OHDSI
Waveform WGWelcome to the OHDSI Waveform Working Group! This page helps you get started whether you’re implementing the Waveform Extension, joining the working group, or proposing a use case.
The OMOP CDM Waveform Extension enables standardized integration of physiological waveform data with electronic health records. The extension consists of four interconnected tables:
1. waveform_occurrence → Define the recording session context
2. waveform_registry → Register individual waveform files
3. waveform_channel_metadata → Describe signal-level metadata
4. waveform_feature → Store derived features and measurements
Prerequisites: - OMOP CDM v5.4+ database - Physiological waveform data (ECG, EEG, ABP, etc.) - ETL development environment - Basic understanding of signal processing (recommended)
What you’ll need: - Raw waveform files with timestamps - Patient identifiers linkable to PERSON table - Visit/encounter context for acquisitions - Device and procedure metadata (if available)
See the Waveform Extension Implementation Guide for detailed ETL specifications.
Join the Waveform Working Group
Attend Working Group Meetings
Introduce Yourself
For Data Engineers: - Review the Implementation Guide - Check Table Specifications - Share your ETL approach and challenges - Contribute reference implementations to GitHub
For Researchers: - Propose use cases that require waveform data integration - Identify required features not yet in the specification - Share validation requirements - Collaborate on multi-site studies
For Developers: - Build ETL tools for common waveform formats (EDF, WFDB, etc.) - Develop visualization tools - Create data quality checks - Contribute to vocabulary development
For Vocabulary Experts: - Map waveform concepts to OMOP standard concepts - Standardize device and procedure terminology - Extend vocabularies for signal types and features
Follow the Waveform Extension Implementation Guide to:
Scenario: Integrate continuous bedside monitor data (ECG, ABP, SpO2) with ICU EHR data
Implementation: - Link telemetry sessions to ICU visits via timestamps - Register multi-channel waveform files (often EDF or proprietary formats) - Extract vital signs as features (HR, BP, RR, SpO2) - Align with medication administration and interventions
Applications: - Early warning systems for hemodynamic instability - Medication effect analysis - ICU length of stay prediction
Scenario: Standardize 12-lead diagnostic ECG data from cardiology clinics
Implementation: - Link ECGs to outpatient visits or procedures - Register ECG files (typically HL7 aECG, DICOM, or MUSE XML) - Extract automated measurements (QT, QRS, PR intervals) - Map ECG interpretations to OMOP concepts
Applications: - QT prolongation risk assessment - Arrhythmia phenotyping - Medication safety surveillance
Scenario: Enable neurological research with EEG and clinical data
Implementation: - Link EEG studies to neurology encounters - Register multi-channel EEG files (often EDF+) - Extract power spectral features, entropy, or seizure annotations - Align with medication, imaging, and outcome data
Applications: - Seizure prediction models - Sleep disorder research - Post-operative cognitive monitoring
Welcome! We support all skill levels: - Pair with experienced implementers - Start by reviewing existing implementations - Ask questions freely during meetings - Review the OHDSI Community resources - Explore PhysioNet datasets for learning