ArticleBMC health services research2023
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.
Article in BMC health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Workload demands, surgical education and training among resident surgeons in Germany: a cross-sectional questionnaire-based study.BMC medical education · 2026Article
- Temporal-spatial analysis and driving factors of coupling coordination between population and health services systems in China, 2010-2022.BMC health services research · 2026Article
- Population aging and changing hospitalization risks in Germany: a decomposition of changes in inpatient cases, 2005-2021.BMC public health · 2026Article
- Financing Regimes and Case-Mix Complexity in Psychiatric Hospitals Beyond the Pandemic Shock-Insights from a Regional European Healthcare System.Healthcare (Basel, Switzerland) · 2026Article
- Resistance training effects on gait parameters in older adults-a systematic review with multilevel meta-analysis and meta-regression.GeroScience · 2026Review
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Authors and funding
8 authors.
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Abstract
backgroundEffects 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.
methodsThe 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.
resultsThe 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.
conclusionsHospital planning should not only consider demographic change but also hospital infrastructure and socio-economic factors.
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