Validating pertussis data measures using electronic medical record data in Ontario, Canada 1986-2016.

ABSTRACT:

Background

Pertussis is a reportable disease in many countries, but ascertainment bias has limited data accuracy. This study aims to validate pertussis data measures using a reference standard that incorporates different suspected case severities, allowing for the impact of case severity on accuracy and detection to be explored.

Methods

We evaluated 25 pertussis detection algorithms in a primary care electronic medical record database between January 1, 1986 and December 30, 2016. We estimated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). We used sensitivity analyses to explore areas of uncertainty and evaluated reasons for lack of detection.

Results

The algorithm including all data measures achieved the highest sensit

SUBMITTER: McBurney SH 

PROVIDER: S-EPMC10755117 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature