A comprehensive analysis of temporal trends of between-hospital variation in mortality, readmission and length of stay using logistic regression

Despite the benefits of studying multiple patient outcomes together, research on between-hospital variation has often focused single or disease-specific study populations. In this we examined nationwide temporal trends and in in-hospital mortality, 30-day readmissions length-of-stay above All-Patient-Refined Diagnoses-Related-Group (APR-DRG)-specific 90th percentile (pLOS). We modelled 13,660,187 admissions derived from an administrative database occurring between 2008 2018 90 (89%) Belgian acute-care hospitals. applied APR-DRG-specific logistic regression to outcomes, hospital-level associations with hospitals characteristics, evaluate how many which APR-DRGs explained variation. Our proposed analytical model managed achieve novel insights into healthcare quality care, illustrating high potential databases can provide. It was revealed that is likely due systemic hospital factors. This illustrated by fact baseline bottom-performing remained underperforming throughout period vice versa. assessments further confirmed this. When have overall outcome ratios significantly deviate benchmark, seems be driven a considerable number APR-DRGs, comprising diverse set pathologies. urges policy reform wherein longitudinal follow-up benchmarking should become starting point towards targeted improvement interventions.