Development of a Standardized Rating Tool for Drug Alerts to Reduce Information Overload.

BACKGROUND: A well-known problem in current clinical decision support systems (CDSS) is the high number of alerts, which are often medically incorrect or irrelevant. This may lead to the so-called alert fatigue, an overriding of alerts, including those that are clinically relevant, and underuse of CDSS in general. OBJECTIVES: The aim of our study was to develop and to apply a standardized tool that allows its users to evaluate the quality of system-generated drug alerts. The users' ratings can subsequently be used to derive recommendations for developing a filter function to reduce irrelevant alerts. METHODS: We developed a rating tool for drug alerts and performed a web-based evaluation study that also included a user review of alerts. In this study the following categories were evaluated: "data linked correctly", "medically correct", "action required", "medication change", "critical alert", "information gained" and "show again". For this purpose, 20 anonymized clinical cases were randomly selected and displayed in our customized CDSS research prototype, which used the summary of product characteristics (SPC) for alert generation. All the alerts that were provided were evaluated by 13 physicians. The users' ratings were used to derive a filtering algorithm to reduce overalerting. RESULTS: In total, our CDSS research prototype generated 399 alerts. In 98 % of all alerts, medication data were rated as linked correctly to drug information; in 93 %, the alerts were assessed as "medically correct"; 19.5 % of all alerts were rated as "show again". The interrater-agreement was, on average, 68.4 %. After the application of our filtering algorithm, the rate of alerts that should be shown again decreased to 14.8 %. CONCLUSIONS: The new standardized rating tool supports a standardized feedback of user-perceived clinical relevance of CDSS alerts. Overall, the results indicated that physicians may consider the majority of alerts formally correct but clinically irrelevant and override them. Filtering may help to reduce overalerting and increase the specificity of a CDSS.

Nuclear medicine diagnostic techniques in the era of pathophysiology-based CSF biomarkers for Alzheimer's disease.

Nuclear medicine techniques were the first functional imaging techniques used to support the clinical diagnosis of Alzheimer's Disease (AD). Perfusion-SPECT allows registration of regional cerebral blood flow (rCBF) which is altered in a characteristic temporal-parietal pattern in AD. Numerous studies have shown the diagnostic value of reduced CBF and metabolic changes using perfusion-SPECT and FDG-PET in AD diagnosis as well as in differential diagnosis against frontotemporal dementia (FTD), dementia with Lewy-Bodies (DLB), and vascular cognitive disorders. This renders perfusion-SPECT an important piece of the puzzle (together with other diagnostic tests) by the clinician is often faced when making a final etiologic dementia diagnosis especially between AD and FTD. A similar diagnostic value can be expected when arterial spin labeling (ASL) MRI sequence is used, but the diagnostic value has yet to be confirmed in lager studies. Recently, more pathophysiology-based biomarkers in CSF and Amyloid-PET tracers have been developed that probably have a higher diagnostic accuracy than the more indirect rCBF changes seen in perfusion-SPECT. In the current review, we describe recent advances in AD biomarkers as well as improvements in the SPECT technique.