title: Mortality control charts for comparing performance of surgical units: validation study using hospital mortality data.
abstract: OBJECTIVE
  To design and validate a statistical method for evaluating the performance of surgical units that adjusts for case volume and case mix.
  
  
  METHODS
  Validation study using routinely collected data on in-hospital mortality.
  
  
  METHODS
  Two UK databases, the ASCOT prospective database and the risk scoring collaborative (RISC) database, covering 1042 patients undergoing surgery in 29 hospitals for gastro-oesophageal cancer between 1995 and 2000.
  
  
  METHODS
  A two level hierarchical logistic regression model was used to adjust each unit's operative mortality for case mix. Crude or adjusted operative mortality was plotted on mortality control charts (a graphical representation of surgical performance) as a function of number of operations. Control limits defined as 90%, 95%, and 99% confidence intervals identified units whose performance diverged significantly from the mean.
  
  
  RESULTS
  The mean in-hospital mortality was 12% (range 0% to 50%). The case volume of the units ranged from one to 55 cases a year. When crude figures were plotted on the mortality control chart, four units lay outside the 90% control limit, including two outside the 95% limit. When operative mortality was adjusted for risk, three units lay outside the 90% limit and one outside the 95% limit. The model fitted the data well and had adequate discrimination (area under the receiver operating characteristics curve 0.78).
  
  
  CONCLUSIONS
  The mortality control chart is an accurate, risk adjusted means of identifying units whose surgical performance, in terms of operative mortality, diverges significantly from the population mean. It gives an early warning of divergent performance. It could be adapted to monitor performance across various specialties.
authors.affiliation: Academic Department of Surgery, King's College Hospital, London SE5 9RS. ptekkis@blueyonder.co.uk
authors.forename: Paris P
authors.initials: PP
authors.lastname: Tekkis
authors.forename: Peter
authors.initials: P
authors.lastname: McCulloch
authors.forename: Adrian C
authors.initials: AC
authors.lastname: Steger
authors.forename: Irving S
authors.initials: IS
authors.lastname: Benjamin
authors.forename: Jan D
authors.initials: JD
authors.lastname: Poloniecki
mesh_terms: D017052:Hospital Mortality; D006779:Hospitals, Public / Q000592:standards*; D006801:Humans; D016015:Logistic Models; D018570:Risk Assessment; D012307:Risk Factors; D012720:Severity of Illness Index; D013222:State Medicine / Q000592:standards; D013503:Surgery Department, Hospital / Q000592:standards* / Q000706:statistics & numerical data*; D013514:Surgical Procedures, Operative / Q000401:mortality* / Q000706:statistics & numerical data*; D006113:United Kingdom / Q000453:epidemiology