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Original article
Impact of missing data on standardised mortality ratios for acute myocardial infarction: evidence from the Myocardial Ischaemia National Audit Project (MINAP) 2004–7
  1. C P Gale1,2,
  2. B A Cattle1,
  3. J Moore3,
  4. H Dawe1,
  5. D C Greenwood1,
  6. R M West1,3
  1. 1Centre for Epidemiology and Biostatistics, University of Leeds, Leeds, UK
  2. 2York Teaching Hospital NHS Foundation Trust, York, UK
  3. 3Institute of Health Sciences, University of Leeds, Leeds, UK
  1. Correspondence to Dr CP Gale, Centre for Epidemiology and Biostatistics, University of Leeds, Clarendon Way, Level 8, Worsley Building, Leeds LS2 9JT, UK; c.p.gale{at}leeds.ac.uk

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.

Objectives 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.

Design 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.

Patients 217,157 patients: 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.

  • Epidemiology
  • NSTEMI
  • STEMI

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Footnotes

  • Funding MINAP is funded by the Health Quality Improvement Partnership (HQIP) This study was funded by the British Heart Foundation, CPG is funded by the National Institute for Health Research as a Clinician Scientist Award Senior Lecturer in Cardiovascular Health Sciences and Honorary Consultant Cardiologist.

  • Competing interests None.

  • Ethical approval Ethical approval was not required; MINAP has PIAG approval.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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