title: Re-resection rates after breast-conserving surgery as a performance indicator: introduction of a case-mix model to allow comparison between Dutch hospitals.
abstract: OBJECTIVE
  Re-resection rate after breast-conserving surgery (BCS) has been introduced as an indicator of quality of surgical treatment in international literature. The present study aims to develop a case-mix model for re-resection rates and to evaluate its performance in comparing results between hospitals.
  
  
  METHODS
  Electronic records of eligible patients diagnosed with in-situ and invasive breast cancer in 2006 and 2007 were derived from 16 hospitals in the Rotterdam Cancer Registry (RCR) (n = 961). A model was built in which prognostic factors for re-resections after BCS were identified and expected re-resection rate could be assessed for hospitals based on their case mix. To illustrate the opportunities of monitoring re-resections over time, after risk adjustment for patient profile, a VLAD chart was drawn for patients in one hospital.
  
  
  RESULTS
  In general three out of every ten women had re-surgery; in about 50% this meant an additive mastectomy. Independent prognostic factors of re-resection after multivariate analysis were histological type, sublocalisation, tumour size, lymph node involvement and multifocal disease. After correction for case mix, one hospital was performing significantly less re-resections compared to the reference hospital. On the other hand, two were performing significantly more re-resections than was expected based on their patient mix.
  
  
  CONCLUSIONS
  Our population-based study confirms earlier reports that re-resection is frequently required after an initial breast-conserving operation. Case-mix models such as the one we constructed can be used to correct for variation between hospitals performances. VLAD charts are valuable tools to monitor quality of care within individual hospitals.
authors.affiliation: Ikazia Hospital, Rotterdam, The Netherlands. koentalsma@hotmail.com
authors.forename: A K
authors.initials: AK
authors.lastname: Talsma
authors.forename: A M J
authors.initials: AM
authors.lastname: Reedijk
authors.forename: R A M
authors.initials: RA
authors.lastname: Damhuis
authors.forename: P J
authors.initials: PJ
authors.lastname: Westenend
authors.forename: W J
authors.initials: WJ
authors.lastname: Vles
mesh_terms: D000328:Adult; D000368:Aged; D000704:Analysis of Variance; D001943:Breast Neoplasms / Q000473:pathology* / Q000601:surgery*; D018270:Carcinoma, Ductal, Breast / Q000473:pathology / Q000601:surgery; D002285:Carcinoma, Intraductal, Noninfiltrating / Q000473:pathology / Q000601:surgery; D018275:Carcinoma, Lobular / Q000469:parasitology / Q000601:surgery; D003953:Diagnosis-Related Groups; D005260:Female; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D015411:Mastectomy, Modified Radical / Q000706:statistics & numerical data*; D015412:Mastectomy, Segmental / Q000706:statistics & numerical data*; D008875:Middle Aged; D009367:Neoplasm Staging; D009426:Netherlands / Q000453:epidemiology; D016017:Odds Ratio; D019984:Quality Indicators, Health Care; D012372:ROC Curve; D012042:Registries; D012086:Reoperation / Q000706:statistics & numerical data