Traditional Chinese Medicine Practitioners Research Articles

Moments of ‘touch’ as a way for mental support in Traditional Chinese Medicine consultations: Analysis of the interactional process of co-constructing understanding of the patient’s body conditions in Hong Kong

Traditional Chinese Medicine (TCM) is a growing phenomenon around the world. However, despite its historical role in Chinese society, there has been limited research on exploring the nature of TCM practitioner-patient interactions in the Chinese context. This study used 10 hours audio recordings of consultations to elucidate how a TCM practitioner used moments of ‘touch’ (where the term is used to represent the nature of holistic TCM interactions) for co-constructing understanding of the patients’ body conditions. In these moments, the practitioner interacted with patients in order to explore their ‘Zheng’, the outcome of an in-depth analysis of all symptoms such as an imbalance in the pulse, lack of energy. This study illustrates how TCM practitioner strategically used discourse features in shaping the patient’ understanding of their current body’s conditions, and thus opened up space to elaborate their concerns or seek clarifications, leading to a holistic understanding and compliance with the recommended treatments. Specifically, the data show how the TCM practitioner through using the moments of ‘touch’ to shape the ongoing discourse so that the patients can have a better understanding of their illnesses. The results suggest that the long-term relationships between TCM practitioners and their patients can be developed through recognising the specific communication strategies used by the TCM practitioners in shaping the patient’s understanding. If TCM practitioners can learn better communication skills, it will lead to better quality of interactions and reach better clinical outcomes such as high patient satisfaction and compliance with treatments.

The spread of foreign toxicology along the Silk Road during Medieval China

ABSTRACT Throughout the Middle Ages, antidotes and toxicological learning originating from foreign territories were conveyed along the Silk Road (via both land and maritime routes) – propelled by diplomacy, religious expansion, and trade – eventually into China. In this article, such threads of remnant text that have been discovered along the Silk Road are pieced together to reveal the story of foreign toxicology’s spread and use in China. Accounts aplenty of this trajectory fill the Dunhuang manuscripts and Traditional Chinese Medicine records handed down to posterity. These documents perhaps evince the willingness of Chinese physicians to accept foreign toxicological direction even while engaged upon their own course of development in the field and may even indicate their endorsement of certain imported concepts. What resulted was a broader, multifaceted approach to toxicology by practitioners of Traditional Chinese Medicine. The hope is to better understand Chinese medicine culture’s richness and diversity.

Artificial Intelligence-Based Traditional Chinese Medicine Assistive Diagnostic System: Validation Study.

BackgroundArtificial intelligence–based assistive diagnostic systems imitate the deductive reasoning process of a human physician in biomedical disease diagnosis and treatment decision making. While impressive progress in this area has been reported, most of the reported successes are applications of artificial intelligence in Western medicine. The application of artificial intelligence in traditional Chinese medicine has lagged mainly because traditional Chinese medicine practitioners need to perform syndrome differentiation as well as biomedical disease diagnosis before a treatment decision can be made. Syndrome, a concept unique to traditional Chinese medicine, is an abstraction of a variety of signs and symptoms. The fact that the relationship between diseases and syndromes is not one-to-one but rather many-to-many makes it very challenging for a machine to perform syndrome predictions. So far, only a handful of artificial intelligence–based assistive traditional Chinese medicine diagnostic models have been reported, and they are limited in application to a single disease-type.ObjectiveThe objective was to develop an artificial intelligence–based assistive diagnostic system capable of diagnosing multiple types of diseases that are common in traditional Chinese medicine, given a patient’s electronic health record notes. The system was designed to simultaneously diagnose the disease and produce a list of corresponding syndromes.MethodsUnstructured freestyle electronic health record notes were processed by natural language processing techniques to extract clinical information such as signs and symptoms which were represented by named entities. Natural language processing used a recurrent neural network model called bidirectional long short-term memory network–conditional random forest. A convolutional neural network was then used to predict the disease-type out of 187 diseases in traditional Chinese medicine. A novel traditional Chinese medicine syndrome prediction method—an integrated learning model—was used to produce a corresponding list of probable syndromes. By following a majority-rule voting method, the integrated learning model for syndrome prediction can take advantage of four existing prediction methods (back propagation, random forest, extreme gradient boosting, and support vector classifier) while avoiding their respective weaknesses which resulted in a consistently high prediction accuracy.ResultsA data set consisting of 22,984 electronic health records from Guanganmen Hospital of the China Academy of Chinese Medical Sciences that were collected between January 1, 2017 and September 7, 2018 was used. The data set contained a total of 187 diseases that are commonly diagnosed in traditional Chinese medicine. The diagnostic system was designed to be able to detect any one of the 187 disease-types. The data set was partitioned into a training set, a validation set, and a testing set in a ratio of 8:1:1. Test results suggested that the proposed system had a good diagnostic accuracy and a strong capability for generalization. The disease-type prediction accuracies of the top one, top three, and top five were 80.5%, 91.6%, and 94.2%, respectively.ConclusionsThe main contributions of the artificial intelligence–based traditional Chinese medicine assistive diagnostic system proposed in this paper are that 187 commonly known traditional Chinese medicine diseases can be diagnosed and a novel prediction method called an integrated learning model is demonstrated. This new prediction method outperformed all four existing methods in our preliminary experimental results. With further improvement of the algorithms and the availability of additional electronic health record data, it is expected that a wider range of traditional Chinese medicine disease-types could be diagnosed and that better diagnostic accuracies could be achieved.

