RESEARCH ARTICLE


The Translation Evidence Mechanism. The Compact between Researcher and Clinician



Janet G Bauer*, Francesco Chiappelli
UCLA School of Dentistry, Division of Restorative Dentistry, June and Paul Ehrlich Endowed Program in Geriatric Dentistry, 23-008E CHS, PO Box 951668, 10833 Le Conte Avenue, Los Angeles, California 90095-1668, USA


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Creative Commons License
© Bauer and Chiappelli; Licensee Bentham Open.

open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

* Address correspondence to this author at the UCLA School of Dentistry, Division of Restorative Dentistry, June and Paul Ehrlich Endowed Program in Geriatric Dentistry, 23-008E CHS, P.O. Box 951668, 10833 Le Conte Avenue, Los Angeles, California 90095-1668, USA; Tel: 310-825-57747; Fax: 310-641-0523; E-mail: jbauer@dent.ucla.edu


Abstract

Currently, best evidence is a concentrated effort by researchers. Researchers produce information and expect that clinicians will implement their advances in improving patient care. However, difficulties exist in maximizing cooperation and coordination between the producers, facilitators, and users (patients) of best evidence outcomes. The Translational Evidence Mechanism is introduced to overcome these difficulties by forming a compact between researcher, clinician and patient. With this compact, best evidence may become an integral part of private practice when uncertainties arise in patient health status, treatments, and therapies. The mechanism is composed of an organization, central database, and decision algorithm. Communication between the translational evidence organization, clinicians and patients is through the electronic chart. Through the chart, clinical inquiries are made, patient data from provider assessments and practice cost schedules are collected and encrypted (HIPAA standards), then inputted into the central database. Outputs are made within a timeframe suitable to private practice and patient flow. The output consists of a clinical practice guideline that responds to the clinical inquiry with decision, utility and cost data (based on the “average patient”) for shared decision-making within informed consent. This shared decision-making allows for patients to “game” treatment scenarios using personal choice inputs. Accompanying the clinical practice guideline is a decision analysis that explains the optimized clinical decision. The resultant clinical decision is returned to the central database using the clinical practice guideline. The result is subsequently used to update current best evidence, indicate the need for new evidence, and analyze the changes made in best evidence implementation. When updates in knowledge occur, these are transmitted to the provider as alerts or flags through patient charts and other communication modalities.