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1000
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Abstract/Summary
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Background!#!The increasing number of elderly individuals in the population and the simultaneous increase of the intensive care demand emphasizes the relevance of an efficient bed capacity analysis. Particularly, cardiovascular diseases represent a frequently occurring disease in the population group over 65 years of age. The objective of the following paper is the analysis of the retrospective and prospective intensive care demand by patients over 65 years with 6 selected (cardiovascular) codes of the International Statistical Classification of Diseases and Related Health Problems (ICD-10).!##!Methods!#!For the retrospective analysis, data from 2015-2017 were analyzed applying descriptive and bivariate methods. The analysis of the intensive care bed demand was based on the queuing theory.!##!Results!#!The monthly capacity utilization rates were constantly higher than the target capacity utilization rate of a maximum of 80% and in some cases even higher than 100%. In particular, the demand of patients with I50.14 was very high throughout the entire hospital. The bed demand analysis shows an increase from 9 needed beds in 2017 to 11 beds by 2030 for the 6 diagnosis groups. Regarding the 5 diagnosis groups without I50.14, only approximately half of the required beds were needed, retrospectively and in future.!##!Conclusion!#!The effect of demographic change on the intensive care demand already exists, and a continuing, prospective increase of the demand is expected. The results underline the need of effective and demand-oriented intensive care capacity planning. However, prior to expanding bed capacities, the analysis of admission criteria of intensive care unit patients is necessary to reserve capacities primarily for patients with real intensive care needs.
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1000
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Hinweis
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DeepGreen-ID: e25589dcc227467cbc9946f68c2120ce ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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