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Filippopulos, Filipp M.; Huppert, Doreen; Brandt, Thomas; Hermann, Margit; Franz, Mareike; Fleischer, Steffen and Grill, Eva (2020): Computerized clinical decision system and mobile application with expert support to optimize management of vertigo in primary care: study protocol for a pragmatic cluster-randomized controlled trial. In: Journal of neurology, Vol. 267: pp. 45-50 [PDF, 662kB]


Vertigo and dizziness are amongst the most common symptoms in medicine and often have a major impact on activities of daily life. Although many causes of vertigo and dizziness can easily be recognized, patients often receive inappropriate and ineffective treatment. The reasons for this are various. Because vertigo/dizziness is an interdisciplinary symptom and there is a lack of standardised diagnostic tools, it is easy to lose the overview of the possible differential diagnoses. There is evidence though, that the management of patients with vertigo/dizziness can be optimized using standardized care pathways with digital support. The present study (within the framework of \textquotedblPoiSe-prevention, online feedback, and interdisciplinary therapy of acute vestibular syndromes by e-health\textquotedbl) aims to evaluate the implementation of a program with several interlocking components. The three main components are a computerized clinical decision system, a mobile application, a counselling and interdisciplinary educational program developed by the German Center for Vertigo and Balance Disorders (DSGZ). The study is a cluster-randomized controlled trial with a parallel-group design, as well as a detailed process evaluation. Clusters comprise of primary care physician practices in Bavaria, Germany. In the scope of the study the effectiveness, acceptability and efficiency of the intervention will be evaluated. It is anticipated that the intervention will improve the quality and efficiency of the management of dizzy patients. A higher diagnostic accuracy, optimized treatment, and disease progression monitoring is expected to improve patient-relevant outcomes and reduce health-care costs.

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