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Tytuł pozycji:

Analyzing economies of scale and scope in hospitals by use of case mix planning.

Tytuł:
Analyzing economies of scale and scope in hospitals by use of case mix planning.
Autorzy:
McRae S; University Center for Health Sciences at Klinikum Augsburg (UNIKA-T), Neusässer Straße 47, 86156 Augsburg, Germany Chair of Health Care Operations/Health Information Management, Faculty of Business and Economics, University of Augsburg, Universitätsstraße 16, 86159, Augsburg, Germany. .
Brunner JO; University Center for Health Sciences at Klinikum Augsburg (UNIKA-T), Neusässer Straße 47, 86156 Augsburg, Germany Chair of Health Care Operations/Health Information Management, Faculty of Business and Economics, University of Augsburg, Universitätsstraße 16, 86159, Augsburg, Germany.
Bard JF; Graduate Program in Operations Research and Industrial Engineering, The University of Texas at Austin, 204 E. Dean Keeton St. C2200, Austin, TX, 78712-1591, USA.
Źródło:
Health care management science [Health Care Manag Sci] 2020 Mar; Vol. 23 (1), pp. 80-101. Date of Electronic Publication: 2019 Feb 21.
Typ publikacji:
Journal Article
Język:
English
Imprint Name(s):
Original Publication: Bussum, Netherlands : Baltzer Science Publishers, c1998-
MeSH Terms:
Economics, Hospital*
Hospital Costs*
Costs and Cost Analysis/*methods
Diagnosis-Related Groups/*economics
Diagnosis-Related Groups/statistics & numerical data ; Germany ; Hospitals/statistics & numerical data ; Humans
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Contributed Indexing:
Keywords: Case mix planning; Economies of scale and scope; Health care; Strategic planning
Entry Date(s):
Date Created: 20190222 Date Completed: 20200909 Latest Revision: 20200909
Update Code:
20240104
DOI:
10.1007/s10729-019-09476-2
PMID:
30790146
Czasopismo naukowe
This study analyzes the effect of economies of scale and scope on the optimal case mix of a hospital or hospital system. With respect to the ideal volume and patient composition, the goal is to evaluate (i) the impact of changes in the efficiency of resource use with increasing scale, and (ii) to determine the potential effects of spreading fixed costs over a greater number of patients. The problem is formulated as a non-linear mixed integer program. It turns out that this non-linear program is too difficult to be solved with standard software. As an alternative, an iterative procedure using piecewise linear approximations to derive lower and upper bounds is proposed and shown to converge to the optimum. The procedure is applied using a public database on German hospital costs and performance statistics. Results indicate that changes in the efficiency of resource use with increasing scale have a considerable impact if similar services can be consolidated, e.g., among different departments. However, if the scope for decision-making regarding the case mix of a hospital is limited, such changes may be negligible.
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