The use of natural language processing to identify Tdap-related local reactions at five health care systems in the Vaccine Safety Datalink.

ABSTRACT:

Objective

Local reactions are the most common vaccine-related adverse event. There is no specific diagnosis code for local reaction due to vaccination. Previous vaccine safety studies used non-specific diagnosis codes to identify potential local reaction cases and confirmed the cases through manual chart review. In this study, a natural language processing (NLP) algorithm was developed to identify local reaction associated with tetanus-diphtheria-acellular pertussis (Tdap) vaccine in the Vaccine Safety Datalink.

Methods

Presumptive cases of local reactions were identified among members ≥ 11 years of age using ICD-9-CM codes in all care settings in the 1-6 days following a Tdap vaccination between 2012 and 2014. The clinical notes were searched for signs and symptoms consiste

SUBMITTER: Zheng C 

PROVIDER: S-EPMC6645678 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature