Insights and decision support for home health care services in times of disasters

Home health care (HHC) services are of vital importance for the health care system of many countries. Further increases in their demand must be expected and with it grows the need to sustain these services in times of disasters. Existing risk assessment tools and guides support HHC service providers...

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Bibliographic Details
Published in:Central European journal of operations research 2022-03, Vol.30 (1), p.133-157
Main Authors: Rest, Klaus-Dieter, Hirsch, Patrick
Format: Article
Language:English
Subjects:
Business and Management
Complex systems
Coronaviruses
COVID-19
Decision support systems
Disaster management
Health care
Health services
Heuristic methods
Home care
Home care services
Home care services industry
Home health care
Management
Medical appointments and schedules
Methods
Operations research
Operations Research/Decision Theory
Pandemics
Public transportation
Risk assessment
Systems design
Tabu search
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Summary:Home health care (HHC) services are of vital importance for the health care system of many countries. Further increases in their demand must be expected and with it grows the need to sustain these services in times of disasters. Existing risk assessment tools and guides support HHC service providers to secure their services. However, they do not provide insights on interdependencies of complex systems like HHC. Causal-Loop-Diagrams (CLDs) are generated to visualize the impacts of epidemics, blackouts, heatwaves, and floods on the HHC system. CLDs help to understand the system design as well as cascading effects. Additionally, they simplify the process of identifying points of action in order to mitigate the impacts of disasters. In a case study, the course of the COVID-19 pandemic and its effects on HHC in Austria in spring 2020 are shown. A decision support system (DSS) to support the daily scheduling of HHC nurses is presented and applied to numerically analyze the impacts of the COVID-19 pandemic, using real-world data from a HHC service provider in Vienna. The DSS is based on a Tabu Search metaheuristic that specifically aims to deal with the peculiarities of urban regions. Various transport modes are considered, including time-dependent public transport.
ISSN:1435-246X
1613-9178
DOI:10.1007/s10100-021-00770-5