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To understand the different types and causes of prescribing errors associated with computerized provider order entry (CPOE) systems, and recommend improvements in these systems.

Agency for Healthcare Research and Quality (AHRQ) software applies standardized algorithms to hospital administrative data to identify patient safety indicators (PSIs). The objective of this study was to assess the validity of PSI flags and report reasons for invalid flagging.

The United States Office of the National Coordinator for Health Information Technology sponsored the development of a "high-priority" list of drug-drug interactions (DDIs) to be used for clinical decision support. We assessed current adoption of this list and current alerting practice for these DDIs with regard to alert implementation (presence or absence of an alert) and display (alert appearance as interruptive or passive).

We explored whether use of deep learning to model temporal relations among events in electronic health records (EHRs) would improve model performance in predicting initial diagnosis of heart failure (HF) compared to conventional methods that ignore temporality.

Electronic trigger detection tools hold promise to reduce Adverse drug event (ADEs) through efficiencies of scale and real-time reporting. We hypothesized that such a tool could automatically detect medication dosing errors as well as manage and evaluate dosing rule modifications.

Government agencies are rapidly developing web portals to proactively publish "open" data that are searchable, available in nonproprietary formats, and with unlimited use and distribution rights. In this dynamic environment, we aimed to understand the experiences of 2 early leaders in open health data, the US Department of Health and Human Services and the New York State Department of Health.

Our objective was to compare the change in research informed knowledge of health professionals and their intended practice following exposure to research information delivered by either Twitter or Facebook.

To develop a descriptive model of structural characteristics of mHealth in the context of newborn nutrition, and to assess the effects of illustrative interventions through a mixed-methods study consisting of an impact evaluation and a qualitative assessment.

Although omics datasets represent valuable assets for hypothesis generation, model testing, and data validation, the infrastructure supporting their reuse lacks organization and consistency. Using nuclear receptor signaling transcriptomic datasets as proof of principle, we developed a model to improve the discoverability, accessibility, and citability of published omics datasets. Primary datasets were retrieved from archives, processed to extract data points, then subjected to metadata enrichment and gap filling. The resulting secondary [...]

To examine changes in patient outcome variables, length of stay (LOS), and mortality after implementation of computerized provider order entry (CPOE).