There is need for software systems in order to coordinate the activities of healthcare professionals involved in the treatment of a patient, aligning the care delivery around already existing Clinical Practice Guidelines (CPGs). This is being carried out in care organizations by implementing integrated Care Pathways (CPs). Nonetheless, the generation of these care pathways is not trivial, and multiple barriers exist for their development and enactment. In this paper, a knowledge-based architecture is presented that, by means of Knowledge Engineering methods and Artificial Intelligence Planning and Scheduling (AI P&S) techniques, is able to automatically generate these care pathways from a computer-interpretable representation of CPGs, tackling some of these barriers. Firstly, these techniques consider the patient profile, the care organization details as well as the temporal and resource constraints, implicit in a care process, in order to generate a patient-focused care pathway. Moreover, they also allow the enactment of personalized care plans in a web-based format, powered by a workflow runtime engine, thus providing an ubiquitous and interactive execution to healthcare professionals. Finally, the architecture also includes monitoring and replanning techniques in order to check the current health status of patients and adapt care plans when they do not progress as expected. For the experimental evaluation of the architecture, several tests have been carried out in order to simulate a clinical environment where different care plans were automatically executed, monitored and adapted regarding the health conditions of patients as well as the recommendations specified in a real, CPG of the paediatric oncology area. As conclusion, the proposed architecture seems to be an adequate infrastructure for supporting the automated generation as well as the interactive execution and monitoring of patient-focused care pathways.
