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Clinical information models are formal specifications for representing the structure and semantics of the clinical content within electronic health record systems. This research aims to define, test, and validate evaluation metrics for software tools designed to support the processes associated with the definition, management, and implementation of these models.

To assess the public's preferences regarding potential privacy threats from devices or services storing health-related personal data.

This study assessed whether having an electronic health record (EHR) super-user, nurse champion for meaningful use (MU), and quality improvement (QI) team leading MU implementation is positively associated with MU Stage 1 demonstration.

To develop a secure, efficient, and easy-to-use data collection platform to measure the prevalence of sepsis in Wales over 24 hours.

Health care generated data have become an important source for clinical and genomic research. Often, investigators create and iteratively refine phenotype algorithms to achieve high positive predictive values (PPVs) or sensitivity, thereby identifying valid cases and controls. These algorithms achieve the greatest utility when validated and shared by multiple health care systems.Materials and Methods We report the current status and impact of the Phenotype KnowledgeBase (PheKB, http://phekb.org), an online environment [...]

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.

We describe use cases and an institutional reference architecture for maintaining high-capacity, data-intensive network flows (e.g., 10, 40, 100 Gbps+) in a scientific, medical context while still adhering to security and privacy laws and regulations.

To describe the creation and evaluate the usage of the first medical wiki linked to dedicated mobile applications.

As health information technologies become more prevalent in physician workflow, it is increasingly important to understand how physicians are using and interacting with these systems. This includes understanding how physicians search for information presented through health information technology systems. Eye tracking technologies provide a useful technique to understand how physicians visually search for information. However, analyzing eye tracking data can be challenging and is often done by measuring summative metrics [...]

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