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Estimating the prevalence and incidence of type 2 diabetes using population level pharmacy claims data: a cross-sectional study
OBJECTIVE: To estimate the prevalence and incidence of type 2 diabetes using a national pharmacy claims database. RESEARCH DESIGN AND METHODS: We used data from the Health Service Executive-Primary Care Reimbursement Service database in Ireland for this cross-sectional study. Prevalent cases of type...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5253438/ https://www.ncbi.nlm.nih.gov/pubmed/28123753 http://dx.doi.org/10.1136/bmjdrc-2016-000288 |
Sumario: | OBJECTIVE: To estimate the prevalence and incidence of type 2 diabetes using a national pharmacy claims database. RESEARCH DESIGN AND METHODS: We used data from the Health Service Executive-Primary Care Reimbursement Service database in Ireland for this cross-sectional study. Prevalent cases of type 2 diabetes were individuals using an oral hypoglycemic agent, irrespective of insulin use, in 2012. Incident cases were individuals using an oral hypoglycemic agent in 2012 who had not used one in the past. Population level estimates were calculated and stratified by age and sex. RESULTS: In 2012, there were 114 957 prevalent cases of type 2 diabetes giving a population prevalence of 2.51% (95% CI 2.49% to 2.52%). Among adults (≥15yrs), this was 3.16% (95% CI 3.15% to 3.18%). The highest prevalence was in those aged 70+ years (12.1%). 21 574 people developed type 2 diabetes in 2012 giving an overall incidence of 0.48% (95% CI 0.48% to 0.49%). In adults, this was 0.60% (95% CI 0.60% to 0.61%). Incidence rose with age to a maximum of 2.08% (95% CI 2.02% to 2.15%) in people aged 65–69 years. Men had a higher prevalence (2.96% vs 2.04%) and incidence (0.54% vs 0.41%) of type 2 diabetes than women. CONCLUSIONS: Pharmacy claims data allow estimates of objectively defined type 2 diabetes at the population level using up-to-date data. These estimates can be generated quickly to inform health service planning or to evaluate the impact of population level interventions. |
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