The necessity to develop a national classification system for Iranian traditional medicine

5^th International Congress on Traditional Medicine, Therapies and Modern Health Care

June 23-24, 2021 | Webinar

Reza Safdari , Hossein Rezaeizadeh, Goli Arji

Department of Health Information Technology, School of Nursing and Midwifery, Saveh University of Medical Sciences, Markaz, Iran

Scientific Tracks Abstracts: Altern Integ Med

Abstract :

Background: Classification of disease and interventions in traditional medicine (TM) is necessary for standardised coding of information. Currently, in Iran, there is no standard electronic classification system for disease and interventions in TM. Objective: The current study aimed to develop a national framework for the classification of disease and intervention in Persian medicine based on expert opinion. Method: A descriptive cross-sectional study was carried out in 2018. The existing systems for the classification of disease and interventions in TM were reviewed in detail, and some of the structural and content characteristics were extracted for the development of the classification of Iranian traditional medicine. Based on these features, a self-administered questionnaire was developed. Study participants (25) were experts in the field of Persian medicine and health information management in Tehran medical universities. Results: Main axes for the classification of disease and interventions were determined. The most important applications of the classification system were related to clinical coding, policymaking, reporting of mortality and morbidity data, cost analysis and determining the quality indicators. Half of the participants (50%) stated that the classification system should be designed by maintaining the main axis of the World Health Organization classification system and changing the subgroups if necessary. A computer-assisted coding system for TM was proposed for the current study. Conclusion: Development of this classification system will provide nationally comparable data that can be widely used by governments, national organisations and academic researchers.

Biography :

Goli Arji has completed his PhD at the age of 31 years from Tehran university of medical sciences . She has published more than 17 papers in reputed journals and has been serving as an editorial board member of repute. She is currently is assistant professor in health information managemnet at Saveh university of medical sciences.