Concerning SNOMED-CT content for public health case reports.
Author(s): Wilcke, Jeffrey R, Green, Julie M, Spackman, Kent A, Martin, Michael K, Case, James T, Santamaria, Suzanne L, Zimmerman, Kurt
DOI: 10.1136/jamia.2010.003756
Author(s): Wilcke, Jeffrey R, Green, Julie M, Spackman, Kent A, Martin, Michael K, Case, James T, Santamaria, Suzanne L, Zimmerman, Kurt
DOI: 10.1136/jamia.2010.003756
We report how seven independent critical access hospitals collaborated with a rural referral hospital to standardize workflow policies and procedures while jointly implementing the same health information technologies (HITs) to enhance medication care processes. The study hospitals implemented the same electronic health record, computerized provider order entry, pharmacy information systems, automated dispensing cabinets (ADC), and barcode medication administration systems. We conducted interviews and examined project documents to explore factors underlying [...]
Author(s): Wakefield, Douglas S, Ward, Marcia M, Loes, Jean L, O'Brien, John
DOI: 10.1136/jamia.2010.004267
OBJECTIVE To describe a new medication information extraction system-Textractor-developed for the 'i2b2 medication extraction challenge'. The development, functionalities, and official evaluation of the system are detailed.
Author(s): Meystre, Stéphane M, Thibault, Julien, Shen, Shuying, Hurdle, John F, South, Brett R
DOI: 10.1136/jamia.2010.004028
While essential for patient care, information related to medication is often written as free text in clinical records and, therefore, difficult to use in computerized systems. This paper describes an approach to automatically extract medication information from clinical records, which was developed to participate in the i2b2 2009 challenge, as well as different strategies to improve the extraction.
Author(s): Deléger, Louise, Grouin, Cyril, Zweigenbaum, Pierre
DOI: 10.1136/jamia.2010.003962
In the i2b2 Medication Extraction Challenge, medication names together with details of their administration were to be extracted from medical discharge summaries.
Author(s): Tikk, Domonkos, Solt, Illés
DOI: 10.1136/jamia.2010.004119
This study presents a system developed for the 2009 i2b2 Challenge in Natural Language Processing for Clinical Data, whose aim was to automatically extract certain information about medications used by a patient from his/her medical report. The aim was to extract the following information for each medication: name, dosage, mode/route, frequency, duration and reason.
Author(s): Spasic, Irena, Sarafraz, Farzaneh, Keane, John A, Nenadic, Goran
DOI: 10.1136/jamia.2010.003657
Medication information comprises a most valuable source of data in clinical records. This paper describes use of a cascade of machine learners that automatically extract medication information from clinical records.
Author(s): Patrick, Jon, Li, Min
DOI: 10.1136/jamia.2010.003939
The Third i2b2 Workshop on Natural Language Processing Challenges for Clinical Records focused on the identification of medications, their dosages, modes (routes) of administration, frequencies, durations, and reasons for administration in discharge summaries. This challenge is referred to as the medication challenge. For the medication challenge, i2b2 released detailed annotation guidelines along with a set of annotated discharge summaries. Twenty teams representing 23 organizations and nine countries participated in the [...]
Author(s): Uzuner, Ozlem, Solti, Imre, Cadag, Eithon
DOI: 10.1136/jamia.2010.003947
Electronic health records (EHRs) and EHR-connected patient portals offer patient-provider collaboration tools for visit-based care. During a randomized controlled trial, primary care patients completed pre-visit electronic journals (eJournals) containing EHR-based medication, allergies, and diabetes (study arm 1) or health maintenance, personal history, and family history (study arm 2) topics to share with their provider. Assessment with surveys and usage data showed that among 2027 patients invited to complete an eJournal [...]
Author(s): Wald, Jonathan S, Businger, Alexandra, Gandhi, Tejal K, Grant, Richard W, Poon, Eric G, Schnipper, Jeffrey L, Volk, Lynn A, Middleton, Blackford
DOI: 10.1136/jamia.2009.001362
In 2005, the American Medical Informatics Association undertook a set of activities relating to clinical decision support (CDS), with support from the office of the national coordinator and the Agency for Healthcare Research and Quality. They culminated in the release of the roadmap for national action on CDS in 2006. This article assesses progress toward the short-term goals within the roadmap, and recommends activities to continue to improve CDS adoption [...]
Author(s): Lyman, Jason A, Cohn, Wendy F, Bloomrosen, Meryl, Detmer, Don E
DOI: 10.1136/jamia.2010.005561