Impact of missing data on standardised mortality ratios for acute myocardial infarction: evidence from the Myocardial Ischaemia National Audit Project (MINAP) 2004–7. Issue 23 (12th January 2011)

• Record Type: Journal Article
• Authors: Gale, C P; Cattle, B A; Moore, J; Dawe, H; Greenwood, D C; West, R M
• Is Part Of: Heart. Volume 97:Issue 23(2011)
• Page Start: 1926
• Page End: 1931
• Publication Date: 2011-01-12
• Subjects: Epidemiology -- NSTEMI -- STEMI; Heart -- Diseases -- Treatment -- Periodicals; Cardiology -- Periodicals; 616.12
• DOI: 10.1136/hrt.2010.204883
• Languages: English
• ISSNs: 1355-6037

Abstract

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 (R 2 0.72) and standardised mortality (R 2 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.