Development of the multivariate administrative data cystectomy model and its impact on misclassification bias
BMC Medical Research Methodology(2024)
摘要
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. 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. 500 people underwent cystectomy (0.12
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关键词
Cystectomy,Urinary diversion,Predictive model,Misclassification bias,Bootstrap imputation,Administrative data
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