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The National Center for Biomedical Ontology

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第2期19卷 190-195页

作者： Musen, Mark A. Noy, Natalya F. Shah, Nigam H. Whetzel, Patricia L. Chute, Christopher G. Story, Margaret-Anne Smith, Barry Stanford Univ Ctr Biomed Informat Res Stanford CA 94305 USA Mayo Clin Div Biomed Stat & Informat Rochester MN USA Univ Victoria Dept Comp Sci Victoria BC Canada SUNY Buffalo Dept Philosophy Buffalo NY 14260 USA

The National Center for Biomedical Ontology is now in its seventh year. The goals of this National Center for Biomedical Computing are to: create and maintain a repository of biomedical ontologies and terminologies;build tools and web services to enable the use of ontologies and terminologies in clinical and translational research;educate their trainees and the scientific community broadly about biomedical ontology and ontology-based technology and best practices;and collaborate with a variety of groups who develop and use ontologies and terminologies in biomedicine. The centerpiece of the National Center for Biomedical Ontology is a web-based resource known as BioPortal. BioPortal makes available for research in computationally useful forms more than 270 of the world's biomedical ontologies and terminologies, and supports a wide range of web services that enable investigators to use the ontologies to annotate and retrieve data, to generate value sets and special-purpose lexicons, and to perform advanced analytics on a wide range of biomedical data.

关键词： Collaborative technologies knowledge representations knowledge acquisition and knowledge management controlled terminologies and vocabularies ontologies knowledge bases applications that link biomedical knowledge from diverse primary sources (includes automated indexing) statistical analysis of large datasets methods for integration of information from disparate sources discovery and text and data mining methods automated learning information retrieval HIT data standards representing identifying and modeling biological structures developing and refining ehr data standards (including image standards)

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Utility of gene-specific algorithms for predicting pathogenicity of uncertain gene variants

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第2期19卷 207-211页

作者： Crockett, David K. Lyon, Elaine Williams, Marc S. Narus, Scott P. Facelli, Julio C. Mitchell, Joyce A. Univ Utah Sch Med Dept Biomed Informat Salt Lake City UT USA Univ Utah Sch Med Dept Pathol Salt Lake City UT USA Intermt Healthcare Clin Genet Inst Salt Lake City UT USA Univ Utah Ctr High Performance Comp Salt Lake City UT USA

The rapid advance of gene sequencing technologies has produced an unprecedented rate of discovery of genome variation in humans. A growing number of authoritative clinical repositories archive gene variants and disease phenotypes, yet there are currently many more gene variants that lack clear annotation or disease association. To date, there has been very limited coverage of gene-specific predictors in the literature. Here the evaluation is presented of "gene-specific" predictor models based on a naive Bayesian classifier for 20 gene-disease datasets, containing 3986 variants with clinically characterized patient conditions. The utility of gene-specific prediction is then compared with "all-gene" generalized prediction and also with existing popular predictors. Gene-specific computational prediction models derived from clinically curated gene variant disease datasets often outperform established generalized algorithms for novel and uncertain gene variants.

关键词： Amino acid properties gene variant classification machine learning phenotype prediction bioinformatics gene variants classification gene disease database developing/using computerized provider order entry designing usable (responsive) resources and systems methods for integration of information from disparate sources high-performance and large-scale computing distributed systems agents software engineering: architecture data exchange communication integration across care settings (inter- and intra-enterprise) system implementation and management issues languages computational methods statistical analysis of large datasets advanced algorithms identifying genome and protein structure and function detecting disease outbreaks and biological threats visualization of data and knowledge

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Applying knowledge-anchored hypothesis discovery methods to advance clinical and translational research: the OAMiner project

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第6期19卷 1110-1114页

作者： Payne, Philip R. O. Jackson, Rebecca D. Best, Thomas M. Borlawsky, Tara B. Lai, Albert M. James, Stephen Gurcan, Metin N. Ohio State Univ Dept Biomed Informat Columbus OH 43210 USA Ohio State Univ Dept Internal Med Columbus OH 43210 USA Ohio State Univ Dept Family Med Columbus OH 43210 USA

