PD41-03 VALIDATED HOSPITAL QUALITY METRICS FOR RADICAL CYSTECTOMY: DISEASE-SPECIFIC AND CORRELATED TO LONG-TERM OUTCOMES

Abstract

You have accessJournal of UrologyBladder Cancer: Invasive V1 Apr 2018PD41-03 VALIDATED HOSPITAL QUALITY METRICS FOR RADICAL CYSTECTOMY: DISEASE-SPECIFIC AND CORRELATED TO LONG-TERM OUTCOMES Abhinav Khanna, Olli Saarela, Keith Lawson, Andrew Stephenson, Georges-Pascal Haber, Byron Lee, Antonio Finelli, and Robert Abouassaly Abhinav KhannaAbhinav Khanna More articles by this author , Olli SaarelaOlli Saarela More articles by this author , Keith LawsonKeith Lawson More articles by this author , Andrew StephensonAndrew Stephenson More articles by this author , Georges-Pascal HaberGeorges-Pascal Haber More articles by this author , Byron LeeByron Lee More articles by this author , Antonio FinelliAntonio Finelli More articles by this author , and Robert AbouassalyRobert Abouassaly More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.1942AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES The Centers for Medicare and Medicaid (CMS), private insurers, and many independent rating agencies are all measuring and publicly reporting hospital quality. However, commonly used quality metrics are not disease-specific and are rarely correlated with meaningful long term outcomes. We aim to develop and validate hospital quality metrics for radical cystectomy that are both disease-specific and correlated with meaningful outcomes. METHODS The National Cancer Database was utilized to identify hospitals performing radical cystectomy for bladder cancer from 2004-2014. A list of candidate quality indicators was developed based on literature review, and included performance of lymphadenectomy, receipt of neoadjuvant chemotherapy, receipt of continent urinary diversion, duration of time from diagnosis to cystectomy, inpatient length of stay and 30-day hospital readmission. Random effects models were used to identify quality indicators (QI's) with statistically significant between-hospital variance. Case-mix adjustment was performed by comparing observed to expected performance using the indirect standardization method. Outlier hospitals were defined as those that performed better or worse than expected based on z-test statistics. Outlier status was correlated to overall mortality using logistic and Cox regression analyses, respectively. RESULTS From 2004-2014, 48,341 patients underwent radical cystectomy at 1200 hospitals. Random effects models demonstrated significant between-hospital variance for all QI's even after adjusting for sociodemographic and clinical patient characteristics. Case-mix adjusted analyses revealed 1.7-25.4% of hospitals were categorized as outliers across the various QI's. High-performing outlier status was associated with lower overall mortality for performance of lymphadenectomy (HR 0.89, 95% confidence interval 0.83-0.95), receipt of neoadjuvant chemotherapy (HR 0.78, 0.66-0.93), receipt of continent urinary diversion (HR 0.80, 0.73-0.89), time from diagnosis to cystectomy (HR 0.90, 0.83-0.98), and 30-day hospital readmission (HR 0.84, 0.74-0.95). CONCLUSIONS Among patients undergoing radical cystectomy, there was significant variation in hospital performance across all quality indicators. High-performing outlier hospitals were associated with lower overall mortality. Our validation of these quality metrics provides support for their potential use by both policymakers and payers in efforts to measure hospital quality for high-cost surgical procedures. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e810 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Abhinav Khanna More articles by this author Olli Saarela More articles by this author Keith Lawson More articles by this author Andrew Stephenson More articles by this author Georges-Pascal Haber More articles by this author Byron Lee More articles by this author Antonio Finelli More articles by this author Robert Abouassaly More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...