Decision-Support Systems for Ambulatory Care, including Pandemic Requirements: Using Mathematically Optimized Solutions
Leithäuser N, Adelhütte D, Braun K, Büsing C, Comis M, Gersing T, Johann S, Koster A, Krumke S, Liers F, Schmidt E, Schneider J, Streicher M, Tschuppik S, Wrede S (2022)
Publication Language: English
Publication Status: Submitted
Publication Type: Journal article, Original article
Future Publication Type: Other publication type
Publication year: 2022
Journal
URI: https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-022-01866-x
DOI: 10.1186/s12911-022-01866-x
Open Access Link: https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-022-01866-x
Abstract
The healthcare sector poses many strategic, tactic and operational planning questions. Due to the historically grown structures, planning is often locally confined and much optimization potential is foregone.
Mathematical optimization can be used to model and solve these planning problems.
However, in order to convince decision-makers of an alternative solution structure, mathematical solutions must be comprehensible and tangible. In this work, we describe optimized decision-support systems for ambulatory care using the example of four different planning problems that cover a variety of aspects in terms of planning scope and decision support tools. The planning problems that we present are the problem of positioning centers for vaccination against Covid-19 (strategical) and emergency doctors (strategical/tactical), the out-of-hours pharmacy planning problem (tactical), and the route planning of patient transport services (operational). For each problem, we describe the planning question, give an overview of the mathematical model and present the implemented decision support application.
Authors with CRIS profile
Dennis Adelhütte
Kristin Braun Lehrstuhl für Analytics & Mixed-Integer Optimization Frauke Liers-Bergmann Professur für Optimization under Uncertainty & Data Analysis Sebastian Tschuppik Professur für Optimization under Uncertainty & Data Analysis
Kristin Braun Lehrstuhl für Analytics & Mixed-Integer Optimization Frauke Liers-Bergmann Professur für Optimization under Uncertainty & Data Analysis Sebastian Tschuppik Professur für Optimization under Uncertainty & Data Analysis
Related research project(s)
Mixed-Integer Non-Linear Optimisation: Algorithms and Applications (MINOA)
Jan. 1, 2018 - Dec. 31, 2021
Optimization of medical care in rural environments (HealthFaCT)
Dec. 1, 2016 - Nov. 30, 2020
Involved external institutions
Technische Universität Kaiserslautern
Germany (DE)
Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen
Germany (DE)
Fraunhofer-Institut für Techno- und Wirtschaftsmathematik (ITWM) / Fraunhofer Institute for Industrial Mathematics
Germany (DE)
Germany (DE)
Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen
Germany (DE)
Fraunhofer-Institut für Techno- und Wirtschaftsmathematik (ITWM) / Fraunhofer Institute for Industrial Mathematics
Germany (DE)
How to cite
APA:
Leithäuser, N., Adelhütte, D., Braun, K., Büsing, C., Comis, M., Gersing, T.,... Wrede, S. (2022). Decision-Support Systems for Ambulatory Care, including Pandemic Requirements: Using Mathematically Optimized Solutions. BMC Medical Informatics and Decision Making. https://dx.doi.org/10.1186/s12911-022-01866-x
MLA:
Leithäuser, Neele, et al. "Decision-Support Systems for Ambulatory Care, including Pandemic Requirements: Using Mathematically Optimized Solutions." BMC Medical Informatics and Decision Making (2022).
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