National Centers for Biomedical Computing: from the BISTI report to the future.
Author(s): Berg, Jeremy M
DOI: 10.1136/amiajnl-2011-000800
Author(s): Berg, Jeremy M
DOI: 10.1136/amiajnl-2011-000800
Since 2007, New York City's primary care information project has assisted over 3000 providers to adopt and use a prevention-oriented electronic health record (EHR). Participating practices were taught to re-adjust their workflows to use the EHR built-in population health monitoring tools, including automated quality measures, patient registries and a clinical decision support system. Practices received a comprehensive suite of technical assistance, which included quality improvement, EHR customization and configuration, privacy [...]
Author(s): Parsons, Amanda, McCullough, Colleen, Wang, Jason, Shih, Sarah
DOI: 10.1136/amiajnl-2011-000557
The performance of a classification system depends on the context in which it will be used, including the prevalence of the classes and the relative costs of different types of errors. Metrics such as accuracy are limited to the context in which the experiment was originally carried out, and metrics such as sensitivity, specificity, and receiver operating characteristic area--while independent of prevalence--do not provide a clear picture of the performance [...]
Author(s): Hripcsak, George
DOI: 10.1136/amiajnl-2011-000633
Translational informatics (TI) is extremely important for the pharmaceutical industry, especially as the bar for regulatory approval of new medications is set higher and higher. This paper will explore three specific areas in the drug development lifecycle, from tools developed by precompetitive consortia to standardized clinical data collection to the effective delivery of medications using clinical decision support, in which TI has a major role to play. Advancing TI will [...]
Author(s): Cantor, Michael N
DOI: 10.1136/amiajnl-2011-000588
The relationship between diseases and their causative genes can be complex, especially in the case of polygenic diseases. Further exacerbating the challenges in their study is that many genes may be causally related to multiple diseases. This study explored the relationship between diseases through the adaptation of an approach pioneered in the context of information retrieval: vector space models.
Author(s): Sarkar, Indra Neil
DOI: 10.1136/amiajnl-2011-000480
Accurate clinical problem lists are critical for patient care, clinical decision support, population reporting, quality improvement, and research. However, problem lists are often incomplete or out of date.
Author(s): Wright, Adam, Pang, Justine, Feblowitz, Joshua C, Maloney, Francine L, Wilcox, Allison R, McLoughlin, Karen Sax, Ramelson, Harley, Schneider, Louise, Bates, David W
DOI: 10.1136/amiajnl-2011-000521
The utility of healthcare utilization data from US emergency departments (EDs) for rapid monitoring of changes in influenza-like illness (ILI) activity was highlighted during the recent influenza A (H1N1) pandemic. Monitoring has tended to rely on detection algorithms, such as the Early Aberration Reporting System (EARS), which are limited in their ability to detect subtle changes and identify disease trends.
Author(s): Kass-Hout, Taha A, Xu, Zhiheng, McMurray, Paul, Park, Soyoun, Buckeridge, David L, Brownstein, John S, Finelli, Lyn, Groseclose, Samuel L
DOI: 10.1136/amiajnl-2011-000793
This paper explored pharmacy staff perceptions of the strengths and weaknesses of electronic prescribing (e-prescribing) design in retail pharmacies using the sociotechnical systems framework. This study examined how adoption of e-prescribing technology is affecting clinical practice and patient care.
Author(s): Odukoya, Olufunmilola, Chui, Michelle A
DOI: 10.1136/amiajnl-2011-000779
To present a framework for combining implicit knowledge acquisition from multiple experts with machine learning and to evaluate this framework in the context of anemia alerts.
Author(s): Joffe, Erel, Havakuk, Ofer, Herskovic, Jorge R, Patel, Vimla L, Bernstam, Elmer Victor
DOI: 10.1136/amiajnl-2012-000849
Meaningful exchange of information is a fundamental challenge in collaborative biomedical research. To help address this, the authors developed the Life Sciences Domain Analysis Model (LS DAM), an information model that provides a framework for communication among domain experts and technical teams developing information systems to support biomedical research. The LS DAM is harmonized with the Biomedical Research Integrated Domain Group (BRIDG) model of protocol-driven clinical research. Together, these models [...]
Author(s): Freimuth, Robert R, Freund, Elaine T, Schick, Lisa, Sharma, Mukesh K, Stafford, Grace A, Suzek, Baris E, Hernandez, Joyce, Hipp, Jason, Kelley, Jenny M, Rokicki, Konrad, Pan, Sue, Buckler, Andrew, Stokes, Todd H, Fernandez, Anna, Fore, Ian, Buetow, Kenneth H, Klemm, Juli D
DOI: 10.1136/amiajnl-2011-000763