Frequency and pattern of Chinese herbal medicine prescriptions for urticaria in Taiwan during 2009: analysis of the national health insurance database

Abstract

BackgroundLarge-scale pharmaco-epidemiological studies of Chinese herbal medicine (CHM) for treatment of urticaria are few, even though clinical trials showed some CHM are effective. The purpose of this study was to explore the frequencies and patterns of CHM prescriptions for urticaria by analysing the population-based CHM database in Taiwan.MethodsThis study was linked to and processed through the complete traditional CHM database of the National Health Insurance Research Database in Taiwan during 2009. We calculated the frequencies and patterns of CHM prescriptions used for treatment of urticaria, of which the diagnosis was defined as the single ICD-9 Code of 708. Frequent itemset mining, as applied to data mining, was used to analyse co-prescription of CHM for patients with urticaria.ResultsThere were 37,386 subjects who visited traditional Chinese Medicine clinics for urticaria in Taiwan during 2009 and received a total of 95,765 CHM prescriptions. Subjects between 18 and 35 years of age comprised the largest number of those treated (32.76%). In addition, women used CHM for urticaria more frequently than men (female:male = 1.94:1). There was an average of 5.54 items prescribed in the form of either individual Chinese herbs or a formula in a single CHM prescription for urticaria. Bai-Xian-Pi (Dictamnus dasycarpus Turcz) was the most commonly prescribed single Chinese herb while Xiao-Feng San was the most commonly prescribed Chinese herbal formula. The most commonly prescribed CHM drug combination was Xiao-Feng San plus Bai-Xian-Pi while the most commonly prescribed triple drug combination was Xiao-Feng San, Bai-Xian-Pi, and Di-Fu Zi (Kochia scoparia).ConclusionsIn view of the popularity of CHM such as Xiao-Feng San prescribed for the wind-heat pattern of urticaria in this study, a large-scale, randomized clinical trial is warranted to research their efficacy and safety.

Traditional Chinese Medicine Use among Patients with Psoriasis in Taiwan: A Nationwide Population‐Based Study

“…In accordance with other studies in atopic dermatitis or urticaria [13, 36], CHM is the most common treatment approaches. We found that only very few patients received acupuncture therapy.…”

“…The second commonly prescribed herbal formula is Xiao-feng-san (Wind-Dispersing Powder). It has long been used to treat skin problems in clinical practice such as atopic dermatitis [13] or urticaria [36]. In a clinical trial conducted in our institution, Xiao-feng-san was found to improve refractory atopic dermatitis symptom and with no side effects [39].…”

Indigenous Therapies for Skin Diseases in Sub‐Saharan Africa

“…In a study of atopic dermatitis in China, the authors reported a high percentage use of herbal medications in contrast to this study (Chen, Lin, Hu, & Chen, ). China is a country where alternative medicine is readily practiced (Chien, Tseng, Hsu, Lai, & Weng, ; Lin et al, ; Tsang et al, ). Among those who admitted to the use of herbal medications, this was mostly oral.…”

“…China is a country where alternative medicine is readily practiced (Chien, Tseng, Hsu, Lai, & Weng, 2013;Lin et al, 2014;Tsang et al, 2017). Among those who admitted to the use of herbal medications, this was mostly oral.…”

Traditional Chinese medicine treatments for upper respiratory tract infections/common colds in Taiwan

“…The method of association rule was often used in large databases for finding frequent item sets which are the lists of commonly displayed together or finding the strong relationships between two items [17,18]. This method has been used extensively in various published studies using the Taiwan NHIRD [19][20][21][22]. Each single herb or Chinese medicine formula was set as an independent fixed prescription to estimate the support probability of all of the prescriptions in the data set containing the fixed prescription in order to measure how frequently the association rule occurred in the data set.…”