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To help cancer registrars efficiently and accurately identify reportable cancer cases.

To illustrate ways in which clinical decision support systems (CDSSs) malfunction and identify patterns of such malfunctions.

To describe the characteristics and online practices of patients and "care partners" who share explicit access to a patient portal account at a large integrated health system that implemented shared access functionality in 2003.

Maintaining patient privacy is a challenge in large-scale observational research. To assist in reducing the risk of identifying study subjects through publicly available data, we introduce a method for obscuring date information for clinical events and patient characteristics.

First, to evaluate the effect of standard vs pictograph-enhanced discharge instructions on patients' immediate and delayed recall of and satisfaction with their discharge instructions. Second, to evaluate the effect of automated pictograph enhancement on patient satisfaction with their discharge instructions.

Traditionally, patient groups with a phenotype are selected through rule-based definitions whose creation and validation are time-consuming. Machine learning approaches to electronic phenotyping are limited by the paucity of labeled training datasets. We demonstrate the feasibility of utilizing semi-automatically labeled training sets to create phenotype models via machine learning, using a comprehensive representation of the patient medical record.

The management of HIV infection requires extensive, longitudinal information record-keeping and coordination to ensure optimal monitoring and outcomes of care and treatment.

We investigate the technology affordances associated with and anticipated from an online human immunodeficiency virus (HIV) prevention awareness platform, myHealthImpactNetwork, intended to reach black female college students. This population is at increased risk for HIV transmission, but is not often studied. In addition, this population regularly uses digital tools, including Web sites and social media platforms, to engage in health information seeking.

Recent massive investment in electronic health records (EHRs) was predicated on the assumption of improved patient safety, research capacity, and cost savings. However, most US health systems and health records are fragmented and do not share patient information. Our study compared information available in a typical EHR with more complete data from insurance claims, focusing on diagnoses, visits, and hospital care for depression and bipolar disorder.

To assess the relationship between (1) task demands and workload, (2) task demands and performance, and (3) workload and performance, all during physician-computer interactions in a simulated environment.