Electronic medical records (EMRs) are becoming an increasing important source of phenotypic information for clinical and genomic research. Researchers create and iteratively refine phenotype algorithms using structured and unstructured data to achieve high positive predictive values to identify true cases and controls from EMR data. The Phenotype KnowledgeBase (PheKB.org) is an online collaborative repository for building, validating, and sharing electronic phenotype algorithms and their performance characteristics.
On PheKB you can:
- View existing algorithms
- Enter or create new algorithms
- Collaborate with others to create or review algorithms
- View implementation details for existing algorithms
Phenotype algorithms can be viewed by data modalities or methods used:
- ICD and CPT codes
- Vital Signs
- Natural Language Processing
Algorithms can also be viewed by:
- Implementation results (positive predictive value, sensitivity, publications)
- Work Group
- Network affiliation (e.g., eMERGE, PGPop, PGRN)
Resources for Phenotyping
Phenotype Design Resources:
Phenotype development and validation. In this two-stage process a primary site first develops and executes the phenotype (boxes), and then secondary sites execute the phenotype. At each step feedback to primary and secondary sites may lead to revisions in the methods.*
* Newton KM, Peissig PL, Kho AN, Bielinski SJ, Berg RL, Choudhary V, Basford M, Chute CG, Kullo IJ, Li R, Pacheco JA, Rasmussen LV, Spangler L, Denny JC.Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network. J Am Med Inform Assoc. 2013 Jun;20(e1):e147-54. doi: 10.1136/amiajnl-2012-000896. Epub 2013 Mar 26.
- MEDI - MEDication Indication Resource - data-derived tables of medications and their indications
- Natural Language Processing Survey of Tools and Resources
- Phenome-wide association studies - PheWAS - grouping of ICD9 codes for clinical and genetic analysis
Validation methods Resources:
- Validation of electronic Medical record-based phenotyping algorithms: Results and Lessons Learned from the eMERGE Network. JAMIA 2013;20(e1):e147-54.
- Chapter 13: Mining Electronic Health Records in the Genomics Era. PLoS Comput Biol 8(12): e1002823.
Building data dictionaries for phenotypes
eleMAP - This allows researchers to harmonize their local phenotype data dictionaries to existing metadata and terminology standards such as the caDSR (Cancer Data Standards Registry and Repository), NCIT (NCI Thesaurus) and SNOMED-CT (Systematized Nomenclature of Medicine-Clinical Terms). Use this tool to search/browse metadata related to different studies, create new study & its related metadata, users can also export metdata in excel format.