title: Impact of missing data on standardised mortality ratios for acute myocardial infarction: evidence from the Myocardial Ischaemia National Audit Project (MINAP) 2004-7.
abstract: BACKGROUND
  Standardised mortality ratios (SMR) are often used to depict cardiovascular care. Data missingness, data quality, temporal variation and case-mix can, however, complicate the assessment of clinical performance.
  
  
  OBJECTIVE
  To study Primary Care Trust (PCT) 30-day SMRs for STEMI and NSTEMI whilst considering the impact of missing data for age, sex and IMD score.
  
  
  METHODS
  Observational study using data from the Myocardial Ischaemia National Audit Project (MINAP) database to generate PCT SMR maps and funnel plots for England, 2004-2007.
  
  
  METHODS
  217,157
  
  
  METHODS
  40.4% STEMI and 59.6% NSTEMI.
  
  
  RESULTS
  95% CI 30-day unadjusted mortality: STEMI 5.8% to 6.2%; NSTEMI 6.6% to 6.9%; relative risk, 95% CI 1.14, 1.10 to 1.19. Median (IQR) data missingess by PCT for composite of age, sex and IMD score was 1.4% (0.7% to 2.2%). For STEMI and NSTEMI statistically significant predictors of mortality were mean age (STEMI: P<0.001; NSTEMI: P<0.001), proportion of females (STEMI: P<0.001; NSTEMI: P<0.001) and proportion of missing ages (STEMI: P=0.02; NSTEMI: P<0.001). Proportion of missing sex also predicted 30-day mortality for NSTEMI (P=0.01). Maps of SMRs demonstrated substantial mortality variation, but no evidence of North / South divide. There were significant correlations between STEMI and NSTEMI observed (R² 0.72) and standardised mortality (R² 0.49) rates. PCT data aggregation gave an acceptable model fit in terms of deviance explained. For STEMI there were 33 (21.7%) regions below the 99.8% lower limit of the associated performance funnel plot, and 28 (18.4%) for NSTEMI; the inclusion of missing data did not affect the distribution of SMRs.
  
  
  CONCLUSIONS
  The proportion of missing data was associated with 30-day mortality for STEMI and NSTEMI, however it did not influence the distribution of PCTs within the funnel plots. There was considerable variation in mortality not attributable to key patient-specific factors, supporting the notion of regional-dependent variation in STEMI and NSTEMI care.
authors.affiliation: Centre for Epidemiology and Biostatistics, University of Leeds, Leeds LS2 9JT, UK. c.p.gale@leeds.ac.uk
authors.forename: C P
authors.initials: CP
authors.lastname: Gale
authors.forename: B A
authors.initials: BA
authors.lastname: Cattle
authors.forename: J
authors.initials: J
authors.lastname: Moore
authors.forename: H
authors.initials: H
authors.lastname: Dawe
authors.forename: D C
authors.initials: DC
authors.lastname: Greenwood
authors.forename: R M
authors.initials: RM
authors.lastname: West
mesh_terms: D000368:Aged; D003625:Data Collection / Q000706:statistics & numerical data*; D004739:England / Q000453:epidemiology; D005260:Female; D006801:Humans; D008297:Male; D008485:Medical Audit; D009203:Myocardial Infarction / Q000401:mortality*; D011446:Prospective Studies; D015996:Survival Rate; D014852:Wales / Q000453:epidemiology