Tables for Allergy NLP Matching

August 6, 2015

An accurate computable representation of food and drug allergy is essential for safe healthcare. We developed and evaluate a SQL-based method to map free-text allergy/adverse reaction entries to structured entries, using RxNorm as the target vocabulary.

PheWAS R Package

July 20, 2015

This package contains methods for performing PheWAS. Please contact PheWAS@vumc.org. if you encounter any errors or apparent bugs. The documentation is done natively in R. The command ?PheWAS once the package is loaded will direct you to the package description, including references to each function and an example. The command vignette("PheWAS-package") will display the package vignette with further "How to's".

PheWAS - phenome-wide association studies

April 8, 2015

PheWAS using ICD9 codes
 Our EMR-based PheWAS uses a custom-developed grouping of International Classification of Disease, 9th edition (ICD9) codes.  These grouping loosely follow the 3-digit (category) and section groupings defined with the ICD9 code system itself, but vary to include, for example, all hypertension codes (401-405) as one grouping.  Each custom PheWAS code group also has an associated control group that excludes other related conditions (e.g., a patient with Graves disease cannot be a control for thyroiditis).  
  

PheWAS - Phenome-Wide Association Studies

May 1, 2013

Methods to identify gene-disease associations primarily rely on clinical trials or observational cohorts and, more recently, Electronic Medical Record-linked DNA Biobanks.  At Vanderbilt, we have used an EMR-linked DNA biobank called BioVU to derive case and controls populations using data within the EMR to define clinical phenotypes.  Genetic data for these EMR-linked association studies are redeposited into BioVU for future EMR-linked studies.  This has opened the possibility of "reverse GWAS" or "Phenome-wide association studies" (PheWAS). 

MedEx - A tool for finding medication information

February 2, 2013

MedEx process free-text clinical records to recognize medication names and signature information, such as drug dose, frequency, route, and duration.  It uses a context-free grammar and regular expression parsing to process free text clinical notes.  After finding medication information, it maps to RxNorm and UMLS concepts at the most specific match it can find (e.g., medication name + strength would be preferred to medication name alone).

MEDI--an Ensemble MEDication Indication Resource

January 1, 2013

MEDI (MEDication Indication) is an ensemble medication indication resource for primary and secondary uses of electronic medical record (EMR) data.  MEDI was created based on multiple commonly used medication resources (RxNorm, MedlinePlus, SIDER 2, and Wikipedia ) and by leveraging both ontology and natural language processing (NLP) techniques. 
  

SecTag -- Tagging Clinical Note Section Headers

March 21, 2010

Clinical notes are often divided into sections, or segments, such as "history of present illness" or "past medical history." These sections often have subsections as well, such as the "cardiovascular exam" section of the "physical exam." One can gain greater understanding of clinical notes by recognition of the section in which a concept lives. For instance, both a "past medical history" and the "family medical history" sections can contain a list of diseases, but the context decribes very different import to the patient about whom the note was written.