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Adverse drug reaction (ADR) can have dire consequences. However, our current understanding of the causes of drug-induced toxicity is still limited. Hence it is of paramount importance to determine molecular factors of adverse drug responses so that safer therapies can be designed.

The rapidly growing volume of multimodal electrophysiological signal data is playing a critical role in patient care and clinical research across multiple disease domains, such as epilepsy and sleep medicine. To facilitate secondary use of these data, there is an urgent need to develop novel algorithms and informatics approaches using new cloud computing technologies as well as ontologies for collaborative multicenter studies.

To examine the impact of a personal health record (PHR) on medication-use safety among older adults.

Pharmacogenetics (PG) examines gene variations for drug disposition, response, or toxicity. At the National Institutes of Health Clinical Center (NIH CC), a multidepartment Pharmacogenetics Testing Implementation Committee (PGTIC) was established to develop clinical decision support (CDS) algorithms for abacavir, carbamazepine, and allopurinol, medications for which human leukocyte antigen (HLA) variants predict severe hypersensitivity reactions. Providing PG CDS in the electronic health record (EHR) during order entry could prevent adverse drug [...]

The infrastructure for data collection implemented by the National Consortium on Alcohol and NeuroDevelopment in Adolescence (N-CANDA) for data collection comprises several innovative features: (a) secure, asynchronous transfer and persistent storage of collected data via a revision control system; (b) two-stage import into a longitudinal database; and (c) use of a script-controlled web browser for data retrieval from a third-party, web-based neuropsychological test battery. The asynchronous operation of data transmission [...]

Real-time alerting systems typically warn providers about abnormal laboratory results or medication interactions. For more complex tasks, institutions create site-wide 'data warehouses' to support quality audits and longitudinal research. Sophisticated systems like i2b2 or Stanford's STRIDE utilize data warehouses to identify cohorts for research and quality monitoring. However, substantial resources are required to install and maintain such systems. For more modest goals, an organization desiring merely to identify patients with [...]

UK primary care databases, which contain diagnostic, demographic and prescribing information for millions of patients geographically representative of the UK, represent a significant resource for health services and clinical research. They can be used to identify patients with a specified disease or condition (phenotyping) and to investigate patterns of diagnosis and symptoms. Currently, extracting such information manually is time-consuming and requires considerable expertise. In order to exploit more fully the [...]

The specificity of medication-related alerts must be improved to overcome the pernicious effects of alert fatigue. A systematic comparison of new drug orders to historical orders could improve alert specificity and relevance. Using historical order data from a computerized provider order entry system, we alerted physicians to atypical orders during the prescribing of five medications: calcium, clopidogrel, heparin, magnesium, and potassium. The percentage of atypical orders placed for these five [...]

Usability testing is increasingly being recognized as a way to increase the usability and safety of health information technology (HIT). Medical simulation centers can serve as testing environments for HIT usability studies. We integrated the quality assurance version of our emergency department (ED) electronic health record (EHR) into our medical simulation center and piloted a clinical care scenario in which emergency medicine resident physicians evaluated a simulated ED patient and [...]

To summarize literature describing approaches aimed at automatically identifying patients with a common phenotype.