Assessing two methods for estimating excess mortality of chronic diseases from aggregated data

OBJECTIVE: To assess the numerical properties of two recently published estimation techniques for excess mortality based on aggregated data about diabetes in Germany. RESULTS: Application of the new methods to the claims data yields implausible findings for the excess mortality of type 2 diabetes in...

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Autores principales: Brinks, Ralph, Tönnies, Thaddäus, Hoyer, Annika
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7161167/
https://www.ncbi.nlm.nih.gov/pubmed/32299486
http://dx.doi.org/10.1186/s13104-020-05046-w
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author Brinks, Ralph
Tönnies, Thaddäus
Hoyer, Annika
author_facet Brinks, Ralph
Tönnies, Thaddäus
Hoyer, Annika
author_sort Brinks, Ralph
collection PubMed
description OBJECTIVE: To assess the numerical properties of two recently published estimation techniques for excess mortality based on aggregated data about diabetes in Germany. RESULTS: Application of the new methods to the claims data yields implausible findings for the excess mortality of type 2 diabetes in ages below 50 years of age.
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spelling pubmed-71611672020-04-22 Assessing two methods for estimating excess mortality of chronic diseases from aggregated data Brinks, Ralph Tönnies, Thaddäus Hoyer, Annika BMC Res Notes Research Note OBJECTIVE: To assess the numerical properties of two recently published estimation techniques for excess mortality based on aggregated data about diabetes in Germany. RESULTS: Application of the new methods to the claims data yields implausible findings for the excess mortality of type 2 diabetes in ages below 50 years of age. BioMed Central 2020-04-10 /pmc/articles/PMC7161167/ /pubmed/32299486 http://dx.doi.org/10.1186/s13104-020-05046-w Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Note
Brinks, Ralph
Tönnies, Thaddäus
Hoyer, Annika
Assessing two methods for estimating excess mortality of chronic diseases from aggregated data
title Assessing two methods for estimating excess mortality of chronic diseases from aggregated data
title_full Assessing two methods for estimating excess mortality of chronic diseases from aggregated data
title_fullStr Assessing two methods for estimating excess mortality of chronic diseases from aggregated data
title_full_unstemmed Assessing two methods for estimating excess mortality of chronic diseases from aggregated data
title_short Assessing two methods for estimating excess mortality of chronic diseases from aggregated data
title_sort assessing two methods for estimating excess mortality of chronic diseases from aggregated data
topic Research Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7161167/
https://www.ncbi.nlm.nih.gov/pubmed/32299486
http://dx.doi.org/10.1186/s13104-020-05046-w
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