Health care network design with multiple objectives and stakeholders
Annals of Operations Research(2023)
Abstract
This paper aims to address the problem of locating/upgrading health care facilities with appropriate service levels while considering the preferences of all stakeholders mapped across a hierarchical decision network. To this end, an extended network goal programming model is adapted to ensure that a mix of balance and optimisation is attained in order to offer the decision that best satisfies the objectives of the national health care system, which are: network coverage, service level, network cost, and social impact of health centres. In addition, due to the highly uncertain environment of the health care systems, the robust counterpart of this model using the budget-of-uncertainty approach is developed in order to analyse the health care network’s performance to deal with uncertain parameters such as the national allocated budget and social impact. Key parameters which indicate the level of non-compensation between objectives, level of non-compensation between stakeholders, and level of centralisation in the health network along with the uncertainty budget are utilised to analyse the dynamics of decision network. The effectiveness of the model is demonstrated through use of a case study. The best-worst method is used to select a number of appropriate potential projects that serve as an input for the proposed model. To highlight the practical implications, different parametric analyses under both deterministic and uncertain environments are conducted. In addition, these experiments explore the compensatory behaviour between objectives and stakeholders in the network. Finally, some managerial insights are provided arising from the analytical results.
MoreTranslated text
Key words
OR in health services,Multiple stakeholders,Robust optimisation,Hierarchical decision network,Extended network goal programming
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined