ArticleBMC public health2007
How many people have had a myocardial infarction? Prevalence estimated using historical hospital data.
Article in BMC public health, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- The impact of the COVID-19 pandemic on longitudinal trends of surgical mortality and inpatient quality of care in Ontario, Canada.Journal of advanced nursing · 2025Article
- Automatic electronic reporting improved the completeness of AMI and stroke incident surveillance in Tianjin, China: a modeling study.Population health metrics · 2023Article
- The Impact of COVID-19 National Lockdown on Myocardial Infarction (MI) Hospitalizations in Northern Jordan.Vascular health and risk management · 2023Article
- Article
- Racial and ethnic differences in smoking changes after chronic disease diagnosis among middle-aged and older adults in the United States.BMC geriatrics · 2017Article
- Assessing the external validity of model-based estimates of the incidence of heart attack in England: a modelling study.BMC public health · 2016Article
- Computing disease incidence, prevalence and comorbidity from electronic medical records.Journal of biomedical informatics · 2016Article
- Surveillance of ischemic heart disease should include physician billing claims: population-based evidence from administrative health data across seven Canadian provinces.BMC cardiovascular disorders · 2013Article
- Article
- Health behaviour changes after diagnosis of chronic illness among Canadians aged 50 or older.Health reports · 2012Article
- Health behavior change following chronic illness in middle and later life.The journals of gerontology. Series B, Psychological sciences and social sciences · 2012Article
- The aging Canadian population and hospitalizations for acute myocardial infarction: projection to 2020.BMC cardiovascular disorders · 2012Article
- Health care utilization in patients with gout.Seminars in arthritis and rheumatism · 2011Article
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4 authors.
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Abstract
backgroundHealth administrative data are increasingly used to examine disease occurrence. However, health administrative data are typically available for a limited number of years - posing challenges for estimating disease prevalence and incidence. The objective of this study is to estimate the prevalence of people previously hospitalized with an acute myocardial infarction (AMI) using 17 years of hospital data and to create a registry of people with myocardial infarction.
methodsMyocardial infarction prevalence in Ontario 2004 was estimated using four methods: 1) observed hospital admissions from 1988 to 2004; 2) observed (1988 to 2004) and extrapolated unobserved events (prior to 1988) using a "back tracing" method using Poisson models; 3) DisMod incidence-prevalence-mortality model; 4) self-reported heart disease from the population-based Canadian Community Health Survey (CCHS) in 2000/2001. Individual respondents of the CCHS were individually linked to hospital discharge records to examine the agreement between self-report and hospital AMI admission.
results170,061 Ontario residents who were alive on March 31, 2004, and over age 20 years survived an AMI hospital admission between 1988 to 2004 (cumulative incidence 1.8%). This estimate increased to 2.03% (95% CI 2.01 to 2.05) after adding extrapolated cases that likely occurred before 1988. The estimated prevalence appeared stable with 5 to 10 years of historic hospital data. All 17 years of data were needed to create a reasonably complete registry (90% of estimated prevalent cases). The estimated prevalence using both DisMod and self-reported "heart attack" was higher (2.5% and 2.7% respectively). There was poor agreement between self-reported "heart attack" and the likelihood of having an observed AMI admission (sensitivity = 63.5%, positive predictive value = 54.3%).
conclusionEstimating myocardial infarction prevalence using a limited number of years of hospital data is feasible, and validity increases when unobserved events are added to observed events. The "back tracing" method is simple, reliable, and produces a myocardial infarction registry with high estimated "completeness" for jurisdictions with linked hospital data.
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