Why Korean Medicine Needs 'Standards'
Pattern identification in Korean medicine is a unique system that comprehensively analyzes patient symptoms to diagnose the cause, location, and nature of diseases9 . However, this traditional medicine with a long history faced modern challenges of objectivity and reproducibility. The same patient could receive different diagnoses depending on the Korean medicine doctor's experience and background3 .
This diagnostic inconsistency was a barrier to the modernization and scientification of Korean medicine. In the mid-1990s, the Korea Institute of Oriental Medicine initiated the 'Standardization Study of Korean Medical Diagnosis Names and Diagnostic Criteria' to address this issue4 5 .
This research aimed to present a standard for Korean medical diagnoses, providing objective basis for academic exchange and clinical case discussions4 .
Diagnostic Challenges
Traditional Korean medicine diagnosis faced issues with:
- Inter-practitioner variability
- Lack of objective criteria
- Difficulty in reproducing diagnoses
- Limited scientific validation
How Standardization Was Achieved
Evolution of Standardization Research
Korean medicine standardization research began in earnest in the 1990s. The standardization study conducted from 1994 to 1997 presented a standard for diagnosis names and diagnostic criteria based on theoretical research on Korean medical diagnosis4 .
The research team organized Korean medical diagnosis into the following system1 :
- Qi-Blood-Yin-Yang-Fluid Pattern Identification: Pattern identification based on body fluid status
- Zang-Fu Pattern Identification: Pattern identification based on pathological changes and interrelationships of zang-fu organs
- Six-Channel Pattern Identification: Analysis of febrile diseases based on the theory of Shang Han Lun
1994-1997
Initial standardization research establishing diagnosis names and criteria
2004
Development of 'Yin Deficiency Questionnaire' with verified reliability and validity8
2010s
SOPI-Stroke project launch for stroke pattern identification standardization
2024
Development of Korean medical examination protocols with data from 11,036 healthy adults6
Development of Scientific Tools for Standardization
As part of standardization research, researchers developed various measurement tools. The 'Yin Deficiency Questionnaire' developed in 2004 was a standardized questionnaire tool for evaluating Yin deficiency, with verified reliability and validity8 . The development of such standardized questionnaires and assessment tools became an important milestone in enhancing the objectivity of Korean medical diagnosis.
Standardized Forms
Development of case report forms (CRF) for consistent data collection
Assessment Tools
Validated questionnaires for specific pattern identification
Data Protocols
Systematic data collection from multiple medical centers
Stroke Pattern Identification Standardization: SOPI-Stroke
The Pinnacle of Standardization: SOPI-Stroke Project
The apex of standardization research was the Standardization and Objectification of Pattern Identification for Stroke (SOPI-Stroke) project. This was a large-scale research project led by the Korea Institute of Oriental Medicine with participation from several Korean medical college hospitals3 .
The goals of the SOPI-Stroke project were3 :
- Standardization and objectification of stroke pattern identification and pattern indicators through scientific and statistical processes
- Development of standardized charts combining Korean and Western medicine diagnoses
- Establishment of blood banks and discovery of stroke biomarkers based on pattern identification
Research Methodology
The research team first formed an expert committee to derive 5 patterns and 122 pattern indicators from 10 Korean medicine texts3 . Based on this, they developed a standardized case report form (CRF) and evaluated inter-observer agreement with 168 stroke patients9 .
Research Process:
Standardization Outcomes: Inter-Observer Agreement Analysis
The outcomes of the SOPI-Stroke research can be seen in the inter-observer agreement. When two experts independently examined patients and evaluated how consistently they made diagnoses, the results showed moderate to high agreement across four examination methods9 .
Pulse Diagnosis Agreement
| Variable | Agreement (%) | Kappa Value |
|---|---|---|
| Floating Pulse | 88.02 | 0.53 |
| Deep Pulse | 85.02 | 0.56 |
| Rapid Pulse | 90.41 | 0.50 |
| Slow Pulse | 80.83 | 0.56 |
| Strong Pulse | 81.92 | 0.51 |
| Weak Pulse | 86.14 | 0.61 |
| Slippery Pulse | 77.84 | 0.51 |
| Thin Pulse | 73.65 | 0.37 |
| Full Pulse | 90.36 | 0.52 |
Examination Method Agreement
| Examination Method | Average Agreement (%) | Average AC1 |
|---|---|---|
| Pulse Diagnosis | 83.80 | 0.77 |
| Tongue Diagnosis | 83.97 | 0.79 |
| Auscultation & Olfaction | 80.67 | 0.74 |
| Inquiry | 84.71 | 0.80 |
Inquiry Indicators Agreement
| Inquiry Indicator | Agreement (%) | AC1 Statistic |
|---|---|---|
| Headache | 87.35 | 0.81 |
| Thirst | 89.76 | 0.86 |
| Oral Temperature | 92.77 | 0.91 |
| Chest Temperature | 94.64 | 0.94 |
| Sleep | 86.14 | 0.79 |
| Sweating | 89.76 | 0.86 |
| Urination | 87.95 | 0.83 |
| Energy Level | 86.14 | 0.79 |
As shown in the tables above, when using standardized diagnostic criteria, all four examination methods showed AC1 statistics between 0.66 and 0.95, indicating moderate to high agreement. This demonstrates that standardization work has contributed to increasing diagnostic consistency among Korean medicine practitioners9 .
Future of Korean Medicine Standardization: Digital Healthcare and AI
Integration with Digital Healthcare
The next phase of standardization research involves integration with digital healthcare. In 2024, the Korea Institute of Oriental Medicine developed Korean medical examination protocols and systematically collected data from 11,036 healthy adults at 6 Korean medicine hospitals6 .
This protocol has the potential to be used for assessing disease prediction risks by standardizing and quantifying the core indicators of Korean medicine6 .
Digital Healthcare Applications:
- Remote diagnosis through digital tongue and pulse analysis
- Mobile apps for symptom tracking and pattern identification
- Wearable devices for continuous health monitoring
- Telemedicine platforms incorporating standardized diagnostics
AI Challenges and Opportunities
Artificial intelligence (AI) technology also presents new opportunities for Korean medicine standardization. At the 2025 academic conference of the Korean Society of Oriental Diagnostics, discussions included modern disease and pattern identification using LLM (Large Language Model) principles, and development of evaluation indicators for AI chatbots' pattern identification capabilities7 .
AI-based Clinical Decision Support Systems (CDSS) can analyze patient inquiry records to suggest differential diagnoses and optimal prescriptions. However, to evaluate AI's pattern identification capabilities, development of evaluation indicators such as symptom determination accuracy, symptom coverage, and query efficiency is necessary7 .
AI Evaluation Metrics:
The Journey of Korean Medicine Standardization: Significance and Prospects
The standardization research of Korean medical diagnosis names and diagnostic criteria has served as a bridge between tradition and modernity. This research was a process of systematizing the unique knowledge and clinical experience of Korean medicine and reinterpreting it in a contemporary context.
Standardization work laid the foundation for Korean medicine to develop as a medicine based on scientific evidence. Additionally, the development of quantitative data and objective assessment tools has become an essential condition for Korean medicine to keep pace with the digital healthcare era.
Looking ahead, Korean medicine standardization research will enable more precise diagnosis and personalized treatment through integration with AI. When digital technology and scientific methodology combine on the foundation of standardization, Korean medicine can establish itself as a valuable medicine even in the era of the Fourth Industrial Revolution.