Estimating the prevalence of diabetes mellitus and thyroid disorders using medication data in Flanders, Belgium-Reference-Cited by-同舟云学术

Estimating the prevalence of diabetes mellitus and thyroid disorders using medication data in Flanders, Belgium

Published:2017-07-16 Issue:1 Volume:28 Page:193-198
ISSN:1101-1262
Container-title:European Journal of Public Health
language:en
Short-container-title:

Author:

Vaes Bert¹,Ruelens Catherine¹,Saikali Samuel¹,Smets Alexander¹,Henrard Séverine¹²,Renard Francoise³,van den Akker Marjan¹⁴,Van Pottelbergh Gijs¹,Goderis Geert¹,Van der Heyden Johan³

Affiliation:

1. Department of Public Health and Primary Care, University of Leuven (KU Leuven), Leuven, Belgium

2. Institute of Health and Society, Université Catholique de Louvain (UCL), Brussels, Belgium

3. Scientific Institute of Public Health (WIV – ISP), Brussels, Belgium

4. Department of Family Medicine, Maastricht University, Maastricht, The Netherlands

Funder

Belgian National Health

National Institute for Health and Disability Insurance

Publisher

Oxford University Press (OUP)

Subject

Public Health, Environmental and Occupational Health

Link

http://academic.oup.com/eurpub/article-pdf/28/1/193/23532133/ckx106.pdf

Reference35 articles.

1. Can we use the pharmacy data to estimate the prevalence of chronic conditions? a comparison of multiple data sources;Chini;BMC Public Health,2011

2. The Intego database: background, methods and basic results of a Flemish general practice-based continuous morbidity registration project;Truyers;BMC Med Inform Decis Mak,2014

3. Estimating disease prevalence using a population-based administrative healthcare database;Wiréhn;Scand J Public Health,2007

4. Monitoring the prevalence of chronic conditions: which data should we use?;Orueta;BMC Health Serv Res,2012

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An interpretable approach using hybrid graph networks and explainable AI for intelligent diagnosis recommendations in chronic disease care;Biomedical Signal Processing and Control;2024-05

2. Estimating Type 2 Diabetes Prevalence: A Model of Drug Consumption Data;Pharmacy;2024-01-22

3. Comparing self-reported health interview survey and pharmacy billing data in determining the prevalence of diabetes, hypertension, and hypercholesterolemia in Belgium;Archives of Public Health;2023-06-30

4. Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium;BMC Health Services Research;2022-10-18

5. Medication burden in young adults with juvenile idiopathic arthritis: data from a multicentre observational study;RMD Open;2022-10