Application of Neural Network and Cluster Analyses to Differentiate TCM Patterns in Patients With Breast Cancer.

Background and PurposePattern differentiation is a critical element of the prescription process for Traditional Chinese Medicine (TCM) practitioners. Application of advanced machine learning techniques will enhance the effectiveness of TCM in clinical practice. The aim of this study is to explore the relationships between clinical features and TCM patterns in breast cancer patients.MethodsThe dataset of breast cancer patients receiving TCM treatment was recruited from a single medical center. We utilized a neural network model to standardize terminologies and address TCM pattern differentiation in breast cancer cases. Cluster analysis was applied to classify the clinical features in the breast cancer patient dataset. To evaluate the performance of the proposed method, we further compared the TCM patterns to therapeutic principles of Chinese herbal medication in Taiwan.ResultsA total of 2,738 breast cancer cases were recruited and standardized. They were divided into 5 groups according to clinical features via cluster analysis. The pattern differentiation model revealed that liver-gallbladder dampness-heat was the primary TCM pattern identified in patients. The main therapeutic goals of the top 10 Chinese herbal medicines prescribed for breast cancer patients were to clear heat, drain dampness, and detoxify. These results demonstrated that the neural network successfully identified patterns from a dataset similar to the prescriptions of TCM clinical practitioners.ConclusionThis is the first study using machine-learning methodology to standardize and analyze TCM electronic medical records. The patterns revealed by the analyses were highly correlated with the therapeutic principles of TCM practitioners. Machine learning technology could assist TCM practitioners to comprehensively differentiate patterns and identify effective Chinese herbal medicine treatments in clinical practice.

The dilemma and hope of Traditional Chinese Medicine practitioners in China

The dilemma and hope of Traditional Chinese Medicine practitioners in China

Development and validation of a diagnostic risk score for assessing a TCM condition, Protective Qi Deficiency, in adults

