Community public hospital provides public health and basic medical services, and their construction environment has an important impact on the health and well-being of the residents. Due to the long… Click to show full abstract
Community public hospital provides public health and basic medical services, and their construction environment has an important impact on the health and well-being of the residents. Due to the long construction period of most community hospitals, the population expansion and the change in age structure have led to a mismatch between the needs of patients and the current situation, which is in urgent need of renovation. This paper aims to support the government and hospitals in making decisions by eliminating the blind spots in capital investment and benefit evaluation. In this study, environmental modification design variables are first established, and on this basis, the fuzzy Delphi method is used to understand the willingness for renovation on the part of patients, accompanying personnel, staff, healthcare workers as well as hospital administrators. Besides, the I-S model is used to identify the renovation projects that would maximize user satisfaction. Furthermore, the differences between patients and medical staff are compared. The ODM (Optimal Decision-making) model is used to evaluate the cost investment and benefits, which provides support for the decision-making of government and hospitals. The results clarify the key renovation design variables that can significantly improve user satisfaction and extend them into renovation strategies that can be landed, and identify renovation strategies with larger improvement scores and the range of renovation funds that maximize benefits to promote the sustainable development of community public hospitals. It can be seen that the ODM model can also be well applied to the renovation of community healthcare services. In addition, the reference classification and design variables should be adjusted according to the characteristics of China, taking into consideration the specificity of individual hospitals.
               
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