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To conduct a series of focus groups with primary care physicians to determine the optimal format of a shortened, focused systematic review.

Increasing the adoption of electronic health records (EHRs) with integrated clinical decision support (CDS) is a key initiative of the current US healthcare administration. High over-ride rates of CDS alerts strongly limit these potential benefits. As a result, EHR designers aspire to improve alert design to achieve better acceptance rates. In this study, we evaluated drug-drug interaction (DDI) alerts generated in EHRs and compared them for compliance with human factors [...]

The Secretary of Health and Human Services (HHS) acting through the Food and Drug Administration (FDA), and in collaboration with the Federal Communications Commission (FCC) and Office of the National Coordinator for Health IT (ONC) was tasked with delivering a report on an appropriate, risk-based regulatory framework for health information technology (IT). An expert stakeholder group was established under the auspices of the Health IT Policy Committee to help provide [...]

The objective of this investigation is to evaluate binary prediction methods for predicting disease status using high-dimensional genomic data. The central hypothesis is that the Bayesian network (BN)-based method called efficient Bayesian multivariate classifier (EBMC) will do well at this task because EBMC builds on BN-based methods that have performed well at learning epistatic interactions.

To apply human factors engineering principles to improve alert interface design. We hypothesized that incorporating human factors principles into alerts would improve usability, reduce workload for prescribers, and reduce prescribing errors.

Drug-drug interactions (DDIs) are an important consideration in both drug development and clinical application, especially for co-administered medications. While it is necessary to identify all possible DDIs during clinical trials, DDIs are frequently reported after the drugs are approved for clinical use, and they are a common cause of adverse drug reactions (ADR) and increasing healthcare costs. Computational prediction may assist in identifying potential DDIs during clinical trials.

To evaluate the internal consistency, construct validity, and criterion validity of a battery of items measuring information technology (IT) adoption, included in the American Hospital Association (AHA) IT Supplement Survey.

The objective was to assess use of a physician handoff tool embedded in the electronic medical record by nurses and other non-physicians. We administered a survey to nurses, physical therapists, discharge planners, social workers, and others to assess integration into daily practice, usefulness, and accuracy of the handoff tool. 231 individuals (61% response) participated. 60% used the tool often or usually/always during a shift. Nurses (46%) used the tool for [...]

To determine the sensitivity and specificity of a dosing alert system for dosing errors and to compare the sensitivity of a proprietary system with and without institutional customization at a pediatric hospital.