Algorithm to select subjects with "normal" electrocardiograms. Subjects do not have heart disease, interfering medications, or abnormal electrolytes at the time of the normal ECG. Individuals may, however, develop abnormalities later in life.
Hypothetical timeline for a single patient:
We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes.
Chronic kidney disease (CKD) is defined as an abnormality of kidney structure or function present for longer than 3 months. CKD can occur as a result of heterogeneous disorders affecting the kidney. In the United States, an estimated 13.6% of adults have CKD. Notably, adjusted mortality rates are higher for patients with CKD than those without, and rates increase with CKD stage. The purpose of this algorithm is to enable accurate CKD diagnosis and staging based on EHR data.
Note: Attached documents contain full case definition and two different control definitions. One is for controls with 2 years of follow up, the other for controls with 1 year of follow up. All available controls with 2 years of follow up were used in Vanderbilt's study. The control population was supplemented by controls with only 1 year of follow up. At the time of study, many of the available controls had experienced their qualifying events somewhat recently and 2 years had not yet passed for full follow up.
A pheontype defining patients with strong evidence of having been diagnosed with colorectal cancer (cases) and patients who clearly do not have such diagnoses (controls). This phenotype is being used for sequencing studies. The only NLP involved in this phenotype is a very simple string search applied to pathology reports.
This phenotype specification supports the identification of patients with lung and gastroenteropancreatic (GEP) neuroendocrine tumors (NETs) for the Neuroendocrine Tumors- Patient-Reported Outcomes Study (NET-PRO) - a multi-site, patient-centered outcomes research initiative (PCORI) funded study (RD-2020C2-20329) conducted within PCORnet.
Algorithm for coronary heart disease (aka coronary artery disease) based on research done by the eMERGE Network. Cases are ascertained by either two ocurrences of diagnostic codes or one ocurrence of a procedural code. Defined as individuals with no diagnostic or procedural codes recorded. All ICD-9 and ICD-10 codes are labeled as diagnostic or procedural in the attached excel file.
Crohn's Disease phenotype algorithm for the DNA DataBank Demonstration Project. Case records are required to have more than 2 occurrences of ICD 9 codes and medications. Control records are required to not have ICD 9 codes or keyword mention of crohn* or Regional enteritis and excludes additional phenotypes as defined by ICD 9 codes and keywords.
Data source summary:
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Diagnostic Codes? |
Please see the PubMed reference below for background information about this phenotype & algorithm (a copy also attached).