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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
US Collaborative Network
Includes data from all participating healthcare organizations within the United States.
Global Collaborative Network
Includes data from all participating healthcare organizations around the world.
EMEA Collaborative Network
Includes data from participating healthcare organizations in Europe, Middle East, and Africa (EMEA).
LATAM Collaborative Network
Includes data from participating healthcare organizations in Latin America.
APAC Collaborative Network
Includes data from participating healthcare organizations in the Asia-Pacific region.
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).
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).