Optimization and Evaluation of Community Smart Health Spaces: A Hybrid Model Based on a SWOT Analysis, the Four Orders of Design, AHP, and TOPSIS

The current design of community smart health spaces lacks a systematic theoretical framework. This study innovatively proposes a hybrid model combining a SWOT analysis, the “four orders of design”, AHP, and TOPSIS to optimize the design of community smart health spaces systematically. First, a SWOT analysis is employed to assess the current state of community smart health spaces, and strategies are proposed based on this study. Subsequently, the “four orders of design” framework is integrated to clarify the design priorities for symbols, tangible objects, action events, and system environments. The AHP hierarchical analysis method is then used to quantify the weights of 16 design indicators, ensuring the objectivity and scientific rigor of decision-making. Finally, the TOPSIS method is introduced to validate the feasibility of the proposed solutions. The study found that (1) among the four categories of needs—behavioral experience, perceptual experience, hardware facilities, and software facilities—behavioral experience (weight 0.470) is the core indicator, with telemedicine (0.197) and autonomous driving (0.121) being the key functions. (2) The overall alignment of this design scheme is 0.844, with user satisfaction significantly superior to traditional schemes, proving the feasibility of the hybrid model. The research findings support decision-making in constructing smart health spaces in communities, thereby helping to upgrade smart health space services in communities.