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Data linkage of German statutory health insurance claims data and care needs assessments preceding a population-based cohort study on nursing home admission
OBJECTIVES: We perform and evaluate record linkage of German Care Needs Assessment (CNA) data to Statutory Health Insurance (SHI) claims data. The resulting dataset should enable the identification of factors in healthcare predicting the time between the onset of long-term care dependency and the ad...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9247689/ https://www.ncbi.nlm.nih.gov/pubmed/35772817 http://dx.doi.org/10.1136/bmjopen-2022-063475 |
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author | Domhoff, Dominik Seibert, Kathrin Stiefler, Susanne Wolf-Ostermann, Karin Peschke, Dirk |
author_facet | Domhoff, Dominik Seibert, Kathrin Stiefler, Susanne Wolf-Ostermann, Karin Peschke, Dirk |
author_sort | Domhoff, Dominik |
collection | PubMed |
description | OBJECTIVES: We perform and evaluate record linkage of German Care Needs Assessment (CNA) data to Statutory Health Insurance (SHI) claims data. The resulting dataset should enable the identification of factors in healthcare predicting the time between the onset of long-term care dependency and the admission to a nursing home in Germany in subsequent analyses. DESIGN: A deterministic record linkage was conducted using the key variables region, sex, date of birth and care level. In further steps, the underlying cause of care dependency (International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10)) was added for a higher level of distinction. Before linkage, the suitability of the two datasets for these procedures was assessed. After linkage, the results of each stage were analysed and the resulting dataset was evaluated cross-sectionally with respect to bias generated through this process. SETTING: The study comprises data from the German SHI and Statutory Long-Term Care Insurance. PARTICIPANTS: The study cohort comprised 158 069 individuals who became care dependent in 2006. We obtained CNA data for the year 2006 including 188 935 individuals. RESULTS: We could link CNAs to 66 310 individuals of the original study cohort, corresponding to 42.0%. Records from two federal states could not be matched due to missing data. Linkage rates were lower where more people shared the same attributes. The resulting dataset showed minor differences regarding age, sex and care level compared to the original cohort. CONCLUSIONS: Data linkage between German SHI claims data and CNA data is feasible. Failure to link was mostly attributable to a lack of distinction between individuals using available identifiers. The resulting dataset contains relevant information from both health services provision and functional status of care dependent people and is suitable for further analyses with critical reflection of representativity. |
format | Online Article Text |
id | pubmed-9247689 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-92476892022-07-14 Data linkage of German statutory health insurance claims data and care needs assessments preceding a population-based cohort study on nursing home admission Domhoff, Dominik Seibert, Kathrin Stiefler, Susanne Wolf-Ostermann, Karin Peschke, Dirk BMJ Open Health Services Research OBJECTIVES: We perform and evaluate record linkage of German Care Needs Assessment (CNA) data to Statutory Health Insurance (SHI) claims data. The resulting dataset should enable the identification of factors in healthcare predicting the time between the onset of long-term care dependency and the admission to a nursing home in Germany in subsequent analyses. DESIGN: A deterministic record linkage was conducted using the key variables region, sex, date of birth and care level. In further steps, the underlying cause of care dependency (International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10)) was added for a higher level of distinction. Before linkage, the suitability of the two datasets for these procedures was assessed. After linkage, the results of each stage were analysed and the resulting dataset was evaluated cross-sectionally with respect to bias generated through this process. SETTING: The study comprises data from the German SHI and Statutory Long-Term Care Insurance. PARTICIPANTS: The study cohort comprised 158 069 individuals who became care dependent in 2006. We obtained CNA data for the year 2006 including 188 935 individuals. RESULTS: We could link CNAs to 66 310 individuals of the original study cohort, corresponding to 42.0%. Records from two federal states could not be matched due to missing data. Linkage rates were lower where more people shared the same attributes. The resulting dataset showed minor differences regarding age, sex and care level compared to the original cohort. CONCLUSIONS: Data linkage between German SHI claims data and CNA data is feasible. Failure to link was mostly attributable to a lack of distinction between individuals using available identifiers. The resulting dataset contains relevant information from both health services provision and functional status of care dependent people and is suitable for further analyses with critical reflection of representativity. BMJ Publishing Group 2022-06-30 /pmc/articles/PMC9247689/ /pubmed/35772817 http://dx.doi.org/10.1136/bmjopen-2022-063475 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Health Services Research Domhoff, Dominik Seibert, Kathrin Stiefler, Susanne Wolf-Ostermann, Karin Peschke, Dirk Data linkage of German statutory health insurance claims data and care needs assessments preceding a population-based cohort study on nursing home admission |
title | Data linkage of German statutory health insurance claims data and care needs assessments preceding a population-based cohort study on nursing home admission |
title_full | Data linkage of German statutory health insurance claims data and care needs assessments preceding a population-based cohort study on nursing home admission |
title_fullStr | Data linkage of German statutory health insurance claims data and care needs assessments preceding a population-based cohort study on nursing home admission |
title_full_unstemmed | Data linkage of German statutory health insurance claims data and care needs assessments preceding a population-based cohort study on nursing home admission |
title_short | Data linkage of German statutory health insurance claims data and care needs assessments preceding a population-based cohort study on nursing home admission |
title_sort | data linkage of german statutory health insurance claims data and care needs assessments preceding a population-based cohort study on nursing home admission |
topic | Health Services Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9247689/ https://www.ncbi.nlm.nih.gov/pubmed/35772817 http://dx.doi.org/10.1136/bmjopen-2022-063475 |
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