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There are few published studies of the use of portable or handheld computers in health care, but these devices have the potential to transform multiple aspects of clinical teaching and practice.

Usability problems in the electronic health record (EHR) lead to workflow inefficiencies when navigating charts and entering or retrieving data using standard keyboard and mouse interfaces. Voice input technology has been used to overcome some of the challenges associated with conventional interfaces and continues to evolve as a promising way to interact with the EHR.

Laboratory-based utilization management programs typically rely primarily on data derived from the laboratory information system to analyze testing volumes for trends and utilization concerns. We wished to examine the ability of an electronic health record (EHR) laboratory orders database to improve a laboratory utilization program.

Defining clinical conditions from electronic health record (EHR) data underpins population health activities, clinical decision support, and analytics. In an EHR, defining a condition commonly employs a diagnosis value set or "grouper." For constructing value sets, Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) offers high clinical fidelity, a hierarchical ontology, and wide implementation in EHRs as the standard interoperability vocabulary for problems.

U.S. poison control centers pose a special case for patient identity matching because they collect only minimal patient identifying information.

Holistic, ubiquitous support of patient-centered health care (eHealth) at all health care institutions and in patients' homes through information processing is increasingly supplementing institution-centered care. While eHealth indicators may measure the transition from institution-centered (e.g., hospital-centered) information processing to patient-centered information processing, collecting relevant and timely data for such indicators has been difficult.

The assessment of user preferences for performance characteristics of patient-oriented clinical prediction models is lacking. It is unknown if complex statistical aspects of prediction models are readily understandable by a general audience.