Proposal for an Integrated Evaluation Model for the Study of Whole Systems Health Care in Cancer

Published in: Integrative Cancer Therapies, v. 5, no. 4, Dec. 2006, p. 315-319

Posted on on January 01, 2006

by Wayne B. Jonas, William Beckner, Ian D. Coulter

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For more than 200 years, biomedicine has approached the treatment of disease by studying disease processes (pathogenesis), inferring causal connections and developing specific approaches for therapeutically interfering with those processes. This pathogenic approach has been highly successful in acute and traumatic disease but less successful in chronic disease, primarily because of the complex, multifactorial nature of most chronic disease, which does not allow for simple causal inference or for simple therapeutic interventions. This article suggests that chronic disease is best approached by enhancing healing processes (salutogenesis) as a whole system. Because of the nature of complex systems in chronic disease, an evaluation model based on integrative medicine is felt to be more appropriate than a disease model. The authors propose and describe here an integrated model for the evaluation of healing (IMEH) that collects multilevel thick case observational data in assessing complex practices for chronic disease. If successful, this approach could become a blueprint for studying healing capacity in whole medical systems, including complementary medicine, traditional medicine, and conventional primary care. In addition, streamlining data collection and applying rapid informatics management might allow for such data to be used for guiding clinical practice. The IMEH involves collection, integration, and potentially feedback of relevant variables collected in the following areas: (1) sociocultural, (2) psychological and behavioral, (3) clinical (diagnosis based), and (4) biological. Evaluation and integration of these components would involve specialized research teams that feed their data into a single data management and information analysis center. These data can then be subjected to descriptive and pathway analysis providing bench and bedside information.

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