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Data-mining algorithms that can produce accurate signals of potentially novel adverse drug reactions (ADRs) are a central component of pharmacovigilance. We propose a signal-detection strategy that combines the adverse event reporting system (AERS) of the Food and Drug Administration and electronic health records (EHRs) by requiring signaling in both sources. We claim that this approach leads to improved accuracy of signal detection when the goal is to produce a highly [...]

This paper summarizes much of the research that is applicable to the design of auditory alarms in a medical context. It also summarizes research that demonstrates that false alarm rates are unacceptably high, meaning that the proper application of auditory alarm design principles are compromised.

The internet is increasingly being used to conduct randomized controlled trials (RCTs). Knowledge of the types of interventions evaluated and the methodological quality of these trials could inform decisions about whether to conduct future trials using conventional methods, fully online or a mixture of the two.

The increasing availability of clinical data from electronic medical records (EMRs) has created opportunities for secondary uses of health information. When used in machine learning classification, many data features must first be transformed by discretization.

Medical visualization tools have traditionally been constrained to tethered imaging workstations or proprietary client viewers, typically part of hospital radiology systems. To improve accessibility to real-time, remote, interactive, stereoscopic visualization and to enable collaboration among multiple viewing locations, we developed an open source approach requiring only a standard web browser with no added client-side software.

We discuss the use of structural models for the analysis of biosurveillance related data.

Alert fatigue represents a common problem associated with the use of clinical decision support systems in electronic health records (EHR). This problem is particularly profound with drug-drug interaction (DDI) alerts for which studies have reported override rates of approximately 90%. The objective of this study is to report consensus-based recommendations of an expert panel on DDI that can be safely made non-interruptive to the provider's workflow, in EHR, in an [...]

There is limited capacity to assess the comparative risks of medications after they enter the market. For rare adverse events, the pooling of data from multiple sources is necessary to have the power and sufficient population heterogeneity to detect differences in safety and effectiveness in genetic, ethnic and clinically defined subpopulations. However, combining datasets from different data custodians or jurisdictions to perform an analysis on the pooled data creates significant [...]