When 'technically preventable' alerts occur, the design--not the prescriber--has failed.
Author(s): Russ, Alissa L, Weiner, Michael, Saleem, Jason J, Wears, Robert L
DOI: 10.1136/amiajnl-2012-001193
Author(s): Russ, Alissa L, Weiner, Michael, Saleem, Jason J, Wears, Robert L
DOI: 10.1136/amiajnl-2012-001193
Author(s): Handler, Jonathan A, Adams, James G
DOI: 10.1136/amiajnl-2012-001149
Accurate and informed prescribing is essential to ensure the safe and effective use of medications in pediatric patients. Computerized clinical decision support (CCDS) functionalities have been embedded into computerized physician order entry systems with the aim of ensuring accurate and informed medication prescribing. Owing to a lack of comprehensive analysis of the existing literature, this review was undertaken to analyze the effect of CCDS implementation on medication prescribing and use [...]
Author(s): Stultz, Jeremy S, Nahata, Milap C
DOI: 10.1136/amiajnl-2011-000798
To demonstrate the potential of de-identified clinical data from multiple healthcare systems using different electronic health records (EHR) to be efficiently used for very large retrospective cohort studies.
Author(s): Kaelber, David C, Foster, Wendy, Gilder, Jason, Love, Thomas E, Jain, Anil K
DOI: 10.1136/amiajnl-2011-000782
Applying multiprofessional electronic health records (EHRs) is expected to improve the quality of patient care and patient safety. Both EHR systems and system users depend on semantic interoperability to function efficiently. A shared clinical terminology comprising unambiguous terms is required for semantic interoperability. Empirical studies of clinical terminology, such as predefined headings, in EHR systems are scarce and limited to one profession or one clinical specialty.
Author(s): Terner, Annika, Lindstedt, Helena, Sonnander, Karin
DOI: 10.1136/amiajnl-2012-000855
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
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 [...]
Author(s): Payne, Philip R O, Jackson, Rebecca D, Best, Thomas M, Borlawsky, Tara B, Lai, Albert M, James, Stephen, Gurcan, Metin N
DOI: 10.1136/amiajnl-2011-000736
Without careful attention to the work of users, implementation of health IT can produce new risks and inefficiencies in care. This paper uses the technology use mediation framework to examine the work of a group of nurses who serve as mediators of the adoption and use of a barcode medication administration (BCMA) system in an inpatient setting.
Author(s): Novak, Laurie L, Anders, Shilo, Gadd, Cynthia S, Lorenzi, Nancy M
DOI: 10.1136/amiajnl-2011-000575
Design and evaluation of the dietary intake monitoring application (DIMA) to assist varying-literacy patients receiving hemodialysis to adhere to their prescribed dietary regimen.
Author(s): Connelly, Kay, Siek, Katie A, Chaudry, Beenish, Jones, Josette, Astroth, Kim, Welch, Janet L
DOI: 10.1136/amiajnl-2011-000732
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 [...]
Author(s): Weng, Chunhua, Appelbaum, Paul, Hripcsak, George, Kronish, Ian, Busacca, Linda, Davidson, Karina W, Bigger, J Thomas
DOI: 10.1136/amiajnl-2012-000878