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

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 “PoiSe—prevention, online feedback, and interdisciplinary therapy of acute vestibular syndromes by e-health”) 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.

Human factors, automation, and alerting mechanisms in nursing home electronic health records

The objective was to evaluate a clinical decision support system in an electronic medical record (EMR) to determine activation frequencies, patterns of activity, and how automated alerting mechanisms affect clinical responses in three Midwestern nursing homes where administrative staff had committed to implementing an EMR and clinical decision system called OneTouch Technologies. Automated alerts in the OneTouch EMR including constipation, decline in condition, dehydration, improvement in condition, skin integrity, weight gain, and weight loss were evaluated. Using alert calculations, frequencies of alerts and triggers were counted. Spearman's rank correlations were determined between the frequency of active alerts and the number of secondary diagnoses for residents. Finally, a comparison was made of clinical responses to active and non-active alerts. Alert data from two facilities totaling 155 days were included in the study. The most frequent alerts were dehydration and improvement in condition. One moderately significant positive correlation was found between the number of secondary diagnoses and weight gain alert frequencies in residents who had a CVA. There were significantly more responses than no clinical responses overall. However, there were as many clinical responses to conditions with no active alerts as active. The study concluded that frequencies of alerts is an indicator of how much information has to be managed in order to meet complex issues in nursing home residents. Automated alerts play a role in reminding nursing home staff of potential trouble spots in resident care.