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Modelling the effect of demographic change and healthcare infrastructure on the patient structure in German hospitals – a longitudinal national study based on official hospital statistics

BACKGROUND: Effects of demographic change, such as declining birth rates and increasing individual life expectancy, require health system adjustments offering age- and needs-based care. In addition, healthcare factors can also influence health services demand. METHODS: The official German hospital s...

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Autores principales: Schoffer, Olaf, Schriefer, Dirk, Werblow, Andreas, Gottschalk, Andrea, Peschel, Peter, Liang, Linda A., Karmann, Alexander, Klug, Stefanie J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10566170/
https://www.ncbi.nlm.nih.gov/pubmed/37821860
http://dx.doi.org/10.1186/s12913-023-10056-y
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author Schoffer, Olaf
Schriefer, Dirk
Werblow, Andreas
Gottschalk, Andrea
Peschel, Peter
Liang, Linda A.
Karmann, Alexander
Klug, Stefanie J.
author_facet Schoffer, Olaf
Schriefer, Dirk
Werblow, Andreas
Gottschalk, Andrea
Peschel, Peter
Liang, Linda A.
Karmann, Alexander
Klug, Stefanie J.
author_sort Schoffer, Olaf
collection PubMed
description BACKGROUND: Effects of demographic change, such as declining birth rates and increasing individual life expectancy, require health system adjustments offering age- and needs-based care. In addition, healthcare factors can also influence health services demand. METHODS: The official German hospital statistics database with odd-numbered years between 1995 and 2011 was analysed. This is a national comprehensive database of all general hospital inpatient services delivered. Official data from hospital statistics were linked at the district level with demographic and socio-economic data as well as population figures from the official regional statistics. Panel data regression, modelling case numbers per hospital, was performed for 13 diagnosis groups that characterised the patient structure. Socio-demographic variables included age, sex, household income, and healthcare factors included bed capacity, personnel and hospital characteristics. RESULTS: The median number of annual treatments per hospital increased from 6 015 (5th and 95th percentile [670; 24 812]) in 1995 to 7 817 in 2011 (5th and 95th percentile [301; 33 651]). We developed models characterising the patient structure of health care in Germany, considering both socio-demographic and hospital factors. Demographic factors influenced case numbers across all major diagnosis groups. For example, the age groups 65–74 and 75 + influenced cerebrovascular disease case numbers (p < 0.001). Other important factors included human and material resources of hospitals or the household income of patients. Distinct differences between the models for the individual diagnosis groups were observed. CONCLUSIONS: Hospital planning should not only consider demographic change but also hospital infrastructure and socio-economic factors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-10056-y.
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spelling pubmed-105661702023-10-12 Modelling the effect of demographic change and healthcare infrastructure on the patient structure in German hospitals – a longitudinal national study based on official hospital statistics Schoffer, Olaf Schriefer, Dirk Werblow, Andreas Gottschalk, Andrea Peschel, Peter Liang, Linda A. Karmann, Alexander Klug, Stefanie J. BMC Health Serv Res Research BACKGROUND: Effects of demographic change, such as declining birth rates and increasing individual life expectancy, require health system adjustments offering age- and needs-based care. In addition, healthcare factors can also influence health services demand. METHODS: The official German hospital statistics database with odd-numbered years between 1995 and 2011 was analysed. This is a national comprehensive database of all general hospital inpatient services delivered. Official data from hospital statistics were linked at the district level with demographic and socio-economic data as well as population figures from the official regional statistics. Panel data regression, modelling case numbers per hospital, was performed for 13 diagnosis groups that characterised the patient structure. Socio-demographic variables included age, sex, household income, and healthcare factors included bed capacity, personnel and hospital characteristics. RESULTS: The median number of annual treatments per hospital increased from 6 015 (5th and 95th percentile [670; 24 812]) in 1995 to 7 817 in 2011 (5th and 95th percentile [301; 33 651]). We developed models characterising the patient structure of health care in Germany, considering both socio-demographic and hospital factors. Demographic factors influenced case numbers across all major diagnosis groups. For example, the age groups 65–74 and 75 + influenced cerebrovascular disease case numbers (p < 0.001). Other important factors included human and material resources of hospitals or the household income of patients. Distinct differences between the models for the individual diagnosis groups were observed. CONCLUSIONS: Hospital planning should not only consider demographic change but also hospital infrastructure and socio-economic factors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-10056-y. BioMed Central 2023-10-11 /pmc/articles/PMC10566170/ /pubmed/37821860 http://dx.doi.org/10.1186/s12913-023-10056-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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
Schoffer, Olaf
Schriefer, Dirk
Werblow, Andreas
Gottschalk, Andrea
Peschel, Peter
Liang, Linda A.
Karmann, Alexander
Klug, Stefanie J.
Modelling the effect of demographic change and healthcare infrastructure on the patient structure in German hospitals – a longitudinal national study based on official hospital statistics
title Modelling the effect of demographic change and healthcare infrastructure on the patient structure in German hospitals – a longitudinal national study based on official hospital statistics
title_full Modelling the effect of demographic change and healthcare infrastructure on the patient structure in German hospitals – a longitudinal national study based on official hospital statistics
title_fullStr Modelling the effect of demographic change and healthcare infrastructure on the patient structure in German hospitals – a longitudinal national study based on official hospital statistics
title_full_unstemmed Modelling the effect of demographic change and healthcare infrastructure on the patient structure in German hospitals – a longitudinal national study based on official hospital statistics
title_short Modelling the effect of demographic change and healthcare infrastructure on the patient structure in German hospitals – a longitudinal national study based on official hospital statistics
title_sort modelling the effect of demographic change and healthcare infrastructure on the patient structure in german hospitals – a longitudinal national study based on official hospital statistics
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10566170/
https://www.ncbi.nlm.nih.gov/pubmed/37821860
http://dx.doi.org/10.1186/s12913-023-10056-y
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