IntroductionStandardized diagnosis is required and therefore advocated for evidence-based research in Traditional Chinese Medicine (TCM). In this study, we aimed to standardize and validate a protocol that assesses Protective Qi Deficiency (PQD), a common TCM condition that predisposes individuals to pathogenic invasion. Methods3 TCM practitioners evaluated 151 participants for PQD status via conventional TCM methods and a standardized protocol consisting of 13 PQD-related variables identified as potential predictors of a diagnostic algorithm of PQD. The collected data served as the training dataset to determine which predictors that significantly contributed to PQD diagnosis and their coefficients in the resulting algorithm. The algorithm was then reviewed and modified by an independent expert panel following the Delphi method, and subsequently validated using a separate validation dataset (n = 56). ResultsThe Delphi-modified algorithm contained 8 predictor variables and accounted for 73.4 % of the PQD variance in the training dataset. Using the validation dataset, the algorithm predicted a TCM practitioner’s conventional diagnosis of PQD with a high degree of accuracy. The protocol also demonstrated significant precision as demonstrated by a high between-practitioner consistency (0.993) measured by intraclass correlation coefficient. ConclusionOur study provides evidence that, through rigorous standardization, quantitation, and statistical analysis, reliable assessment of a TCM concept can be achieved and applied for researching TCM therapeutics. Nonetheless, the generalizability of these findings need to be tested in future studies with increased numbers of practitioners and participants and in studies conducted at multiple geographical venues.

Understanding the Traditional Chinese Medicine (TCM) consultation: Why do patients adhere to treatment?

Backgroundand purpose: Adherence is an issue that affects Complementary and Alternative Medicine (CAM) and conventional medicine practitioners, whereby approximately half of the patients do not take their medicines or remedies as prescribed. The consultation is an opportune area where practitioners can have an impact on patient adherence to treatment. As such, research was undertaken to explore this in depth within one CAM. The aim of the study was to understand the Traditional Chinese Medicine (TCM) consultation process that occurs in relation to adherence and develop a consultation model health professionals can use. Materials and methodsA classical grounded theory approach was employed to semi-structured interviews of TCM practitioners and patients along with observations of their consultations. Sampling was theoretical and by snowball in the United Kingdom. NVivo 11 was used to assist with analysis of the transcribed interviews and observations. ResultsSeven TCM practitioners and twenty-eight patients were recruited. TCM practitioners built a therapeutic relationship through the consultation by enabling patients to feel comfortable, valued as individuals which incorporated feeling understood and known, as well as supported in the management of their health. Fundamentally, patients needed to feel cared for and have trust in their TCM practitioner for the therapeutic relationship to be established. This motivated patients to continue with treatment. ConclusionThe TCM Consultation Model for Adherence was developed to conceptualise the consultation process that occurs in relation to adherence. It can be used to encourage patient persistence with treatment by TCM practitioners and potentially other health professionals.

The regulation of complementary and alternative medicine professions in Ontario, Canada

BackgroundThis paper explains the regulation of complementary and alternative medicine (CAM) health professions, through the comparison of four distinct examples in Ontario, Canada including: chiropractors, naturopaths, homeopaths, and traditional Chinese medicine (TCM) practitioners. MethodsThis study analyzes the agenda setting and formulation stage of the policy process. In other words, it explores what happened between stakeholders before each of these CAM professions achieved regulation. Alford’s model of dominant, challenging and repressed structured interests (DSIs, CSIs, and RSIs respectively) is used to describe the competition between various players within the healthcare system and their position in the health policy process. ResultsAll four CAM professions have existed as a RSI at some point in their history, however, over the last century has sought to align themselves with various (or even become) challenging structural interests (CSIs) in order to be recognized as a regulated health profession. Dominant structural interests (DSIs), particularly the medical profession, initially largely ignored these professions’ practices, unless sufficient public support of CAM practitioners’ therapies warranted them to consider the need to regulate them. ConclusionUnregulated CAM professions may increase their likelihood of becoming regulated if they: (1) gain popularity/strong support from patients or the general public, (2) organize themselves sufficiently that they pose a direct threat to one or more scopes of practice desirable by the DSIs and/or (3) are willing to adopt standards in education, training, and ethics that may [initially] reduce their scope of practice or profession’s membership or slow their profession’s growth.

Review on the systems biology research of Yin-deficiency-heat syndrome in traditional Chinese medicine.

