the space of clinical planning requires a complex arrangement of information, often not capable of being captured in a singular dataset. as a result, data fusion techniques can be used to combine multiple data sources as a method of enriching data to mimic and compliment the nature of clinical planning. these techniques are capable of aiding healthcare providers to produce higher quality clinical plans and better progression monitoring techniques. clinical planning and monitoring are important facets of healthcare which are essential to improving the prognosis and quality of life of patients with chronic and debilitating conditions such as copd. to exemplify this concept, we utilize a node-red-based clinical planning and monitoring too that combines data fusion techniques using the jdl model for data fusion and a domain specific language which features a self-organizing abstract syntax tree.