Careers in informatics: a diversity of options with an abundance of jobs.
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2012-001363
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2012-001363
To develop and evaluate a text mining system for extracting key clinical features from vaccine adverse event reporting system (VAERS) narratives to aid in the automated review of adverse event reports.
Author(s): Botsis, Taxiarchis, Buttolph, Thomas, Nguyen, Michael D, Winiecki, Scott, Woo, Emily Jane, Ball, Robert
DOI: 10.1136/amiajnl-2012-000881
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2012-001224
Author(s): Russ, Alissa L, Weiner, Michael, Saleem, Jason J, Wears, Robert L
DOI: 10.1136/amiajnl-2012-001193
To understand the nature of emerging electronic documentation practices, disconnects between documentation workflows and computing systems designed to support them, and ways to improve the design of electronic documentation systems.
Author(s): Mamykina, Lena, Vawdrey, David K, Stetson, Peter D, Zheng, Kai, Hripcsak, George
DOI: 10.1136/amiajnl-2012-000901
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
Relation extraction in biomedical text mining systems has largely focused on identifying clause-level relations, but increasing sophistication demands the recognition of relations at discourse level. A first step in identifying discourse relations involves the detection of discourse connectives: words or phrases used in text to express discourse relations. In this study supervised machine-learning approaches were developed and evaluated for automatically identifying discourse connectives in biomedical text.
Author(s): Ramesh, Balaji Polepalli, Prasad, Rashmi, Miller, Tim, Harrington, Brian, Yu, Hong
DOI: 10.1136/amiajnl-2011-000775
To describe an analytical framework for quantifying the societal savings and financial consequences of a health information exchange (HIE), and to demonstrate its use in designing pricing policies for sustainable HIEs.
Author(s): Sridhar, Srikrishna, Brennan, Patricia Flatley, Wright, Stephen J, Robinson, Stephen M
DOI: 10.1136/amiajnl-2011-000606
Computerized provider order entry (CPOE) with clinical decision support (CDS) can help hospitals improve care. Little is known about what CDS is presently in use and how it is managed, however, especially in community hospitals. This study sought to address this knowledge gap by identifying standard practices related to CDS in US community hospitals with mature CPOE systems.
Author(s): Ash, Joan S, McCormack, James L, Sittig, Dean F, Wright, Adam, McMullen, Carmit, Bates, David W
DOI: 10.1136/amiajnl-2011-000705