Automated identification of diagnostic labelling errors in medicine.

ABSTRACT:

Objectives

Identification of diagnostic error is complex and mostly relies on expert ratings, a severely limited procedure. We developed a system that allows to automatically identify diagnostic labelling error from diagnoses coded according to the international classification of diseases (ICD), often available as routine health care data.

Methods

The system developed (index test) was validated against rater based classifications taken from three previous studies of diagnostic labeling error (reference standard). The system compares pairs of diagnoses through calculation of their distance within the ICD taxonomy. Calculation is based on four different algorithms. To assess the concordance between index test and reference standard, we calculated the area under the receiver op

SUBMITTER: Hautz WE 

PROVIDER: S-EPMC9125795 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature