Marjorie Carter

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reproduction in any medium, provided the original work is properly cited. Objective To highlight the importance of templates in extracting surveillance data from the free text of electronic medical records using natural language processing (NLP) techniques. Introduction The main stay of recording patient data is the free text of electronic medical records(More)
Patients report their symptoms and subjective experiences in their own words. These expressions may be clinically meaningful yet are difficult to capture using automated methods. We annotated subjective symptom expressions in 750 clinical notes from the Veterans Affairs EHR. Within each document, subjective symptom expressions were compared to mentions of(More)
Front line health care providers (HCPs) play a central role in endemic (pertussis), epidemic (influenza) and pandemic (avian influenza) infectious disease outbreaks. Effective preparedness for this role requires access to and awareness of population-based data (PBD). We investigated the degree to which this is currently achieved among HCPs in Utah by(More)
We describe the rates and predictors of initiation of treatment for chronic hepatitis C (HCV) infection in a large cohort of HCV positive Veterans seen in U.S. Department of Veterans Affairs (VA) facilities between January 1, 2004 and December 31, 2009. In addition, we identify the relationship between homelessness among these Veterans and treatment(More)
INTRODUCTION Substantial amounts of clinically significant information are contained only within the narrative of the clinical notes in electronic medical records. The v3NLP Framework is a set of "best-of-breed" functionalities developed to transform this information into structured data for use in quality improvement, research, population health(More)
INTRODUCTION Network projections of data can provide an efficient format for data exploration of co-incidence in large clinical datasets. We present and explore the utility of a network projection approach to finding patterns in health care data that could be exploited to prevent homelessness among U.S. Veterans. METHOD We divided Veteran ICD-9-CM (ICD9)(More)
Researchers at the U.S. Department of Veterans Affairs (VA) have used administrative criteria to identify homelessness among U.S. Veterans. Our objective was to explore the use of these codes in VA health care facilities. We examined VA health records (2002-2012) of Veterans recently separated from the military and identified as homeless using VA(More)
OBJECTIVE To develop a method to exploit the UMLS Metathesaurus for extracting and categorizing concepts found in clinical text representing signs and symptoms to anatomically related organ systems. The overarching goal is to classify patient reported symptoms to organ systems for population health and epidemiological analyses. MATERIALS AND METHODS Using(More)
"Identifying and labeling" (annotating) sections improves the effectiveness of extracting information stored in the free text of clinical documents. OBSecAn, an automated ontology-based section annotator, was developed to identify and label sections of semi-structured clinical documents from the Department of Veterans Affairs (VA). In the first step, the(More)