The conduct of clinical and translational research regularly involves the use of a variety of heterogeneous and large-scale data resources. Scalable methods for the integrative analysis of such resources, particularly when attempting to leverage computable domain knowledge in order to generate actionable hypotheses in a high-throughput manner, remain an open area of research. In this report, we describe both a generalizable design pattern for such integrative knowledge-anchored hypothesis discovery operations and our experience in applying that design pattern in the experimental context of a set of driving research questions related to the publicly available Osteoarthritis Initiative data repository. We believe that this 'test bed' project and the lessons learned during its execution are both generalizable and representative of common clinical and translational research paradigms.

关键词： Informatics computing methodologies knowledge bases research design phenotype biological markers visualization of data and knowledge translational research—application of biological knowledge to clinical care linking the genotype and phenotype methods for integration of information from disparate sources knowledge acquisition and knowledge management skeletal muscle cartilage osteoarthritis data modeling and integration knowledge representations data models imaging informatics image analysis CAD radiology pathology

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Using EHRs to integrate research with patient care: promises and challenges

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第5期19卷 684-687页

作者： Weng, Chunhua Appelbaum, Paul Hripcsak, George Kronish, Ian Busacca, Linda Davidson, Karina W. Bigger, J. Thomas Columbia Univ Dept Biomed Informat New York NY 10032 USA Columbia Univ Irving Inst Clin & Translat Res New York NY 10032 USA Columbia Univ Dept Psychiat New York NY 10032 USA Columbia Univ Dept Med New York NY 10032 USA Columbia Univ Clin Trials Off New York NY 10032 USA

Clinical research is the foundation for advancing the practice of medicine. However, the lack of seamless integration between clinical research and patient care workflow impedes recruitment efficiency, escalates research costs, and hence threatens the entire clinical research enterprise. Increased use of electronic health records (EHRs) holds promise for facilitating this integration but must surmount regulatory obstacles. Among the unintended consequences of current research oversight are barriers to accessing patient information for prescreening and recruitment, coordinating scheduling of clinical and research visits, and reconciling information about clinical and research drugs. We conclude that the EHR alone cannot overcome barriers in conducting clinical trials and comparative effectiveness research. Patient privacy and human subject protection policies should be clarified at the local level to exploit optimally the full potential of EHRs, while continuing to ensure participant safety. Increased alignment of policies that regulate the clinical and research use of EHRs could help fulfill the vision of more efficiently obtaining clinical research evidence to improve human health.

关键词： Knowledge bases knowledge acquisition knowledge representations methods for integration of information from disparate sources knowledge acquisition and knowledge management data mining electronic health records

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Clinical research informatics: a conceptual perspective

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第E1期19卷 E36-E42页

作者： Kahn, Michael G. Weng, Chunhua Univ Colorado Dept Pediat Aurora CO USA Columbia Univ Dept Biomed Informat New York NY USA

Clinical research informatics is the rapidly evolving sub-discipline within biomedical informatics that focuses on developing new informatics theories, tools, and solutions to accelerate the full translational continuum: basic research to clinical trials (T1), clinical trials to academic health center practice (T2), diffusion and implementation to community practice (T3), and 'real world' outcomes (T4). We present a conceptual model based on an informatics-enabled clinical research workflow, integration across heterogeneous data sources, and core informatics tools and platforms. We use this conceptual model to highlight 18 new articles in the JAMIA special issue on clinical research informatics.

