Real-world cohorts from 100M+ patients.

Compare treatments, exposures, and outcomes across a global network of de-identified electronic health records, in real time, with propensity matching, and without collecting any new data yourself.

What it is

A live window into routine clinical care.

TriNetX is a global federated network of de-identified electronic health record (EHR) data drawn from more than 120 healthcare organizations, covering well over 100 million patients. It can be queried in real time to count patients, build cohorts, and compare outcomes, the data reflects care as it actually happened, not a controlled trial.

What it is built for

Scale, 100M+ patients across many countries, queried live.

Design, retrospective cohort and propensity-matched comparative effectiveness/safety, with time-to-event analysis.

Limits, coded EHR data; outcomes outside the network may be missed.

How it works

The method, in plain terms.

01

Define cohorts

Diagnosis, drug, procedure codes

02

Set time-zero

First prescription or diagnosis

03

Propensity matching

1:1 balance on covariates

04

Define outcomes

Mortality, readmission, new diagnoses

05

Time-to-event

Kaplan-Meier, hazard ratios

06

Sensitivity checks

Alternative matching, subgroups

How you benefit

Why authors start here.

The project, step by step

How a TriNetX study runs with Cohira.

Start a TriNetX study →

1

Scope the question

We turn your idea into a clear exposure-vs-comparator question TriNetX can answer.

2

Protocol & codes

We pre-specify cohorts, index event, outcomes, covariates, and the matching plan.

3

Build & match cohorts

We construct the groups and run propensity-score matching, checking balance.

4

Analysis

We run time-to-event and risk analyses, with the sensitivity checks reviewers expect.

5

Manuscript

We draft a clear paper with you, tables, survival curves, and honest limitations.

6

Submit & revise

We target the right journal, submit, and answer reviewers with you to a decision.

Published examples

What TriNetX studies look like in print.

Independent, peer-reviewed examples of what this route can produce.

Lancet PsychiatryComparative cohort

Bidirectional associations between COVID-19 and psychiatric disorder: retrospective cohort studies of 62,354 cases

Taquet M, et al. · 2021

TriNetX cohorts compared against six matched control health events, the design most TriNetX papers in top journals use.

View in journal →
Lancet PsychiatryIllustrative example

6-month neurological and psychiatric outcomes in 236,379 survivors of COVID-19

Taquet M, et al. · 2021

In 236,379 COVID-19 survivors, a third received a neurological or psychiatric diagnosis within six months, exceeding matched controls.

View in journal →
JAMA OphthalmologyIllustrative example

Panretinal photocoagulation vs anti-VEGF for proliferative diabetic retinopathy

Alsoudi AF, et al. · 2024

Propensity-matched cohorts showed laser-first treatment raised later vitrectomy risk versus anti-VEGF-first.

View in journal →
Lancet OncologyIllustrative example

Multi-organ immune-related adverse events from immune checkpoint inhibitors

Wan G, et al. · 2024

A matched cohort showing immune-related adverse-event clusters predict differing survival after checkpoint-inhibitor immunotherapy.

View in journal →

These are independent published studies, shown to illustrate what TriNetX makes possible, they are not Cohira's work. We help you design and publish studies of comparable rigor.

Pricing

One fee, from idea to publication.

Database study, idea to publication
Protocol, analysis with reproducible code, manuscript, journal shortlist, submission, and reviewer responses.
$1,800per study

Per project, never per author. Journal fees are billed at cost. TriNetX access, yours or ours, and its cost are confirmed in the free feasibility note before you commit. Your week-by-week timeline is written into the free feasibility note before you pay. Booking more than one study? 10% off the second, 15% off from the third. Acceptance Guarantee & group pricing →

More study types

NIS / real-world dataNRD readmissionsGlobal Burden of DiseaseSEER cancer registryUK BiobankAI & ML prediction modelsMeta-analysisNetwork meta-analysesDiagnostic accuracy meta-analysesNarrative reviewsCross-sectional studiesYour clinical dataSingle stages

Start a conversation

Have a real-world question to test?

Tell us the treatments or outcomes you want to compare. We will tell you honestly whether TriNetX can support a strong paper, and how we would build it.

Get a free feasibility note See all study types →