Network | Approximate Patient Count | Sites Included |
|---|---|---|
University of Southern California & University of Southern California with NLP* | 1 Million Patients | 1 site |
Research & Research with NLP* | 127.1 Million Patients | 89 sites |
US Collaborative Network & US Collaborative Network with NLP* | 113.5 Million Patients | 64 sites |
Linked & Linked with NLP* | 13.9 Million Patients | 22 sites |
COVID-19 Research Network | 124.4 Million Patients | 92 sites |
Global Collaborative Network & Global Collaborative Network with NLP* | 147.9 Million Patients | 123 sites |
APAC Collaborative Network | 4.8 Million Patients | 14 sites |
EMEA Collaborative Network | 18.9 Million Patients | 26 sites |
LATAM Collaborative Network | 30.3 Million Patients | 29 sites |
What is Natural Language Processing (NLP)?*
Natural Language Processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with extracting information from human language (natural language in unstructured text) and converting it to structured data. TriNetX has access to ~8.4 Million patients and 345 million searchable unstructured documents to extract standardized information using Natural Language Processing (NLP), and that can also be used on a project-by-project basis. Data elements derived from NLP are tagged as "NLP-derived" with the recorded date to ensure provenance. TriNetX currently extracts selected types of data elements from unstructured data, primarily medications, diagnoses, and other terms that are readily identifiable.
Network Descriptions
Linked Network
TriNetX Linked is an offering that lets researchers analyze more complete and more longitudinal patient data by integrating your electronic health records with data from medical claims, pharmacy claims, and mortality databases.
Data sourced from your EHR form the foundation of this combined data asset, providing a rich clinical picture of your patients from encounters with your providers. Medical and pharmacy claims, on the other hand, while providing limited clinical detail, can provide insight on a patient’s journey before and after these encounters, regardless of provider. Pre-existing co-morbidities, long-term outcomes, and retail pharmacy fills not discoverable in your EHR are part of the patient record in TriNetX Linked. Finally, if a deceased patient’s death is not reflected in your EHR, the mortality databases that contribute to TriNetX Linked may supply the date of death. Click here for more information (TriNetX login required).
COVID-19 Research Network
Launched on April 9, 2020, The COVID-19 Research Network empowers healthcare researchers to analyze cohorts of patients infected or likely infected with the Novel Coronavirus (SARS-CoV-2).