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Diagnostic test evaluation by patient‐outcome study in homeopathy: balancing of feasibility and validity
Author(s) -
Rutten A. L. B.,
Stolper C. F.
Publication year - 2009
Publication title -
journal of evaluation in clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.737
H-Index - 73
eISSN - 1365-2753
pISSN - 1356-1294
DOI - 10.1111/j.1365-2753.2009.01285.x
Subject(s) - homeopathy , medicine , observational study , medical prescription , outcome (game theory) , confidence interval , test (biology) , odds ratio , odds , bayes' theorem , diagnostic test , physical therapy , alternative medicine , logistic regression , pediatrics , statistics , bayesian probability , pathology , paleontology , mathematics , mathematical economics , pharmacology , biology
Background Signs and symptoms can be considered as diagnostic tests, updating prior odds by applying Bayes' theorem. In homeopathy, signs and symptoms guide the doctor when prescribing appropriate medicines but the powers of these indicators are largely based on common experience. Objective We want to know whether it is possible to calculate the power of arguments of signs and symptoms indicating homeopathic medicines, expressed in likelihood ratios. Methods An observational patient‐outcome study as advocated for diagnostic test evaluation. There was no independent observation of symptoms and results. Instead, observers were extensively trained in assessing each other's cases and the process was regularly monitored. Results A total of 4072 prescriptions for 4094 patients were recorded. The relation between six clinical symptoms and outcome was calculated. Variance between observers in assessing symptoms and results were considerable. Some indications of confirmation bias were detected by follow‐up, and 48 statistically significant likelihood ratios regarding six symptoms were calculated. Conclusion A diagnostic patient‐outcome study within homeopathy collecting a large amount of data is demonstrated. Results partly confirm clinical practice at a 95% confidence level. This kind of research could validate knowledge from practical experience.