Hospital discharge database optimization in guillain‐barré syndrome surveillance

Abstract

Precise causes and risk factors for Guillain-Barré syndrome (GBS) remain incompletely understood, and monitoring its incidence remains important in public health. Active surveillance is not sustainable, but hospital discharge databases (HDDs) may be suitable for passive surveillance. We optimized Tennessee's HDD of all ICD-9 codes of 357.0, from 2000 to 2010. Discharges for persons with a GBS diagnosis in a previous hospitalization in the database were excluded. HDD results were compared with the CDC's active surveillance program during the H1N1 vaccination program of 2009-2010. Of 2,659 records of Tennessee residents initially identified, 1077 (40%) had prior diagnoses of GBS. Adjusted annual rates ranged from 1.24 to 1.57 per 100,000 population. The sensitivity of the optimized HDD was 0.81 with a positive predictive value of 0.45. Optimization of a HDD through exclusion of nonacute cases results in an acceptable and practical database for passive surveillance of GBS.