Biomedical imaging informatics in the era of precision medicine: progress, challenges, and opportunities.
Author(s): Hsu, William, Markey, Mia K, Wang, May D
DOI: 10.1136/amiajnl-2013-002315
Author(s): Hsu, William, Markey, Mia K, Wang, May D
DOI: 10.1136/amiajnl-2013-002315
With the objective of bringing clinical decision support systems to reality, this article reviews histopathological whole-slide imaging informatics methods, associated challenges, and future research opportunities.
Author(s): Kothari, Sonal, Phan, John H, Stokes, Todd H, Wang, May D
DOI: 10.1136/amiajnl-2012-001540
National organizations historically focused on increasing use of effective services are now attempting to identify and discourage use of low-value services. Electronic health records (EHRs) could be used to measure use of low-value services, but few studies have examined this. The aim of the study was to: (1) determine if EHR data can be used to identify women eligible for an extended Pap testing interval; (2) determine the proportion of [...]
Author(s): Mathias, Jason S, Gossett, Dana, Baker, David W
DOI: 10.1136/amiajnl-2011-000536
To explore the feasibility of using statistical text classification to automatically detect extreme-risk events in clinical incident reports.
Author(s): Ong, Mei-Sing, Magrabi, Farah, Coiera, Enrico
DOI: 10.1136/amiajnl-2011-000562
To address the challenge of balancing privacy with the need to create cross-site research registry records on individual patients, while matching the data for a given patient as he or she moves between participating sites. To evaluate the strategy of generating anonymous identifiers based on real identifiers in such a way that the chances of a shared patient being accurately identified were maximized, and the chances of incorrectly joining two [...]
Author(s): Weber, Susan C, Lowe, Henry, Das, Amar, Ferris, Todd
DOI: 10.1136/amiajnl-2011-000329
To study ontology modularization techniques when applied to SNOMED CT in a scenario in which no previous corpus of information exists and to examine if frequency-based filtering using MEDLINE can reduce subset size without discarding relevant concepts.
Author(s): López-García, Pablo, Boeker, Martin, Illarramendi, Arantza, Schulz, Stefan
DOI: 10.1136/amiajnl-2011-000503
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 [...]
Author(s): Buck, Michael D, Anane, Sheila, Taverna, John, Amirfar, Sam, Stubbs-Dame, Remle, Singer, Jesse
DOI: 10.1136/amiajnl-2011-000322
Although the penetration of electronic health records is increasing rapidly, much of the historical medical record is only available in handwritten notes and forms, which require labor-intensive, human chart abstraction for some clinical research. The few previous studies on automated extraction of data from these handwritten notes have focused on monolithic, custom-developed recognition systems or third-party systems that require proprietary forms.
Author(s): Rasmussen, Luke V, Peissig, Peggy L, McCarty, Catherine A, Starren, Justin
DOI: 10.1136/amiajnl-2011-000182
Standard written methods of presenting research information may be difficult for many parents and children to understand. This pilot study was designed to examine the use of a novel prototype interactive consent program for describing a hypothetical pediatric asthma trial to parents and children. Parents and children were interviewed to examine their baseline understanding of key elements of a clinical trial, eg, randomization, placebo, and blinding. Subjects then reviewed age-appropriate [...]
Author(s): Tait, Alan R, Voepel-Lewis, Terri, McGonegal, Maureen, Levine, Robert
DOI: 10.1136/amiajnl-2011-000253
Failure to reach research subject recruitment goals is a significant impediment to the success of many clinical trials. Implementation of health-information technology has allowed retrospective analysis of data for cohort identification and recruitment, but few institutions have also leveraged real-time streams to support such activities.
Author(s): Ferranti, Jeffrey M, Gilbert, William, McCall, Jonathan, Shang, Howard, Barros, Tanya, Horvath, Monica M
DOI: 10.1136/amiajnl-2011-000115