TriNetX is a Research Cohort Exploration and Data Analytics Tool. The TriNetX platform helps investigators at healthcare organizations and life sciences companies with:

Protocol Design and Feasibility

  • Determine if a sufficient population matches a protocol
  • Investigate attributes and comorbidities of a cohort
  • Analyze inclusion/exclusion criteria and the impact of changes

Ability to match site investigators to industry sponsored trials

  • Sponsors are able to locate study sites based upon the availability of eligible patients matching a protocol
  • Predict the arrival rate of newly eligible patients
  • Engage the right contact within the clinical trials office at study sites

Generation of Real-World Evidence

  • Explore and compare cohorts
  • Compare outcomes of interest
  • Characterize drug efficacy and burden of illness

Collaboration with Peers

  • Participate in multi-site research across organizations
  • Pursue grant-based research funding
  • Strengthen relationships between healthcare organizations and sponsors

The main source of TriNetX data comes from healthcare organizations (HCOs) around the globe. Ranging from specialty clinics to large academic medical centers, HCOs start with providing data typically found in a structured format (e.g. Diagnoses, Procedures, Medications, Labs, and Vitals) from their electronic health records system (EHR). From there, HCOs can opt into sharing additional data not typically found in their EHR, such as cancer registry, genomics data, and data found in notes (extracted via natural language processing).

Availability of data can vary by institution or region. For example, nearly all of USA HCOs provide four or five of the main data types (Diagnoses, Procedures, Medications, Labs, and Vitals), but Procedures and Medications might not be as readily available to ingest from ex-USA HCOs.

See this link for more details (requires a TriNetX login).

How does TriNetX map the data?

As part of onboarding an HCO, their data is mapped to a set of standard terminologies. Demographics data (e.g., race and ethnicity) are mapped to HL7 administrative standards. Diagnoses are represented by ICD-9-CM and ICD-10-CM. Procedures are represented by ICD-9-CM, ICD-10-PCS and CPT. Medications are mapped to RxNorm ingredients. Laboratory test results and vital signs are mapped to LOINC. Molecular genomics data conforms to HGNC for gene naming and HGVS for variant descriptions.

The TriNetX Master Terminology also includes lab roll-ups and derived facts. For example, to ease finding and using common labs, LOINC codes are rolled up to clinically significant level for most frequent labs. One case you’ll see this is the lab TNX:LAB:9029 Sodium [Moles/volume] in Serum, Plasma or Blood corresponds to 2947-0 Sodium [Moles/volume] in Blood and 2951-2 Sodium [Moles/volume] in Serum or Plasma.

Examples of derived and calculated facts include:

  • The Oncology Treatments hierarchy identifies patients who have received radiation, chemotherapy, targeted therapy, hormone therapy, and stem cell transplants.
  • Chemotherapy Lines of Treatment identifies patients who received anywhere from 1 to 5 lines of chemotherapy.
  • Glomerular Filtration Rate (GFR) is based on serum creatinine and other information according to MDRD, CKD-EPI, and Schwartz formulas.

At Penn, the TriNetX data is mapped to the OMOP common data model. The data in TriNetX are medication, diagnosis, labs, demographics and vitals. The Penn Medicine TriNetX network is Penn data only and can only be accessed by Penn researchers. It is a limited data set as the dates are not shifted. All other networks include Penn + other health care centers data and are considered deidentified via expert determination.

TriNetX access is provided on an as-needed basis and is currently only available to Penn Medicine (UPHS or PSOM) employees (faculty or staff) with a PMACS AD account.  Individuals who would like to access TriNetX must complete the requisite training, which includes the following:

  • Complete human research/biomedical researcher training through CITI and HIPAA training through Workday
  • Complete TriNetX  “Read and Acknowledge” training through Workday


TriNetX accounts may be requested through the IS Self Service Desk, with a ticket to the Research Analytics team. Documentation of completed TriNetX “Read and Acknowledge” training must be attached to this request. After the ticket is submitted, it is assigned to the Research Analytics team for compliance review. Once review is completed and approved, a new TriNetX account is created, linked to the user’s PMACS AD account, and login information is sent to the requestor.


  In order to access TriNetX the only required trainings are:

  • Complete human research/biomedical researcher training through CITI and HIPAA training through Workday
  • Complete TriNetX  “Read and Acknowledge” training through Workday


Additionally Training though TriNetX are highly recommended.

  • TriNetX 101: Network(s) Overview, Query Building and Patient Counts
  • TriNetX 102: Basic Analytics for Clinical Trial Optimization Insights
  • TriNetX 242: Best Practices in Querying COVID-19
  • TriNetX 401 – Part 1: Advanced Analytics – Analyze Outcomes, Compare Outcomes, and Compare Cohorts
  • TriNetX 401 – Part 2: Advanced Analytics – Treatment Pathways and Incidence and Prevalence


You can also watch on-demand training in the TriNetX Platform Help Center.



For more information about TriNetX contact the Office of Clinical Research.