Multimodal Analgesia
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.
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.
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.
Laboratory results for ESR and RBC indices (hemoglobin, MCV, MCH, RDW… etc) should be extracted from the Laboratory databases. For Mayo, from January 1994 till October 2009, ESR and RBC test results were populated for our 3336 participants. All samples were collected on an outpatient basis. Samples collected during an inpatient hospitalization (admit date ≤ collection date ≤ discharge date) should be excluded unless this sample was the only one available for a patient.
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To identify cases with auto-immune rheumatologic phenotye (for NT198) we request information about auto-antibody (whether it was tested and what the restults were) and drug information (whether it was prescribed) for each patients that is enrolled in eMERGE. We are requesting every mention of any of the expanded generic drugs.
This phenotype includes RxNorm RxCUI codes for cancer therapies. These codes map to drug records in the PCORnet Common Data Model and other data sources. The phenotype was developed in 2019. Please see the associated files for additional information.
The development of this phenotype was supported by a Patient-Centered Outcomes Research Institute (PCORI) Award (No. CDRN-1306-04631) for the development of the national patient-centered clinical research network, known as PCORnet.
Genetic variation that predicts white blood count (WBC) and it differential, a marker of the health of the immune system.
WBC is unique among the identified inflammatory predictors of chronic disease in that it has been routinely measured in healthy patients in an unbiased way for the duration of the electronic medical record data.