Evaluation of Treatment Outcomes in Kampo Outpatients Using an Electronic Questionnaire and Development of Predictive Algorithms: A Protocol of Observational Study

ABSTRACT Introduction This study aims to evaluate treatment outcomes in Kampo outpatients using electronic questionnaires by accumulating multi‐institutional data. It also aims to improve algorithms for predicting traditional pattern diagnosis and create algorithms for prescribed formulas and subjective symptom changes. Methods This multi‐center observational study involves adult patients visiting Kampo outpatient clinics in Japan. Data will be collected from patient electronic questionnaires, physicians' entries into an Electronic Data Capture system (Kampo/Western diagnoses and prescriptions), and medical records including medical history, concomitant medications, and routine blood/urine test results. The primary outcome is the change in Visual Analogue Scale (VAS) scores for the chief complaint. Secondary outcomes involve developing predictive models for VAS changes, pattern diagnosis, and formula prescription. Statistical analyses will be performed using R‐software. Missing data will generally be handled by excluding cases lacking essential items. Outliers will be addressed through sensitivity analyses performed both with and without exclusion. Anticipated Results The study will yield predictive algorithms for pattern diagnosis, formula selection, and subjective symptom changes. Performance metrics such as accuracy, precision, sensitivity, specificity, and F‐measure will be reported for the models. Conclusion This study aims to contribute to the appropriate use of Kampo medicine by developing clinical support systems through the creation and improvement of predictive algorithms. The findings are expected to enable efficient and safe healthcare delivery in clinical settings. Trial Registration The study is registered with the University hospital Medical Information Network (UMIN‐CTR). Registration No.: UMIN000042048

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Publication Details

Journal
Traditional & Kampo Medicine
Published
2026-03-11
DOI
https://doi.org/10.1002/tkm2.70045
Primary Topic
Traditional Chinese Medicine Studies
Type
article
Field-Weighted Citation Impact
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article

Evaluation of Treatment Outcomes in Kampo Outpatients Using an Electronic Questionnaire and Development of Predictive Algorithms: A Protocol of Observational Study

Tomonori Nakamura, Takao Namiki, Tatsuya Nogami, Hidenori Ito et al.
Traditional & Kampo Medicine
Traditional Chinese Medicine Studies
article

Evaluation of Treatment Outcomes in Kampo Outpatients Using an Electronic Questionnaire and Development of Predictive Algorithms: A Protocol of Observational Study

Tomonori Nakamura, Takao Namiki, Tatsuya Nogami, Hidenori Ito, Eiichi Tahara, K Kaneda, S. Imoto, Shin Takayama, Koichi Fukunaga, Yuko Kaneko, Tetsuhiro Yoshino
article en

Abstract

ABSTRACT Introduction This study aims to evaluate treatment outcomes in Kampo outpatients using electronic questionnaires by accumulating multi‐institutional data. It also aims to improve algorithms for predicting traditional pattern diagnosis and create algorithms for prescribed formulas and subjective symptom changes. Methods This multi‐center observational study involves adult patients visiting Kampo outpatient clinics in Japan. Data will be collected from patient electronic questionnaires, physicians' entries into an Electronic Data Capture system (Kampo/Western diagnoses and prescriptions), and medical records including medical history, concomitant medications, and routine blood/urine test results. The primary outcome is the change in Visual Analogue Scale (VAS) scores for the chief complaint. Secondary outcomes involve developing predictive models for VAS changes, pattern diagnosis, and formula prescription. Statistical analyses will be performed using R‐software. Missing data will generally be handled by excluding cases lacking essential items. Outliers will be addressed through sensitivity analyses performed both with and without exclusion. Anticipated Results The study will yield predictive algorithms for pattern diagnosis, formula selection, and subjective symptom changes. Performance metrics such as accuracy, precision, sensitivity, specificity, and F‐measure will be reported for the models. Conclusion This study aims to contribute to the appropriate use of Kampo medicine by developing clinical support systems through the creation and improvement of predictive algorithms. The findings are expected to enable efficient and safe healthcare delivery in clinical settings. Trial Registration The study is registered with the University hospital Medical Information Network (UMIN‐CTR). Registration No.: UMIN000042048

Traditional & Kampo MedicineVol. 13(1)
Tokai University (JP), University of Aizu (JP), Tokyo Medical University (JP), Keio University (JP), Kyoto University (JP), Tohoku University Hospital (JP), Chiba University Hospital (JP), Kitasato Institute Hospital (JP), International University of Health and Welfare (JP)
Reduced inequalities
Openalex Percentile: Top 23%
Traditional Chinese Medicine Studies
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