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Identification of myocardial infarction type from electronic hospital data in England and Australia: a comparative data linkage study

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 Wes...

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Autores principales: Nedkoff, Lee, Lopez, Derrick, Goldacre, Michael, Sanfilippo, Frank, Hobbs, Michael, Wright, F Lucy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5695341/
https://www.ncbi.nlm.nih.gov/pubmed/29133337
http://dx.doi.org/10.1136/bmjopen-2017-019217
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author Nedkoff, Lee
Lopez, Derrick
Goldacre, Michael
Sanfilippo, Frank
Hobbs, Michael
Wright, F Lucy
author_facet Nedkoff, Lee
Lopez, Derrick
Goldacre, Michael
Sanfilippo, Frank
Hobbs, Michael
Wright, F Lucy
author_sort Nedkoff, Lee
collection PubMed
description 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.
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spelling pubmed-56953412017-11-24 Identification of myocardial infarction type from electronic hospital data in England and Australia: a comparative data linkage study Nedkoff, Lee Lopez, Derrick Goldacre, Michael Sanfilippo, Frank Hobbs, Michael Wright, F Lucy BMJ Open Epidemiology 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. BMJ Publishing Group 2017-11-12 /pmc/articles/PMC5695341/ /pubmed/29133337 http://dx.doi.org/10.1136/bmjopen-2017-019217 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
spellingShingle Epidemiology
Nedkoff, Lee
Lopez, Derrick
Goldacre, Michael
Sanfilippo, Frank
Hobbs, Michael
Wright, F Lucy
Identification of myocardial infarction type from electronic hospital data in England and Australia: a comparative data linkage study
title Identification of myocardial infarction type from electronic hospital data in England and Australia: a comparative data linkage study
title_full Identification of myocardial infarction type from electronic hospital data in England and Australia: a comparative data linkage study
title_fullStr Identification of myocardial infarction type from electronic hospital data in England and Australia: a comparative data linkage study
title_full_unstemmed Identification of myocardial infarction type from electronic hospital data in England and Australia: a comparative data linkage study
title_short Identification of myocardial infarction type from electronic hospital data in England and Australia: a comparative data linkage study
title_sort identification of myocardial infarction type from electronic hospital data in england and australia: a comparative data linkage study
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5695341/
https://www.ncbi.nlm.nih.gov/pubmed/29133337
http://dx.doi.org/10.1136/bmjopen-2017-019217
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