Description

Two types of systems are used in the medical/health industry to manage individual patient medical and health records: Electronic Medical Record (EMR) and Electronic Health Record (EHR).  


An EMR system manages a digital version of each patient's medical record or chart. They are used by one organization and are provider-specific. 

An EHR system contains a digital version of a patient's charts and stores, manages, and shares this information electronically. Hospitals, clinics, and other healthcare providers use these systems to document and track a patient's care over time. An EHR represents a person's full health record across multiple providers. They can be shared across systems and are patient-focused.


GenRocket can generate synthetic test data for EHR/EMR systems while protecting PII and PHI data. The generated data can be used for testing, validation, and training without risking patient privacy or compliance violations.


How Can GenRocket Fit Into an EHR/EMR Environment?

Here are some examples of how Genrocket can be used:  

  1. Generate HIPAA-Compliant Test Data - GenRocket synthetic patient data mimics real patient records without exposing PII (Personally Identifiable Information) or PHI (Protected Health Information).

  2. Data Volume and Performance Testing - GenRocket can simulate large volumes of patient records, clinical visits, lab results, etc. You can also perform scalability and performance testing on EHR applications, like Epic Systems and Oracle Health (formerly Cerner), to ensure they can handle real-world data loads.

  3. End-to-End System Testing - Generate complete datasets that mimic real-world workflows, such as patient registration or appointment scheduling. You can validate interoperability between systems by generating HL7-compliant data.

  4. Testing Data Integration and ETL Pipelines - Generate synthetic source data for ETL testing to ensure the accuracy of data extracted and loaded into EHR databases, data warehouses, etc.

  5. Training and Demonstration Environments - GenRocket can populate sandbox or training environments with realistic synthetic patient data for training or vendor demonstrations.


What Features Are Available for Generating Test Data? 

GenRocket lets you easily model the required data and define complex relationships between datasets or records. Additional features can be used to generate the desired output and test specific workflows as needed. Here are a few of the features that GenRocket offers for this type of testing: 

  1. Model Complex Data Relationships Across Multiple Records to Simulate Real Patient Workflows- EHR systems manage complex, interconnected data entities (patients, providers, visits, etc.). The following features can help model real patient workflows while maintaining referential integrity: 
    • Parent-Child Relationships - Govern how complex relationships (Domain models) can be easily represented and manipulated with full referential integrity.
    • Organization Variables - Variables that are global to all Projects within an Organization. Any Generator can reference them within an Attribute of a Domain or the Self Service module. 
    • Organization Attributes - Attributes that are global to all Projects within an Organization. Multiple Projects can reference their generated value without setting up the Attribute each time.
    • Master Projects - Maintain referential integrity for a Domain (e.g., a User Domain) ACROSS applications and databases. They should be used when multiple databases or applications share a common Domain or set of Domains. 
    • G-Map Server - Map values in memory to be maintained and used throughout a complex workflow.
    • CI/CD Pipeline Integration - Integrate test data generation into your CI/CD pipeline for continuous and streamlined testing.

  2. EDI (Electronic Data Interchange) Transaction Generation for Healthcare Admin Workflows- EHR systems handle administrative items such as claims and eligibility verification through EDI transactions. 
    • Generate EDI transactions (837, 835, 270, etc.) for testing claims processing, eligibility checks, and payment posting.
    • G-Cases, G-Rules, and G-Queries allow you to generate different volumes and varieties of conditioned EDI test data.

  3. HL7 Messages - The HL7SegmentMergeReceiver generates synthetic HL7 messages to test healthcare interoperability, including data exchange between EHR systems and external providers.

  4. High-Volume, Scalable Test Data- EHR systems process extensive data volumes and require stress/load testing. GenRocket can generate large patient populations, high transaction rates, and more. 
    • Parallel Scenario Execution
    • Controlled Looping and Data Volumes
    • Performance and Load Testing Support
    • G-Partition and Scenario Thread Engine (can be used to speed up data generation)

  5. Conditional and Dynamic Business Rule Logic- GenRocket can generate test data that adheres to defined logic to test different clinical scenarios, such as emergency visits, prior authorizations, etc.
  6. Reusable Scenarios and G-Cases - Different departments require different data scenarios (e.g., clinical, billing, admin). G-Cases can generate different patient data sets for functional testing, integration testing, etc.

  7. Multi-Format Output Support for Integration Testing- EHR systems interface with other external systems such as labs, pharmacies, and Health Information Exchange or HIEs. 
    • Receivers for Formatting - JSON, XML, CSV, Parquet, HL7
    • Custom Receiver Support

  8. Integration with CI/CD and Test Automation Frameworks - GenRocket offers a Command Line Interface (CLI), automation APIs, and CI/CD tool integration for Jenkins, Selenium, and more. These features allow for the automation of test data generation for continuous testing pipelines.

Example Medical and Health Record Use Case Scenarios

  1. Simulate the Patient Lifecycle - Domain Modeling and Referential Integrity.
  2. Test HL7 Interface Engines - HL7 Receivers and Message Generation.
  3. Verify Claims Processing - EDI 837/835 Transaction Generation. 
  4. Load Testing for EHR Databases - High-Volume Parallel Data Generation. 
  5. End-to-End Clinical Workflows - G-Cases + JSON/XML Receivers
  6. End-to-End Functional Testing - Generate test data for a new module roll-out in an EHR system.
  7. Integration Testing - Generate consistent, varied data for testing APIs and workflows. 
  8. Analytics Testing - Generate diverse patient datasets (e.g., Patient Risk Stratification Models).

How to Integrate GenRocket with EHR Workflows

  1. Model Data Entities: Patients, Encounters, Diagnoses, Medications.
  2. Define Test Data Scenarios: Based on clinical workflows. 
  3. Generate Data Outputs: HL7 messages, direct database inserts. 
  4. Load into EHR Test Environment: Validate using existing workflows and ETL pipelines.