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Poison control centers (PCCs) routinely collaborate with emergency departments (EDs) to provide care for poison-exposed patients. During this process, a significant amount of information is exchanged between EDs and PCCs via telephone, leading to important inefficiencies and safety vulnerabilities. In the present work, we identified and assessed a set of data standards to enable a standards-based health information exchange process between EDs and PCCs.

The American Recovery and Reinvestment Act (ARRA) of 2009 clearly articulated the central role that health information technology (HIT) standards would play in improving healthcare quality, safety, and efficiency through the meaningful use of certified, standards based, electronic health record (EHR) technology. In 2012, the Office of the National Coordinator (ONC) asked the Nationwide Health Information Network (NwHIN) Power Team of the Health Information Technology Standards Committee (HITSC) to develop [...]

There is wide recognition that, with the rapid implementation of electronic health records (EHRs), large data sets are available for research. However, essential standardized nursing data are seldom integrated into EHRs and clinical data repositories. There are many diverse activities that exist to implement standardized nursing languages in EHRs; however, these activities are not coordinated, resulting in duplicate efforts rather than building a shared learning environment and resources.

The ability to share nursing data across organizations and electronic health records is a key component of improving care coordination and quality outcomes. Currently, substantial organizational and technical barriers limit the ability to share and compare essential patient data that inform nursing care. Nursing leaders at Kaiser Permanente and the U.S. Department of Veterans Affairs collaborated on the development of an evidence-based information model driven by nursing practice to enable [...]

The healthcare landscape is changing, driven by innovative care models and the emergence of new roles that are inter-professional in nature. Currently, the HL7/LOINC Document Ontology (DO) aids the use and exchange of clinical documents using a multi-axis structure of document attributes for Kind of Document, Setting, Role, Subject Matter Domain, and Type of Service. In this study, the adequacy of the Role axis for representing the type of author [...]

The verification of biomedical ontologies is an arduous process that typically involves peer review by subject-matter experts. This work evaluated the ability of crowdsourcing methods to detect errors in SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) and to address the challenges of scalable ontology verification.

Standards terminologies may be large and complex, making their quality assurance challenging. Some terminology quality assurance (TQA) methodologies are based on abstraction networks (AbNs), compact terminology summaries. We have tested AbNs and the performance of related TQA methodologies on small terminology hierarchies. However, some standards terminologies, for example, SNOMED, are composed of very large hierarchies. Scaling AbN TQA techniques to such hierarchies poses a significant challenge. We present a scalable [...]

Large and complex terminologies, such as Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT), are prone to errors and inconsistencies. Abstraction networks are compact summarizations of the content and structure of a terminology. Abstraction networks have been shown to support terminology quality assurance. In this paper, we introduce an abstraction network derivation methodology which can be applied to SNOMED CT target hierarchies whose classes are defined using only hierarchical relationships (ie [...]