Identification of myocardial infarction type from electronic hospital data in England and Australia: a comparative data linkage study. Issue 11 (12th November 2017)

• Record Type: Journal Article
• Authors: Nedkoff, Lee; Lopez, Derrick; Goldacre, Michael; Sanfilippo, Frank; Hobbs, Michael; Wright, F Lucy
• Is Part Of: BMJ open. Volume 7:Issue 11(2017)
• Publication Date: 2017-11-12
• Subjects: myocardial infarction -- cardiac epidemiology; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2017-019217
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Objective: To determine the utility of International Classification of Diseases (ICD) codes in investigating trends in ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) using person-linked electronic hospitalisation data in England and Western Australia (WA). Methods: All hospital admissions with myocardial infarction (MI) as the principal diagnosis were identified from 2000 to 2013 from both jurisdictions. Fourth-digit ICD-10 codes were used to delineate all MI types—STEMI, NSTEMI, unspecified and subsequent MI. The annual frequency of each MI type was calculated as a proportion of all MI admissions. For all MI and each MI type, age-standardised rates were calculated and age-adjusted Poisson regression models used to estimate annual percentage changes in rates. Results: In 2000, STEMI accounted for 49% of all MI admissions in England and 59% in WA, decreasing to 35% and 25% respectively by 2013. Less than 10% of admissions were recorded as NSTEMI in England throughout the study period, whereas by 2013, 70% of admissions were NSTEMI in WA. Unspecified MI comprised 60% of all MI admissions in England by 2013, compared with <1% in WA. Trends in age-standardised rates differed for all MI (England, −2.7%/year; WA, +1.7%/year), underpinned by differing age-adjusted trends in NSTEMI (England, −6.1%/year; WA, +10.2%/year). Conclusion: Differences between the proportion and trends for MI types in English and WA data were observed. These were consistent with the coding standards in each country. This has important implications for using electronic hospital data for monitoring MI and identifying MI types for outcome studies.