A journal's role in resource sharing and reproducibility.
Author(s): Ohno-Machado, Lucila
DOI: 10.1093/jamia/ocv057
Author(s): Ohno-Machado, Lucila
DOI: 10.1093/jamia/ocv057
Author(s): Richesson, Rachel L, Chute, Christopher G
DOI: 10.1093/jamia/ocv039
We show how the HL7 Virtual Medical Record (vMR) standard can be used to design and implement a data integrator (DI) component that collects patient information from heterogeneous sources and stores it into a personal health record, from which it can then retrieve data. Our working hypothesis is that the HL7 vMR standard in its release 1 version can properly capture the semantics needed to drive evidence-based clinical decision support [...]
Author(s): Marcos, Carlos, González-Ferrer, Arturo, Peleg, Mor, Cavero, Carlos
DOI: 10.1093/jamia/ocv003
There is a lack of recommended models for clinical informatics (CI) governance that can facilitate successful health information technology implementation.
Author(s): Collins, Sarah A, Alexander, Dana, Moss, Jacqueline
DOI: 10.1093/jamia/ocu001
Develop and evaluate a foundational oncology-specific standard for the communication and coordination of care throughout the cancer journey, with early-stage breast cancer as the use case.
Author(s): Warner, Jeremy L, Maddux, Suzanne E, Hughes, Kevin S, Krauss, John C, Yu, Peter Paul, Shulman, Lawrence N, Mayer, Deborah K, Hogarth, Mike, Shafarman, Mark, Stover Fiscalini, Allison, Esserman, Laura, Alschuler, Liora, Koromia, George Augustine, Gonzaga, Zabrina, Ambinder, Edward P
DOI: 10.1093/jamia/ocu015
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 [...]
Author(s): Rajamani, Sripriya, Chen, Elizabeth S, Akre, Mari E, Wang, Yan, Melton, Genevieve B
DOI: 10.1136/amiajnl-2014-003100
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.
Author(s): Mortensen, Jonathan M, Minty, Evan P, Januszyk, Michael, Sweeney, Timothy E, Rector, Alan L, Noy, Natalya F, Musen, Mark A
DOI: 10.1136/amiajnl-2014-002901
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 [...]
Author(s): Ochs, Christopher, Geller, James, Perl, Yehoshua, Chen, Yan, Xu, Junchuan, Min, Hua, Case, James T, Wei, Zhi
DOI: 10.1136/amiajnl-2014-003151
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 [...]
Author(s): Ochs, Christopher, Geller, James, Perl, Yehoshua, Chen, Yan, Agrawal, Ankur, Case, James T, Hripcsak, George
DOI: 10.1136/amiajnl-2014-003173
Markers of illness severity are increasingly captured in emergency department (ED) electronic systems, but their value for surveillance is not known. We assessed the value of age, triage score, and disposition data from ED electronic records for predicting influenza-related hospitalizations.
Author(s): Savard, Noémie, Bédard, Lucie, Allard, Robert, Buckeridge, David L
DOI: 10.1093/jamia/ocu002