Traditional Chinese medicine (TCM) is a systematic medical method that has existed for more than 3,000 years. Unlike Western medicine, the disease diagnosis in TCM is carried out by inspection, auscultation, olfaction, interrogation, and palpation. The patient is then treated according to the disease and corresponding TCM syndrome. However, the development of Chinese medicine is stagnated, partially because it can be influenced by subjective factors, such as the experience and knowledge of TCM practitioners, and there is a lack of relevant biological research on TCM syndromes. Yin-deficiency-heat (YDH) syndrome in TCM is characterized by a series of pathological changes caused by the insufficiency of Yin-fluid, inability to moisturize, and the failure to suppress Yang. In recent years, systems biology research on TCM syndromes has gradually become the focus of TCM research, including syndrome differentiation and functional research using systems biology methodologies such as proteomics, transcriptomics, and metabolomics. This journal aims to publish a series of issues on the systems biology research of TCM syndromes that can provide biological indicators for the syndrome differentiation of YDH syndrome and can provide perspectives on the biological research of YDH syndrome.

The Diagnosis Performance of the TCM Syndromes of Irritable Bowel Syndrome by Gastroenterologists Based on Modified Simple Criteria Compared to TCM Practitioners: A Prospective, Multicenter Preliminary Study.

Purpose Traditional Chinese medicine (TCM) including Chinese patent medicine has been widely used to treat irritable bowel syndrome (IBS). Syndrome differentiation is the essence of TCM. However, the diagnostic ability of gastroenterologists to detect TCM syndromes in IBS in China remains unknown. The aim of this study was to investigate the ability of gastroenterologists to diagnose the TCM syndromes of IBS based on modified simple criteria compared with TCM practitioners. Methods Patients meeting the Rome III criteria for IBS-D or IBS-C were recruited from six tertiary referral centers between January 2016 and December 2017. After learning the diagnosis criteria of the TCM syndromes in IBS, gastroenterologists first diagnosed the syndromes of the enrolled patients. Subsequently, the patients were diagnosed by TCM practitioners. The rate of agreement between the gastroenterologists and TCM practitioners was analyzed. In addition, demographic data and the distribution of TCM syndrome types in IBS were also analyzed. Results A total of 178 patients (93 males and 85 females), including 131 patients with IBS-D and 47 patients with IBS-C, were enrolled in this study. The rate of agreement of the syndrome diagnosis between the gastroenterologists and TCM practitioners was 84.3%. The diagnosis consistency rates among IBS-D patients and IBS-C patients were 87.0% and 76.5%, respectively. The most common TCM syndrome type in IBS-D patients was liver depression and spleen deficiency syndrome (27.5%), followed by spleen-yang deficiency syndrome (19.8%). Dryness and heat in intestine syndrome was the most common TCM syndrome in IBS-C patients (57.4%). Conclusions Gastroenterologists had good diagnostic agreement with TCM practitioners for diagnosing TCM syndrome types in IBS after learning the diagnostic criteria. This knowledge can aid gastroenterologists in selecting suitable Chinese patent medicine to treat IBS.

Testing the Traditional Chinese Medicine Consultation Model for Adherence in Complementary and Alternative Medicine.

The Traditional Chinese Medicine (TCM) Consultation Model for Adherence conceptualises the consultation process specific to patient adherence. It can be used to improve patient persistence with treatment by TCM practitioners and possibly other health professionals. The aim of this research was to determine the applicability of the TCM Consultation Model for Adherence in the wider complementary and alternative medicine (CAM) setting. A survey containing validated questionnaires and items developed specifically to test the model was administered online in the United Kingdom. SPSS 25 was used to perform Spearman's correlations and Mann–Whitney U tests on the data. In total, 101 patients completed the survey. The results showed that patients having a therapeutic relationship and trusting in their practitioner was associated with overall adherence to CAM, while patients feeling supported was associated with all types of adherence to CAM. Specific behaviours of the TCM Consultation Model for Adherence that were positively correlated with adherence to CAM were identified. They could potentially be used by CAM practitioners to improve their patients' adherence with treatment.

Veterinary acutherapy in management of musculoskeletal disorders: An eye-opener to the developing countries' veterinarians.