关键词： Clinical research informatics clinical and translational research visualization of data and knowledge knowledge representations methods for integration of information from disparate sources data models data exchange knowledge bases knowledge acquisition knowledge acquisition and knowledge management

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Using ontology-based annotation to profile disease research

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第E1期19卷 E177-E186页

作者： Liu, Yi Coulet, Adrien LePendu, Paea Shah, Nigam H. Stanford Univ Stanford Ctr Biomed Informat Res Stanford CA 94305 USA LORIA INRIA Nancy Vandoeuvre Les Nancy France

Background Profiling the allocation and trend of research activity is of interest to funding agencies, administrators, and researchers. However, the lack of a common classification system hinders the comprehensive and systematic profiling of research activities. This study introduces ontology-based annotation as a method to overcome this difficulty. Analyzing over a decade of funding data and publication data, the trends of disease research are profiled across topics, across institutions, and over time. Results This study introduces and explores the notions of research sponsorship and allocation and shows that leaders of research activity can be identified within specific disease areas of interest, such as those with high mortality or high sponsorship. The funding profiles of disease topics readily cluster themselves in agreement with the ontology hierarchy and closely mirror the funding agency priorities. Finally, four temporal trends are identified among research topics. Conclusions This work utilizes disease ontology (DO)based annotation to profile effectively the landscape of biomedical research activity. By using DO in this manner a use-case driven mechanism is also proposed to evaluate the utility of classification hierarchies.

关键词： Applications that link biomedical knowledge from diverse primary sources (includes automated indexing) bioinformatics collaborative technologies informatics knowledge discovery knowledge representations machine learning medical records methods for integration of information from disparate sources natural language processing ontologies ontology pharmacogenomics statistical analysis of large datasets text mining

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The Hub Population Health System: distributed ad hoc queries and alerts

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第E1期19卷 E46-E50页

作者： Buck, Michael D. Anane, Sheila Taverna, John Amirfar, Sam Stubbs-Dame, Remle Singer, Jesse New York City Dept Hlth & Mental Hyg Bur Primary Care Informat Project Queens NY 11101 USA Columbia Univ Dept Biomed Informat New York NY USA

The Hub Population Health System enables the creation and distribution of queries for aggregate count information, clinical decision support alerts at the point-of-care for patients who meet specified conditions, and secure messages sent directly to provider electronic health record (EHR) inboxes. Using a metronidazole medication recall, the New York City Department of Health was able to determine the number of affected patients and message providers, and distribute an alert to participating practices. As of September 2011, the system is live in 400 practices and within a year will have over 532 practices with 2500 providers, representing over 2.5 million New Yorkers. The Hub can help public health experts to evaluate population health and quality improvement activities throughout the ambulatory care network. Multiple EHR vendors are building these features in partnership with the department's regional extension center in anticipation of new meaningful use requirements.

关键词： Decision support systems clinical public health informatics population surveillance electronic health records medical informatics developing/using computerized provider order entry methods for integration of information from disparate sources distributed systems agents software engineering: architecture PCIP ambulatory care new york city cardiovascular disease food environment population health

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The coming age of data-driven medicine: translational bioinformatics' next frontier

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第E1期19卷 E2-E4页

作者： Shah, Nigam H. Tenenbaum, Jessica D. Stanford Univ Sch Med Stanford Ctr Biomed Informat Res Stanford CA 94305 USA Duke Univ Duke Translat Med Inst Durham NC USA

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Using the time and motion method to study clinical work processes and workflow: methodological inconsistencies and a call for standardized research

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第5期18卷 704-710页

作者： Zheng, Kai Guo, Michael H. Hanauer, David A. Univ Michigan Sch Publ Hlth Dept Hlth Management & Policy Ann Arbor MI 48109 USA Univ Michigan Sch Informat Ann Arbor MI 48109 USA Univ Florida Coll Med Gainesville FL USA Univ Michigan Dept Pediat Ann Arbor MI 48109 USA Univ Michigan Ctr Comprehens Canc Ann Arbor MI 48109 USA

