Big Data Analysis of Traditional Knowledge-based Ayurveda Medicine. Issue 5 (October 2018) - Singh, Harpreet; Bhargava, Sapna; Ganeshan, Sailesh; Kaur, Ravneet; Sethi, Tavpritesh; Sharma, Mukesh; Chauhan, Madhusudan; Chauhan, Neerja; Chauhan, Rishipal; Chauhan, Partap; Brahmachari, Samir K.
Abstract : Introduction: Modern medicine has embraced data-driven understanding of health, principally through electronic medical records. However, Ayurveda, which is the dominant traditional medicine system in India, much of it is still practiced without digital records. Methods: In this study, 353, 000 patients' data were captured digitally by 300 Ayurveda doctors over teleconsultation and in-person consultations. The entire dataset was analyzed based on age, sex, region, chronicity, Vikriti, disease morbidity, and comorbitidy and reported effectiveness of the treatment. Results: Younger patients were found to use more Ayurveda telemedicine, but all age groups were well represented. It was found that 82% patients had disease chronicity greater than 1 year. About 85% of the diseases were related to 6 organ systems, digestive (30.6%), endocrine (14.6%), skeleton (13.5%), skin (11.2%), nervous (7.6%), and respiratory (7.4%). The network analysis of the data revealed difference in sex and age-based patterns. Disease of endocrine and cardiovascular systems become comorbid for patient population at older age-groups as also observed in case of modern medicines. Conclusion: Within the limitations of using practice data from a single large group of Ayurveda practitioners, this represents the first data-driven view of Ayurveda practice in India. In spite of 82% of all the patients having chronic diseases, Ayurveda treatment offered complete or partial relief in more than 76% of cases, and only 0.9% reported aggravation in symptoms. Abstract : Supplemental Digital Content is available in the text.