Geriatric

Diverticulosis and Diverticulitis

An algorithm for finding patients with diverticulosis, and of those, patients who also have diverticulitis, and to also find control patients.  Control patients will have had a colonoscopy but have no evidence of diverticula.

Simple NLP (a portable program is posted here, with instructions, and support is availabe from NU as needed) of colonoscopy reports is the gold standard algorithm, but if the text of colonoscopy reports is not available, an alternate algorithm using CPT & ICD-9 codes can be used, which is also posted.

Owner Phenotyping Groups: 
eMERGE Phenotype WG
View Phenotyping Groups: 
eMERGE Phenotype WG
Final

Hearing Loss

Phenotype Description:  individuals with sensorineural hearing loss (SNHL)
Below are algorithms used to identify individuals with SNHL at BioVU. If you have questions regarding any of the information presented on this page, you may contact either:
Wei-Qi Wei at wei-qi.wei@vanderbilt.edu or Joshua Denny at josh.denny@vanderbilt.edu

Owner Phenotyping Groups: 
Denny’s Group at Vandy
eMERGE Phenotype WG
eMERGE Vanderbilt Group
View Phenotyping Groups: 
Denny’s Group at Vandy
eMERGE CCHMC Group
eMERGE CCHMC/BCH Group
eMERGE CHOP Group
eMERGE Columbia Group
eMERGE Geisinger Group
eMERGE GHC/University of Washington Group
eMERGE Harvard Group
eMERGE Marshfield Group
eMERGE Mayo Group
eMERGE Meharry Group
eMERGE Mount Sinai Group
eMERGE Northwestern Group
eMERGE Phenotype WG
eMERGE Vanderbilt Group
Vanderbilt - SD/RD Group
Final

Ovarian/Uterine Cancer (OvUtCa)

The KPWA/UW-led ovarian/uterine cancer phenotype has been validated at Mayo Clinic, the secondary phenotype development site.  Validation results at both the primary and secondary sites were strong and the phenotype is ready for network wide implementation.  The pseudo code document posted 11/30/2017 is correct as is and should be used by network sites for phenotype implementation.  A validated data dictionary of covariates for this phenotype will be added to PheKB by 2/15/2018, but sites are encouraged to begin implementing the phenotype algorithm now.

Owner Phenotyping Groups: 
eMERGE GHC/University of Washington Group
View Phenotyping Groups: 
eMERGE CCHMC Group
eMERGE CCHMC/BCH Group
eMERGE CHOP Group
eMERGE Columbia Group
eMERGE Geisinger Group
eMERGE GHC/University of Washington Group
eMERGE Harvard Group
eMERGE Marshfield Group
eMERGE Mayo Group
eMERGE Meharry Group
eMERGE Mount Sinai Group
eMERGE Northwestern Group
eMERGE Phenotype WG
eMERGE Vanderbilt Group
Final

PGx medication risk prediction model

This algorithm predicts those who are going to be exposed to warfarin, simvastatin, or clopidogrel as three medications that have known pharmacogenomic influences.  This algorithm was used to select individuals for the Vanderbilt PREDICT (Pharmacogenomic Resource for Enhanced Decisions in Care & Treatment) program, which prospectively tests individuals at risk of needing medications whose efficacy is effected by genetic variants.  

 

For more information on PREDICT, see http://mydruggenome.org.

Owner Phenotyping Groups: 
eMERGE Vanderbilt Group
View Phenotyping Groups: 
Denny’s Group at Vandy
eMERGE Phenotype WG
Final

SLE (Systemic Lupus Erythematosus) using SLICC (Systemic Lupus Internation Collaborating Clinics) Criteria

Systemic Lupus Erythematosus (SLE) is a chronic, systemic autoimmune disease that can affect many parts of the body including skin, lungs, brain, heart, kidneys, joints, and blood vessels. SLE presentation can vary significantly between patients. Because of this, it can be challenging to identify a patient as having SLE. Between 300,000 and 2,000,000 people in the US are estimated to have SLE. Determination of an exact number of people affected is challenging as the disease is difficult to identify given the diverse presentations and the length of time it may take for symptoms to appear.

Owner Phenotyping Groups: 
eMERGE Northwestern Group
View Phenotyping Groups: 
eMERGE Mayo Group
eMERGE Phenotype WG
Final

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