in depression: A nationwide 10-year follow-up study.Journal of traditional and complementary medicine · 2026Article
- Establishing an Active Vaccine Safety Surveillance System Using Large Scale Databases in Korea: Lessons and Scalable Insights for Global Application.Journal of Korean medical science · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: This study aims to provide a practical framework for Korean medicine (KM) researchers on effectively utilizing Korean National Health Insurance (NHI) data, focusing on database characteristics, access methods, and methodological considerations for generating high-quality evidence in KM research. Methods: This study analyzed the NHI data system structure, analyzing its two major databases the National Health Insurance Service (NHIS) and Health Insurance Review and Assessment Service (HIRA). We examined available data types, access protocols, and methodological approaches, with particular emphasis on their application in KM research. The study synthesized current challenges and opportunities specific to KM research using these databases. Results: Our analysis revealed three key findings 1) The distinct characteristics and complementary nature of NHIS and HIRA databases, with NHIS providing comprehensive longitudinal data suitable for cohort studies and HIRA offering detailed cross-sectional data optimal for utilization pattern analysis; 2) Multiple data access options including Sample Research DB and Customized Research DB from NHIS, and Patient Sample Data and Customized Research Data from HIRA, each with specific advantages for different research designs; 3) Critical methodological considerations for KM research, particularly addressing the limited coverage of KM services (0.8% of total covered items) and the high proportion of non-covered services in KM practices (24.2-49.2% across different institution types). Conclusion: For effective utilization of NHI data in KM research, we recommend 1) Implementing hybrid research designs that combine health insurance data with institutional data to overcome limited KM coverage; 2) Establishing clear operational definitions and applying appropriate statistical methods for bias adjustment; 3) Working toward developing a specialized Korean Medicine Utilization Cohort Database. These approaches can enhance the quality and generalizability of KM research using health insurance data, ultimately contributing to evidence-based practice in Korean medicine.
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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.