Abstract

? ? The MOMENT (Monitoring for Outpatient Medication Effects and New Toxicities) in TIME project will extend the in-progress TIME (Tools for Inpatient Monitoring using Evidence) for Safe and Appropriate Testing grant, #5 R01 LM007995-03, by developing sophisticated text-mining and data extraction tools to examine adverse drug effects in patients presenting for emergency and hospital care. ? ? Using a UMLS-based concept identifier enhanced with natural language processing, the MOMENT project will detect: (a) individual clinical manifestations (symptoms and physical exam findings) that are potentially drug related; (b) clinical syndromes (e.g., hepatoxicity, myopathy, renal insufficiency, glucose intolerance); and, (c) and clinical diseases (such as systemic lupus induced by hydralazine or procainamide, or acute myocardial infarction associated with rofecoxib). Innovative aspects of the proposed work include use of advanced natural language processing techniques to abstract concepts representing potential drug effects from patient history and physical examination records and ancillary test reports, the combination of evidence based templates and diagnostic algorithms to detect complex patterns of drug toxicity (e.g., hepatocelluar damage, pulmonary fibrosis, or acute coronary syndrome), advanced statistical methods for determining medication effects in large populations, and utilization of a clinical database containing data on more than 100,000 patients. ? ? Public Statement ? ? The MOMENT project (Monitoring for Outpatient Medication Effects and New Toxicities) will demonstrate the feasibility of combining informatics applications increasingly present in many healthcare institutions - electronic medical record systems and care provider order entry (CPOE) systems - to create an advanced detection and monitoring system for adverse medication effects. The project will develop tools and algorithms to detect the patient symptoms, physical exam signs, test results, and medical diagnoses that may indicate drug-induced injury. ? ? ?

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Research Project (R01)
Project #
2R01LM007995-04
Application #
7262635
Study Section
Biomedical Library and Informatics Review Committee (BLR)
Program Officer
Sim, Hua-Chuan
Project Start
2004-02-01
Project End
2010-06-14
Budget Start
2007-06-15
Budget End
2008-06-14
Support Year
4
Fiscal Year
2007
Total Cost
$304,785
Indirect Cost

  Institution

Name
Vanderbilt University Medical Center
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
004413456
City
Nashville
State
TN
Country
United States
Zip Code
37212

  Publications

Rosenbaum, Benjamin P; Silkin, Nikolay; Miller, Randolph A (2014) Easily configured real-time CPOE Pick Off Tool supporting focused clinical research and quality improvement. J Am Med Inform Assoc 21:564-8
Tang, Buzhou; Wu, Yonghui; Jiang, Min et al. (2013) A hybrid system for temporal information extraction from clinical text. J Am Med Inform Assoc 20:828-35
Atreya, Ravi V; Smith, Joshua C; McCoy, Allison B et al. (2013) Reducing patient re-identification risk for laboratory results within research datasets. J Am Med Inform Assoc 20:95-101
Fan, Jung-wei; Yang, Elly W; Jiang, Min et al. (2013) Syntactic parsing of clinical text: guideline and corpus development with handling ill-formed sentences. J Am Med Inform Assoc 20:1168-77
Smith, J C; Denny, J C; Chen, Q et al. (2013) Lessons learned from developing a drug evidence base to support pharmacovigilance. Appl Clin Inform 4:596-617
Tang, Buzhou; Cao, Hongxin; Wu, Yonghui et al. (2013) Recognizing clinical entities in hospital discharge summaries using Structural Support Vector Machines with word representation features. BMC Med Inform Decis Mak 13 Suppl 1:S1
Denny, Joshua C; Choma, Neesha N; Peterson, Josh F et al. (2012) Natural language processing improves identification of colorectal cancer testing in the electronic medical record. Med Decis Making 32:188-97
Schildcrout, Jonathan S; Haneuse, Sebastien; Peterson, Josh F et al. (2011) Analyses of longitudinal, hospital clinical laboratory data with application to blood glucose concentrations. Stat Med 30:3208-20
Carnevale, Randy J; Talbot, Thomas R; Schaffner, William et al. (2011) Evaluating the utility of syndromic surveillance algorithms for screening to detect potentially clonal hospital infection outbreaks. J Am Med Inform Assoc 18:466-72
Denny, Joshua C; Peterson, Josh F; Choma, Neesha N et al. (2010) Extracting timing and status descriptors for colonoscopy testing from electronic medical records. J Am Med Inform Assoc 17:383-8

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