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The intersection of electronic health records (EHR) and patient safety is complex. To examine the applicability of two previously developed conceptual models comprehensively to understand safety implications of EHR implementation in the English National Health Service (NHS).

The purpose of this integrative review based on the published literature was to identify information systems currently being used by local health departments and to determine the extent to which standard terminology was used to communicate data, interventions, and outcomes to improve public health informatics at the local health department (LHD) level and better inform research, policy, and programs.

In this paper, we focus on three aspects: (1) to annotate a set of standard corpus in Chinese discharge summaries; (2) to perform word segmentation and named entity recognition in the above corpus; (3) to build a joint model that performs word segmentation and named entity recognition.

Electronic health record (EHR) use in ambulatory care can improve safety and quality; however, problems with design, implementation, and poor interface with other systems lead users to develop 'workarounds', or behaviors users adopt to overcome perceived limitations in a technical system. We documented workarounds used in independent, community-based primary care practices, and developed a typology of their key features.

The aim of this paper is to report on the use of the systematised nomenclature of medicine clinical terms (SNOMED CT) by providing an overview of published papers.

To determine the accuracy of vendor-supplied dosing eRules for pediatric medication orders. Inaccurate or absent dosing rules can lead to high numbers of false alerts or undetected prescribing errors and may potentially compromise safety in this already vulnerable population.

To review the literature on the views of healthcare professionals to the linkage of healthcare data and to identify any potential barriers and/or facilitators to participation in a data linkage system.

Coding of clinical communication for fine-grained features such as speech acts has produced a substantial literature. However, annotation by humans is laborious and expensive, limiting application of these methods. We aimed to show that through machine learning, computers could code certain categories of speech acts with sufficient reliability to make useful distinctions among clinical encounters.

It is important to consider the way in which information is presented by the interfaces of clinical decision support systems, to favor the adoption of these systems by physicians. Interface design can focus on decision processes (guided navigation) or usability principles.

Challenges persist on how to effectively integrate the electronic health record (EHR) into patient visits and clinical workflow, while maintaining patient-centered care. Our goal was to identify variations in, barriers to, and facilitators of the use of the US Department of Veterans Affairs (VA) EHR in ambulatory care workflow in order better to understand how to integrate the EHR into clinical work. We observed and interviewed 20 ambulatory care providers [...]