Phenotype Details

🎯 What This Phenotype Does

This phenotype identifies patients based on specific clinical criteria and can be executed across any OMOP CDM database.

  • ✅ Compatible with OHDSI Atlas
  • ✅ Direct SQL execution
  • ✅ WebAPI integration
  • ✅ Standardized vocabulary

📈 Execution Metrics

👥 Patient Demographics

📊 Available Phenotypes

Interactive Phenotype Execution Demo

Watch how this phenotype executes step-by-step:

Step 1: Loading Phenotype Definition

Loading JSON definition and parsing cohort logic...


                  

Step 2: Connecting to Database

Establishing connection to OMOP CDM database...


                  

Step 3: Executing Cohort Logic

Running the cohort definition against patient data...


                  

Step 4: Results Generated

Cohort execution completed successfully!


                  

📊 Execution Results

🎯 Cohort Summary

Atlas-Compatible JSON Definition

This JSON can be imported into OHDSI Atlas for cohort creation:


                  

📊 JSON Structure Analysis

🔍 Definition Components

Executable SQL Query

This SQL can be run directly against an OMOP CDM database:


                  

📊 SQL Complexity Analysis

🔧 Query Components

Vocabulary Mappings

Standardized medical concepts used in this phenotype:

📊 Concept Distribution

🏥 Domain Coverage

📋 Concept Set Details


                  

Sample Patient Charts

Review 5-10 randomly selected patients from this phenotype cohort:

🎯 Chart Review Summary

These patients were identified by the phenotype and represent typical cases in the cohort.

  • ✅ Clinical timeline visualization
  • ✅ Key events and diagnoses
  • ✅ Treatment patterns
  • ✅ Risk factors and comorbidities

📊 Patient Timeline Overview

👤 Individual Patient Charts

How to Execute This Phenotype

🌐 Method 1: OHDSI Atlas

  1. Open OHDSI Atlas
  2. Go to Cohort Definitions
  3. Import the JSON definition
  4. Generate cohort

💾 Method 2: Direct SQL

  1. Connect to OMOP CDM database
  2. Replace schema parameters
  3. Execute the SQL query
  4. Results in generated table

🔌 Method 3: WebAPI

  1. Use the JSON definition
  2. POST to /cohortdefinition
  3. Use returned ID for generation

🎯 Execution Best Practices

  • Always validate your database schema before execution
  • Test with a small subset of data first
  • Monitor execution time and resource usage
  • Review results for clinical validity
  • Document any modifications made to the phenotype