In this paper we consider self organizing frameworks for healthcare in a model mimicking biologic frameworks. We support self organization via attribute based memory mapped information in original random form. ‘Spontaneous interoperability’ and subsequent adaptability is facilitated by the memory map which describes the serialized electronic ordering of transferred information, its evolutionary history, and meta-data associated with the information. Memory maps are transferred in a discovery process facilitating interoperability by means of application adaptation. We demonstrate the potential for network entities utilizing the framework to work together even though they were initially unaware of the potential. We recognize the challenges faced, define initial targeted infrastructure to aid in the advancement of adaptive networks, and suggest future work. The goals of adaptability in healthcare require timely access to information relevant to the decision process and the elimination of slow and costly integrations. It will allow for accurate representation, diversity, longevity/viability, and increased depth/ range of computable information for computational intelligence enhancement. Increased availability of information provided by an adaptive network may help to improved patient outcomes and provide earlier detection, prevention of disease, and a reduction in medical errors.