Objective To identify ways for improving the consistency of design, conduct, and results reporting of time and motion (TEM) research in health informatics. Materials and methods We analyzed the commonalities and divergences of empirical studies published 1990-2010 that have applied the T&M approach to examine the impact of health IT implementation on clinical work processes and workflow. The analysis led to the development of a suggested 'checklist' intended to help future T&M research produce compatible and comparable results. We call this checklist STAMP (Suggested Time And Motion Procedures). Results STAMP outlines a minimum set of 29 data/information elements organized into eight key areas, plus three supplemental elements contained in an 'Ancillary Data' area, that researchers may consider collecting and reporting in their future T&M endeavors. Discussion TEM is generally regarded as the most reliable approach for assessing the impact of health IT implementation on clinical work. However, there exist considerable inconsistencies in how previous TEN studies were conducted and/or how their results were reported, many of which do not seem necessary yet can have a significant impact on quality of research and generalisability of results. Therefore, we deem it is time to call for standards that can help improve the consistency of TEN research in health informatics. This study represents an initial attempt. Conclusion We developed a suggested checklist to improve the methodological and results reporting consistency of T&M research, so that meaningful insights can be derived from across-study synthesis and health informatics, as a field, will be able to accumulate knowledge from these studies.

关键词： Time and motion studies (F02.784.412.846.707) workflow (L01.906.893) health information technology (L01.700) medical informatics applications (L01.700.508) collaborative technologies personal health records and self-care systems developing/using clinical decision support (other than diagnostic) and guideline systems systems supporting patient-provider interaction human-computer interaction and human-centered computing improving healthcare workflow and process efficiency system implementation and management issues social/organizational study qualitative/ethnographic field study cognitive study (including experiments emphasizing verbal protocol analysis and usability) methods for integration of information from disparate sources information storage and retrieval (text and images) data exchange communication integration across care settings (inter- and intra-enterprise) visualization of data and knowledge developing/using computerized provider order entry

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Handling anticipated exceptions in clinical care: investigating clinician use of 'exit strategies' in an electronic health records system

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第6期18卷 883-889页

作者： Zheng, Kai Hanauer, David A. Padman, Rema Johnson, Michael P. Hussain, Anwar A. Ye, Wen Zhou, Xiaomu Diamond, Herbert S. Univ Michigan Sch Informat Dept Hlth Management & Policy Sch Publ Hlth Ann Arbor MI 48109 USA Univ Michigan Dept Pediat Ann Arbor MI 48109 USA Carnegie Mellon Univ H John Heinz Coll 3 Pittsburgh PA 15213 USA Univ Massachusetts Dept Publ Policy & Publ Affairs John W McCormack Grad Sch Policy Studies Boston MA 02125 USA United Hlth Serv Hosp Johnson City NY USA Univ Michigan Sch Publ Hlth Dept Biostat Ann Arbor MI 48109 USA Rutgers State Univ Sch Commun & Informat New Brunswick NJ 08903 USA Univ Pittsburgh Sch Med Dept Med Div Rheumatol Pittsburgh PA USA

Unpredictable yet frequently occurring exception situations pervade clinical care. Handling them properly often requires aberrant actions temporarily departing from normal practice. In this study, the authors investigated several exception-handling procedures provided in an electronic health records system for facilitating clinical documentation, which the authors refer to as 'data entry exit strategies.' Through a longitudinal analysis of computer-recorded usage data, the authors found that (1) utilization of the exit strategies was not affected by postimplementation system maturity or patient visit volume, suggesting clinicians' needs to 'exit' unwanted situations are persistent;and (2) clinician type and gender are strong predictors of exit-strategy usage. Drilldown analyses further revealed that the exit strategies were judiciously used and enabled actions that would be otherwise difficult or impossible. However, many data entries recorded via them could have been 'properly' documented, yet were not, and a considerable proportion containing temporary or incomplete information was never subsequently amended. These findings may have significant implications for the design of safer and more user-friendly point-of-care information systems for healthcare.

关键词： Electronic health records (E05.318.308.940.968.625.500) workflow (L01.906.893) documentation (L01.453.245) exit strategy exception-handling collaborative technologies personal health records and self-care systems developing/using clinical decision support (other than diagnostic) and guideline systems systems supporting patient–provider interaction human–computer interaction and human-centered computing improving healthcare workflow and process efficiency system implementation and management issues social/organizational study qualitative/ethnographic field study cognitive study (including experiments emphasizing verbal protocol analysis and usability) methods for integration of information from disparate sources information storage and retrieval (text and images) data exchange communication and integration across care settings (inter- and intraenterprise) visualization of data and knowledge developing/using computerized provider order entry diamond

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