Linking Individual Data From the Spinal Cord Injury Model Systems Center and Local Trauma Registry: Development and Validation of Probabilistic Matching Algorithm | Zendy

Yuying Chen | Zendy; Huacong Wen | Zendy; Russell Griffin | Zendy; Mary Joan Roach | Zendy; Michael L. Kelly | Zendy

Open Access

Linking Individual Data From the Spinal Cord Injury Model Systems Center and Local Trauma Registry: Development and Validation of Probabilistic Matching Algorithm

Author(s) -

Yuying Chen,

Huacong Wen,

Russell Griffin,

Mary Joan Roach,

Michael L. Kelly

Publication year - 2020

Publication title -

topics in spinal cord injury rehabilitation

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.597

H-Index - 35

eISSN - 1945-5763

pISSN - 1082-0744

DOI - 10.46292/sci20-00015

Subject(s) - medicine , medical record , trauma center , spinal cord injury , probabilistic logic , matching (statistics) , record linkage , algorithm , data mining , medical emergency , retrospective cohort study , computer science , artificial intelligence , spinal cord , surgery , population , pathology , psychiatry , environmental health

Linking records from the National Spinal Cord Injury Model Systems (SCIMS) database to the National Trauma Data Bank (NTDB) provides a unique opportunity to study early variables in predicting long-term outcomes after traumatic spinal cord injury (SCI). The public use data sets of SCIMS and NTDB are stripped of protected health information, including dates and zip code.

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