ABSTRACT
BACKGROUND: Even though several initiatives have been undertaken in different locations worldwide to collect clinical data in homeopathy, it is important to further investigate these aspects in the context of health care in India. OBJECTIVE: The study aimed to gather and analyze patients' clinical data and to derive insights into homeopathic treatment using an internet-based software program for data storage, retrieval and repertorization. METHODS: A multi-center observational study was conducted across 14 homeopathy outpatient clinics in India that are affiliated with the Central Council for Research in Homoeopathy (CCRH). Patient symptoms and demographic details were documented anonymously, and prescriptions were guided by repertorial suggestions from the Vithoulkas Compass software. During follow-up visits, treatment outcome was also recorded using an online assessment form. A retrospective analysis of data on patients' demographics, follow-up visits, morbidity (International Classification of Diseases 11th Revision), rubrics used, prescribed medicines and the level of improvement was achieved using Microsoft Excel-generated pivot tables. RESULTS: Throughout the study duration of one year a total of 2,811 patients attended the 14 outpatient clinics, of whom 2,468 were new patients with a total of 2,172 initial homeopathic prescription entries. Across the study, there were 3,491 prescriptions and 1,628 follow-up consultations for 868 follow-up patients, all of which data were thoroughly analyzed. The highest frequency of patients was in the 20-49 age group, and a higher proportion of the patients overall was female. Musculoskeletal, dermatological and respiratory complaints were the most frequently reported. The rubrics "Desire for sweets" and "Desire for spices" emerged as the most commonly used in the repertorizations. Further, Sulphur stood out as the most commonly prescribed medicine overall. With homeopathic treatment, some degree of clinical improvement was reported in 86% of the follow-up cases. CONCLUSION: Homeopathy is prescribed in CCRH outpatient clinics for a wide range of ailments in people across India, with at least some clinical improvement noted in a high proportion of those patients. The large-scale systematic data collection in these clinics has provided clear insights into the use and clinical value of homeopathy in India, with the potential to build a substantive nationwide data inventory over time.
ABSTRACT
BACKGROUND: Polar symptoms (PS)-symptoms with opposite values-are frequently used in homeopathy, but have many misleading entries in the repertory. This is caused by using absolute occurrence of symptoms, causing the same medicine to appear in both (opposite) symptom rubrics, and by lack of comparison with other medicines. Some PS, like 'aversion/desire for sweets' have a frequency distribution that is not evenly distributed around the neutral value: a desire for sweets is much more common than aversion. A desire for sweets is an indication for a specific medicine only if this desire occurs more frequently in this specific medicine population than in the remainder of the population. We need to find the best way to represent this difference. METHODS: A multi-centre, explorative, prospective, observational study was conducted by nine centres of the Central Council for Research in Homoeopathy. Two-hundred and sixteen patients were enrolled with chronic cough lasting more than 8 weeks, and received usual homeopathic care. During intake, 30 general PS, 27 polar cough symptoms and 3 non-polar cough symptoms were checked. Different ways of representing results were explored, including two quantities borrowed from mechanics: Centre of Mass (CoM) and Leverage. RESULTS: At the fourth follow-up, three medicines with more than 10 cases with good results were identified: 20 Phosphorus, 19 Pulsatilla and 13 Sulphur. The mean value of the frequency distribution of some symptoms in the whole sample was considerably different from the neutral value. Comparing a medicine population with the remainder of the respective population can give results that differ from polarity analysis. For some symptoms, the 'distance' (Leverage) between the CoMs of the medicine population and the remainder of the population was clearer than the likelihood ratio (LR). CONCLUSION: If the LR value is not clear about the prognostic value in PS, notions from mechanics such as CoM and Leverage can clarify how to interpret a polar symptom.
