Population-based comparison of traditional medicine use in adult patients with allergic rhinitis between South Korea and Taiwan
Bibliographic record
Abstract
BACKGROUND: As the number of people seeking to use traditional medicine to treat common diseases is increasing worldwide, the quantity of information that needs to be analyzed is also increasing. Traditional medicine is commonly used in South Korea and Taiwan for treating allergic rhinitis and is covered by the National Health Insurance in both countries. To date, there has been no nationwide comparison of traditional medicine used to treat patients with allergic rhinitis between these two countries. METHODS: This study analyzed the National Health Insurance cohort database in 2011 from South Korea and Taiwan to compare the utilization pattern of traditional medicine in adult patients with allergic rhinitis. RESULTS: During 2011, there were significantly more adult patients with allergic rhinitis using traditional medicine in Taiwan (9898/54,555, 18.1%) than in South Korea (533/11,761, 0.5%). Users of traditional medicine from both countries were more prevalent among women, the younger population aged 20-39 years, and among people who visited traditional medicine clinics more frequently than hospitals. The most common traditional medicine treatment modality for allergic rhinitis was acupuncture in South Korea, while powdered herbal preparations was most commonly used in Taiwan. Xiaoqinglong-tang (Socheongryongtong-tang) was the most commonly used herbal preparation in South Korea, while Xinyi-san (Sinyi-san) was the most commonly prescribed herbal preparation in Taiwan. CONCLUSION: An analysis of the National Health Insurance database of South Korea and Taiwan revealed different utilization patterns of traditional medicine in adult patients with allergic rhinitis between the two countries. We believe these phenomena are due to the difference in the national healthcare systems in both countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".