Traditional Chinese medicine practitioners believed that the maintenance of the health status of any individual or animal is by the harmonious flow of Chi (life force) along a pathway known as the meridian. Interruption or blockage of Chi brings about disorders, pain, and diseases. Acutherapy, therefore, aims at correcting the interruption or blockage of the harmonious flow of Chi along the meridian to restore the healthy condition of the body system. This correction could be accomplished by either acupuncture or acupressure, and are both collectively referred to as acutherapy. This form of therapy has been used in both humans and animals for several decades. It is, however, just gaining popularity in the treatment of humans and is still not yet in practice among veterinarians for animal patients in most developing countries like Nigeria. This review, therefore, is aimed at exposing veterinarians from the developing countries to the general application of acutherapy with emphasis on the musculoskeletal system and associated pain where it is most applied. It is highly recommended that the universities, where Veterinary Medicine is studied in developing countries, should endeavor to train their veterinary surgeons in this area and see to how acutherapy can be included in the curriculum.

Artificial intelligence in tongue diagnosis: Using deep convolutional neural network for recognizing unhealthy tongue with tooth-mark

Tongue diagnosis plays a pivotal role in traditional Chinese medicine (TCM) for thousands of years. As one of the most important tongue characteristics, tooth-marked tongue is related to spleen deficiency and can greatly contribute to the symptoms differentiation and treatment selection. Yet, the tooth-marked tongue recognition for TCM practitioners is subjective and challenging. Most of the previous studies have concentrated on subjectively selected features of the tooth-marked region and gained accuracy under 80%. In the present study, we proposed an artificial intelligence framework using deep convolutional neural network (CNN) for the recognition of tooth-marked tongue. First, we constructed relatively large datasets with 1548 tongue images captured by different equipments. Then, we used ResNet34 CNN architecture to extract features and perform classifications. The overall accuracy of the models was over 90%. Interestingly, the models can be successfully generalized to images captured by other devices with different illuminations. The good effectiveness and generalization of our framework may provide objective and convenient computer-aided tongue diagnostic method on tracking disease progression and evaluating pharmacological effect from a informatics perspective.

A preliminary discussion of the necessity of controlled setting of placebo moxibustion

Compared with acupuncture research, moxibustion research has made slow progress with great obstacles. With randomized controlled trials as the widely accepted gold standard for the evaluation of clinical effect, moxibustion therapy is facing a great challenge: how to establish a reasonable placebo control group. This article reviewed the current application of placebo moxibustion, analyzed the difficulties in setting up placebo moxibustion, and explored corresponding solutions, in order to attract more attention to moxibustion therapy among traditional Chinese medicine practitioners.

Can Reliability of the Chinese Medicine Diagnostic Process Be Improved? Results of a Prospective Randomized Controlled Trial.

Background: The diagnostic framework and clinical reasoning process of Chinese medicine are central to the practice of acupuncture and other related disciplines. There is growing interest in integrating it into clinical trials of acupuncture and Chinese herbal medicine to guide individualized treatment protocols and evaluate outcomes. Strategies that enhance diagnostic reliability may contribute to this integration. Objectives: (1) To evaluate inter-rater reliability among practitioners of Traditional Chinese Medicine (TCM) when assessing women with dysmenorrhea using a structured assessment questionnaire (Traditional East Asian Medicine Structure Interview [TEAMSI]-TCM) compared to using a TCM questionnaire from routine clinical practice, not developed for research purposes (CONTROL); and (2) To evaluate the impact of training in the use of each approach on reliability. Design: Thirty-eight acupuncturists were asked to complete assessments of 10 subjects based on the viewing of a videotape of the initial assessment interview, a picture of the tongue, and a description of the pulse. Acupuncturists were randomized into one of four groups comparing the use of two questionnaires, TEAMSI-TCM versus CONTROL, and comparing training in the use of each versus no training. Analysis: The authors used Cohen's kappa to estimate agreement on TCM diagnostic categories relevant to dysmenorrhea between 2 practitioners with respect to questionnaires and training over all 10 patients and all 10 TCM diagnostic categories. For all analyses, the authors estimated kappa values for questionnaire, training, and experience level. Analysis of variance was used to test agreement among various groupings. Results: Regardless of the questionnaire used or training, analysis of inter-rater reliability indicated overall agreement to be low among practitioners (median 0.26). Kappa varied slightly by questionnaire and training, among 38 practitioners, but the difference was not statistically significant (p = 0.227 and p = 0.126, respectively). Conclusions: A structured assessment interview instrument designed for research purposes with or without training did not significantly improve reliability of TCM diagnosis of dysmenorrhea compared to a commonly used instrument. Challenges in assessing reliability in TCM remain.

