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Stud Health Technol Inform. 2018;247:671-674.

Approach Towards an Evidence-Oriented Knowledge and Data Acquisition for the Optimization of Interdisciplinary Care in Dentistry and General Medicine.

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University of Heidelberg, Institute of Medical Biometry and Informatics, Heidelberg, Germany.
University of Cologne, PMV forschungsgruppe, Cologne, Germany.
University Hospital Heidelberg, Department of Conservative Dentistry, Division of Translational Health Economics, Heidelberg, Germany.


Associations between dental and chronic-systemic diseases were observed frequently in medical research, however the findings of this research have so far found little relevance in everyday clinical treatment. Major problems are the assessment of evidence for correlations between such diseases and how to integrate current medical knowledge into the intersectoral care of dentists and general practitioners. On the example of dental and chronic-systemic diseases, the Dent@Prevent project develops an interdisciplinary decision support system (DSS), which provides the specialists with information relevant for the treatment of such cases. To provide the physicians with relevant medical knowledge, a mixed-methods approach is developed to acquire the knowledge in an evidence-oriented way. This procedure includes a literature review, routine data analyses, focus groups of dentists and general practitioners as well as the identification and integration of applicable guidelines and Patient Reported Measures (PRMs) into the treatment process. The developed mixed methods approach for an evidence-oriented knowledge acquisition indicates to be applicable and supportable for interdisciplinary projects. It can raise the systematic quality of the knowledge-acquisition process and can be applicable for an evidence-based system development. Further research is necessary to assess the impact on patient care and to evaluate possible applicability in other interdisciplinary areas.


Chronic-systemic disease; Decision support system (DSS); Dental disease; Evidence-oriented data acquisition; Interdisciplinary care

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