Development of the multivariate administrative data cystectomy model and its impact on misclassification bias.

ABSTRACT:

Background

Misclassification bias (MB) is the deviation of measured from true values due to incorrect case assignment. This study compared MB when cystectomy status was determined using administrative database codes vs. predicted cystectomy probability.

Methods

We identified every primary cystectomy-diversion type at a single hospital 2009-2019. We linked to claims data to measure true association of cystectomy with 30 patient and hospitalization factors. Associations were also measured when cystectomy status was assigned using billing codes and by cystectomy probability from multivariate logistic regression model with covariates from administrative data. MB was the difference between measured and true associations.

Results

500 people underwent cystectomy (0.12% of 42

SUBMITTER: Ross J 

PROVIDER: S-EPMC10956281 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature