Natural Medicines is built strictly on the evidence. Many aspects of medicine are influenced by tradition and beliefs passed from one person to another. This is especially true in the area of natural medicines. Some natural medicines are used due to traditional or folkloric beliefs, and some are the subject of excessive marketing claims or excessive extrapolations from test tube or animal studies.

• Natural Medicines approaches the subject of natural medicines from a completely objective and unbiased perspective. It seeks to answer questions about natural medicines by systematically identifying, evaluating, and applying scientific information. As a result, it curtails perpetuation of myths and age-old beliefs and replaces them with reliable scientific data.
• In addition to providing reliable scientific data, Natural Medicines provides information that is clinically practical for health professionals. Health professionals need information that is soundly grounded in the evidence, but also need practical information that can support the clinical decision making process.
• To achieve these goals, Natural Medicines relies on a solid evidence-based foundation. Each product monograph in the Database and its associated Safety Ratings, Effectiveness Ratings, and Interaction Ratings are supported by the best available scientific evidence. This evidence is systematically identified, critically evaluated, and applied using the same high standards used to evaluate evidence related to other therapies. We do not believe that there should be different standards of evidence for conventional therapies compared to alternative therapies. Therefore, we do not consider anecdote, tradition or folklore to be scientific “evidence.”
• We recognize several different levels of evidence. Evidence that is highly relevant and valid is given greater weight than evidence that is less relevant or reliable.
• When evidence does not exist or is severely deficient, which is often the case, this deficiency is clearly acknowledged in the Database with a statement indicating a lack of data.

 

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