Experimental Studies of Inter-Rater Agreement in Traditional Chinese Medicine: A Systematic Review.

Objectives: It has been recommended that clinical trials of Traditional Chinese Medicine (TCM) would be more ecologically valid if its characteristic mode of diagnostic reasoning were integrated into their design. In that context, however, it is also widely held that demonstrating a high level of agreement on initial TCM diagnoses is necessary for the replicability that the biomedical paradigm requires for the conclusions from such trials. Our aim was to review, summarize, and critique quantitative experimental studies of inter-rater agreement in TCM, and some of their underlying assumptions. Design: Systematic electronic searches were conducted for articles that reported a quantitative measure of inter-rater agreement across a number of rating choices based on examinations of human subjects in person by TCM practitioners, and published in English language peer-reviewed journals. Publications in languages other than English were not included, nor those appearing in other than peer-reviewed journals. Predefined categories of information were extracted from full texts by two investigators working independently. Each article was scored for methodological quality. Outcome measures: Design features across all studies and levels of inter-rater agreement across studies that reported the same type of outcome statistic were compared. Results: Twenty-one articles met inclusion criteria. Fourteen assessed inter-rater agreement on TCM diagnoses, two on diagnostic signs found upon traditional TCM examination, and five on novel rating schemes derived from TCM theory and practice. Raters were students of TCM colleges or graduates of TCM training programs with 3 or more years experience and licensure. Type of outcome statistic varied. Mean rates of pairwise agreement averaged 57% (median 65, range 19-96) across the 9 studies reporting them. Mean Cohen's kappa averaged 0.34 (median 0.34, range 0.07-0.59) across the seven studies reporting them. Meta-analysis was not possible due to variations in study design and outcome statistics. High risks of bias and confounding, and deficits in statistical reporting were common. Conclusions: With a few exceptions, the levels of agreement were low to moderate. Most studies had significant deficits of both methodology and reporting. Results overall suggest a few design features that might contribute to higher levels of agreement. These should be studied further with better experimental controls and more thorough reporting of outcomes. In addition, methods of complex systems analysis should be explored to more adequately model the relationship between clinical outcomes, and the series of diagnoses and treatments that are the norm in actual TCM practice.

Agro-ecological suitability assessment of Chinese Medicinal Yam under future climate change

Chinese Medicinal Yam (CMY) has been prescribed as medicinal food for thousand years in China by Traditional Chinese Medicine (TCM) practitioners. Its medical benefits include nourishing the stomach and spleen to improve digestion, replenishing lung and kidney, etc., according to the TCM literature. As living standard rises and public health awareness improves in recent years, the potential medicinal benefits of CMY have attracted increasing attention in China. It has been found that the observed climate change in last several decades, together with the change in economic structure, has driven significant shift in the pattern of the traditional CMY planting areas. To identify suitable planting area for CMY in the near future is critical for ensuring the quality and supply quantity of CMY, guiding the layout of CMY industry, and safeguarding the sustainable development of CMY resources for public health. In this study, we first collect 30-year records of CMY varieties and their corresponding phenology and agro-meteorological observations. We then consolidate these data and use them to enrich and update the eco-physiological parameters of CMY in the agro-ecological zone (AEZ) model. The updated CMY varieties and AEZ model are validated using the historical planting area and production under observed climate conditions. After the successful validation, we use the updated AEZ model to simulate the potential yield of CMY and identify the suitable planting regions under future climate projections in China. This study shows that regions with high ecological similarity to the genuine and core producing areas of CMY mainly distribute in eastern Henan, southeastern Hebei, and western Shandong. The climate suitability of these areas will be improved due to global warming in the next 50 years, and therefore, they will continue to be the most suitable CMY planting regions.

