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Standardized surveillance syndromes do not exist but would facilitate sharing data among surveillance systems and comparing the accuracy of existing systems. The objective of this study was to create reference syndrome definitions from a consensus of investigators who currently have or are building syndromic surveillance systems.

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 [...]

There is significant interest in leveraging the electronic medical record (EMR) to conduct genome-wide association studies (GWAS).

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.

Pharmacotherapy is an integral part of any medical care process and plays an important role in the medical history of most patients. Information on medication is crucial for several tasks such as pharmacovigilance, medical decision or biomedical research.

In the i2b2 Medication Extraction Challenge, medication names together with details of their administration were to be extracted from medical discharge summaries.

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.

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.

Within the context of the Third i2b2 Workshop on Natural Language Processing Challenges for Clinical Records, the authors (also referred to as 'the i2b2 medication challenge team' or 'the i2b2 team' for short) organized a community annotation experiment.

We aim to build and evaluate an open-source natural language processing system for information extraction from electronic medical record clinical free-text. We describe and evaluate our system, the clinical Text Analysis and Knowledge Extraction System (cTAKES), released open-source at http://www.ohnlp.org. The cTAKES builds on existing open-source technologies-the Unstructured Information Management Architecture framework and OpenNLP natural language processing toolkit. Its components, specifically trained for the clinical domain, create rich linguistic and [...]