HIV
Algorithm for the identification of all patients aged 13 or older with HIV in an electronic health record dataset.
Algorithm for the identification of all patients aged 13 or older with HIV in an electronic health record dataset.
Project Outline: Selection of all Caucasian patients with hypothyroidism without a secondary cause of surgical removal or radiological ablation. The search is designed to eliminate subclinical hypothyroidism (by requiring that patients be on a replacement medication), medication-induced hypothyroidism (e.g., PTU, lithium, or history of amiodarone), and transient causes (e.g., pregnancy or subacute thyroiditis).
Described in this document are the Stanford University algorithms for extracting both cases and controls of Multimodal analgesia from electronic health records (EHR) for surgical patients.
Multiple Sclerosis (MS) phenotype algorithm for the DNA Databank demonstration project.
Non-alcoholic fatty liver disease (NAFLD)
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.
Peripheral Arterial Disease (PAD) is prevalent with approximately 10-12 million adults in US affected. For those with PAD, morbidity and mortality are high and quality of life is markedly impaired. The genetic basis of PAD is poorly understood and is the focus of the Mayo Clinic Electronic Medical Records and Genomics (eMERGE) Network study.
This is PhEMA (Phenotype Execution Modeling Architecture, projectphema.org)'s implementation of the following BPH (Benign Prostatic Hyperplasia) case algorithm from the following BPH case and control algorithm on PheKB:
https://phekb.org/phenotype/benign-prostatic-hyperplasia-bph
Artifacts for this phenotype, inc. an HQMF representation, a KNIME workflow that can run against an i2b2 instance, and a snapshot of the PhAT graphical representation, are posted on GitHub: