Knowledge-Driven Adaptive Execution of Care Pathways Based on Continuous Planning Techniques

Abstract

Abstract. Care pathways are excellent tools for the standardization of care delivery and the improvement of clinical efficiency. The high dynamism and unpredictability of the clinical environment require pathways to be adaptable to the deviations that may arise during their execution. In this work we present a methodology for the identification, monitoring, detection and managing of these deviations. Such deviations include evolving patient conditions, arbitrary medical modifications and unpredicted clinical settings. The care pathways are dynamically generated based on a knowledge-driven planning process that personalizes treatments according to up-to-date patient conditions and guarantees adherence to clinical guidelines recommendations. The implementation of the proposed methodology in a domain-independent continuous planning architecture is presented.Keywords: Personalization and adaptation of healthcare processes, Managing flexibility and exceptions in healthcare processes, Lifecycle management for healthcare processes, Process modeling in healthcare, Compliance of healthcare processes MotivationClinical guidelines and care pathways are clinical tools used in Clinical Decision Making in order to unify criteria according to the best scientific evidence [9,19]. Care Pathways can be seen as a way for adapting clinical guidelines to local conditions and their subsequent application to clinical practice [4]. These pathways are patient-centric processes that manage the patient care through the centralization of multidisciplinary tasks[13] which (1) are temporally annotated, (2)

Ten years of knowledge representation for health care (2009–2018): Topics, trends, and challenges

“…In addition, sensitive clinical knowledge must continually undergo quality analysis, critique, and review. In [52], SWRL rules were used to express guideline constraints and they were checked against CIGs that are personalized to the patient's context [60,63]. used continuous planning to adjust care pathways when deviations occur in the patient's expected state.…”

“…Among the papers, there are some in which new engines for the enactment of CIGs are described. The main approaches focus on adaptive continuous planning [51,60], a meta-engine for CIG execution [80], and the use of semantic-web inference rules in SPARQL [86,87] for clinical guidelines application.…”