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Goals

The project Dent@Prevent aims at improving quality and efficiency of care for patients with oral and general chronic conditions. This is addressed via examining the links between the various disease processes, development of a mobile computing app for collecting Patient Reported Outcome Measures (PROMs), and piloting of an electronic Decision Support System. The project will integrate routinely collected administrative data and PROMs to support better evidence-informed and inter-sectoral decision making.

Project description

Studies indicate the existence of common risk factors for chronic pathologies and other chronic diseases. This correlation is particularly noticeable at periodontitis, diabetes and coronary heart disease. Dent@Prevent aims to improve the cooperation between the medical staff both inside and outside the dentistry. The objective is to ensure that doctors and patients are equally informed and can decide together about further treatment.

Firstly, it will be investigated how and why dental- and chronic-systemic diseases are related. To achieve this, scientific articles are systematically analysed and anonymised data from statutory health insurances analysed. Simultaneously, a smartphone app is developed with which the treatment decision can be more strongly targeted to the individual patient: With the app, patients can, for example, provide individual information about their health with regard to their oral health and general health.

Together with the results of the literature research and the analysis of the health insurance data, these reports are used for the development of a digital decision support tool. The insights gained during the project on the interrelationship of dental and systemic diseases can be incorporated into the training and further education of (dentists) physicians.

In the case of success, the developed app and the digital tool can be adapted and used for decision support in other areas.

Funding

Dent@Prevent receives funding from the Federal Joint Committee (G-BA) - Innovation Fund, Grant agreement number: 01VSF16052

Project period

2017 - 2020