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Assessing asthma severity based on claims data: a systematic review
INTRODUCTION: Asthma is one of the most common chronic diseases in Germany. Substantial economic evaluation of asthma cost requires knowledge of asthma severity, which is in general not part of claims data. Algorithms need to be defined to use this data source. AIMS AND OBJECTIVES: The aim of this s...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5313583/ https://www.ncbi.nlm.nih.gov/pubmed/26931557 http://dx.doi.org/10.1007/s10198-016-0769-2 |
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author | Jacob, Christian Haas, Jennifer S. Bechtel, Benno Kardos, Peter Braun, Sebastian |
author_facet | Jacob, Christian Haas, Jennifer S. Bechtel, Benno Kardos, Peter Braun, Sebastian |
author_sort | Jacob, Christian |
collection | PubMed |
description | INTRODUCTION: Asthma is one of the most common chronic diseases in Germany. Substantial economic evaluation of asthma cost requires knowledge of asthma severity, which is in general not part of claims data. Algorithms need to be defined to use this data source. AIMS AND OBJECTIVES: The aim of this study was to systematically review the international literature to identify algorithms for the stratification of asthma patients according to disease severity based on available information in claims data. METHODS: A systematic literature review was conducted in September 2015 using the DIMDI SmartSearch, a meta search engine including several databases with a national and international scope, e.g. BIOSIS, MEDLINE, and EMBASE. Claims data based studies that categorize asthma patients according to their disease severity were identified. RESULTS: The systematic research yielded 54 publications assessing asthma severity based on claims data. Thirty-nine studies used a standardized algorithm such as HEDIS, Leidy, the GINA based approach or CACQ. Sixteen publications applied a variety of different criteria for the severity categorisation such as asthma diagnoses, asthma-related drug prescriptions, emergency department visits, and hospitalisations. CONCLUSION: There is no best practice method for the categorisation of asthma severity with claims data. Rather, a combination of algorithms seems to be a pragmatic approach. A transfer to the German context is not entirely possible without considering particular conditions associated with German claims data. |
format | Online Article Text |
id | pubmed-5313583 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-53135832017-03-01 Assessing asthma severity based on claims data: a systematic review Jacob, Christian Haas, Jennifer S. Bechtel, Benno Kardos, Peter Braun, Sebastian Eur J Health Econ Original Paper INTRODUCTION: Asthma is one of the most common chronic diseases in Germany. Substantial economic evaluation of asthma cost requires knowledge of asthma severity, which is in general not part of claims data. Algorithms need to be defined to use this data source. AIMS AND OBJECTIVES: The aim of this study was to systematically review the international literature to identify algorithms for the stratification of asthma patients according to disease severity based on available information in claims data. METHODS: A systematic literature review was conducted in September 2015 using the DIMDI SmartSearch, a meta search engine including several databases with a national and international scope, e.g. BIOSIS, MEDLINE, and EMBASE. Claims data based studies that categorize asthma patients according to their disease severity were identified. RESULTS: The systematic research yielded 54 publications assessing asthma severity based on claims data. Thirty-nine studies used a standardized algorithm such as HEDIS, Leidy, the GINA based approach or CACQ. Sixteen publications applied a variety of different criteria for the severity categorisation such as asthma diagnoses, asthma-related drug prescriptions, emergency department visits, and hospitalisations. CONCLUSION: There is no best practice method for the categorisation of asthma severity with claims data. Rather, a combination of algorithms seems to be a pragmatic approach. A transfer to the German context is not entirely possible without considering particular conditions associated with German claims data. Springer Berlin Heidelberg 2016-03-01 2017 /pmc/articles/PMC5313583/ /pubmed/26931557 http://dx.doi.org/10.1007/s10198-016-0769-2 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Paper Jacob, Christian Haas, Jennifer S. Bechtel, Benno Kardos, Peter Braun, Sebastian Assessing asthma severity based on claims data: a systematic review |
title | Assessing asthma severity based on claims data: a systematic review |
title_full | Assessing asthma severity based on claims data: a systematic review |
title_fullStr | Assessing asthma severity based on claims data: a systematic review |
title_full_unstemmed | Assessing asthma severity based on claims data: a systematic review |
title_short | Assessing asthma severity based on claims data: a systematic review |
title_sort | assessing asthma severity based on claims data: a systematic review |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5313583/ https://www.ncbi.nlm.nih.gov/pubmed/26931557 http://dx.doi.org/10.1007/s10198-016-0769-2 |
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