Algorithm to detect functional seizures, also known as:
Psychogenic nonepileptic seizures
Nonepileptic attack disorder
Pseudoseizures
Hystero-epilepsy
Conversion disorder with seizures
Dissociative Seizures
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
Herpes zoster, also known as zoster or shingles, is caused by a virus called varicella zoster virus (VZV). Initial infection with the virus causes chickenpox. After chickenpox resolves the virus continues to resides in certain nerve cells. It may remain latent for many years. It may also re-activate, many years later, and cause shingles which is a painful skin rash. How the virus remains latent in the body is not well understood.
Objective
We leveraged existing data from a single electronic health care system in the southeastern United States to demonstrate the feasibility of measuring quality indicators for the hospital-based care of opioid-exposed newborns using existing data infrastructure. Additionally, we identified other key variables related to the care of opioid-exposed maternal-infant dyads.
Patients and Methods
Objective
Observational studies examining outcomes among opioid-exposed infants are limited by phenotype algorithms that may under identify opioid-exposed infants without neonatal opioid withdrawal syndrome (NOWS). We developed and validated the performance of different phenotype algorithms to identify opioid-exposed infants using electronic health record (EHR) data.
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.
Identify bacterial pneumonia, similar to that reported with genetic association risk in CD143 and TLR4 A229G in literature.
This rheumatoid arthritis (RA) algorithm was created using a machine-learning logistic regression model.