A Traditional Chinese Medicine (TCM) Based Screener for Autistic Spectral Symptoms

Unlike most of the autism screeners that use the classical triad of impairments in social interaction, communication and stereotyped behaviors to identify autism, the present screener is based on the yin-yang concept of dualism relying on the eight principles of the Chinese Traditional Medicine (TCM) to understand autism. Though not validated yet, it can still be used as an alternative screening tool by parents, teachers and other interested parties, such as the TCM practitioners, to make an initial identification of someone displaying prodromal autistic spectral symptoms, ranging from one end of the continuum that shows signs of low passivity (yin) to the other end that shows signs of high activity or reactivity (yang) in responding to either eternal or internal stimuli. The screener is strictly not to be used as a diagnostic tool. However, its results may be used for a possible quick referral to the professionals for a formal assessment to be conducted so that early intervention can be provided before the condition becomes more serious over time.

Utilization of Traditional Chinese Medicine Practitioners in Later Life in Mainland China.

Mainland China is one of the world’s most rapidly aging countries, and yet there is very limited literature on traditional Chinese medicine (TCM) use in older individuals. This study aimed to determine the national and provincial prevalence of TCM practitioner utilization in later life and associated factors. We used World Health Organization China Study on Global Aging and Adult Health Wave 1 data to determine descriptive statistics of the study population of participants aged 50 years and over. Multivariate logistic regression was conducted controlling for sociodemographic and health factors. A total of 14% of participants utilized a TCM practitioner, and the prevalence of utilization varied significantly by locality. Utilization was more likely in participants living in rural areas [adjusted odds ratio (OR) = 12.96; p < 0.001], Hubei (OR = 7.17; p < 0.001), or Shandong provinces (OR = 4.21; p < 0.001) and being diagnosed with chronic lung disease (OR = 1.97; p = 0.005). Hence, rurality, provincial influence, and chronic lung diseases are significant factors associated with TCM practitioner utilization among older individuals in China. These findings may inform policy for preservation and development of TCM nationally as well as its sustainability in an increasingly aging society.

A Novel Approach to Describing Traditional Chinese Medical Patterns: The “Traditional Chinese Medical Diagnostic Descriptor”

Objectives: In the first of a series of three articles by the present authors, diagnostic agreement between Traditional Chinese Medicine (TCM) practitioners was found to be low. This was the first time that TCM diagnoses had been evaluated with an open population of patients and this result is a cause of concern. In the second article, incorrect statistics were shown to have often been used to calculate chance-removed inter-rater agreement, and appropriate statistics such as Gwet's Agreement Coefficient 2 (AC2) was recommended for future studies. In this, the third article, a novel approach to recording TCM diagnostic patterns, the Traditional Chinese Medical Diagnostic Descriptor (TCMDD), is presented that allows chance-removed agreement calculation. An example of mapping TCM diagnostic patterns to the TCMDD format is given and diagnostic agreement is evaluated. Design, Settings, Subjects: The same 35 subjects used to report agreement in our first article were also diagnosed by additional practitioners using the TCMDD format during the same experimental sessions at the University of Technology, Sydney Clinic. TCM diagnoses from the first article were also mapped to the TCMDD format. Outcome measures: Linearly weighted simple agreement and the AC2 statistic were utilized and all results compared. Results: Linearly weighted simple agreement using the TCMDD and TCM mapped to TCMDD format averaged 0.80 ± 0.02 compared with 0.19 for TCM. TCMDD and TCM mapped to TCMDD chance-removed agreement, as calculated with AC2, ranged between 0.67 and 0.73 ± 0.03. Conclusions: The TCMDD allows the essence of diagnoses expressed by TCM practitioners to be appropriately compared. This was confirmed by the TCM mapped to TCMDD results. In both cases, simple agreement was significantly greater than that obtained with the TCM format. Chance-removed statistics and error estimates can be reliably calculated with the AC2 and the TCMDD in open populations.