A KNOWLEDGE MANAGEMENT FRAMEWORK TO DEVELOP, MODEL, ALIGN AND OPERATIONALIZE CLINICAL PATHWAYS TO PROVIDE DECISION SUPPORT FOR COMORBID DISEASES

In this thesis we present an ontology based decision-support framework for handling co-morbidities by the alignment of ontologically modeled clinical practice guidelines (CPGs). The objective of this thesis is to formalize, model, align and operationalize the evidence-based clinical algorithms of co-morbid chronic heart failure (CHF) and atrial fibrillation (AF) in order to provide evidence-based clinical recommendations, care coordination and decision support to general practitioners (GPs) for effective management of CHF and AF. In this regard, the thesis addresses the following healthcare knowledge modeling issues: (a) modeling of healthcare knowledge, especially in terms of clinical guidelines and clinical pathways, to develop an ontology-based healthcare knowledge model for handling co-morbid diseases; (b) computerization of clinical pathways to offer point-of-care decision support; (c) alignment of ontologically-modeled disease-specific clinical pathways to handle co-morbid diseases; and (d) the provision of computerized decision support to general practitioners, based on modeled clinical guidelines and pathways, to assist them in handling chronic and co-morbid diseases. An elaborate OWL CP ontology for co-morbid CHF and AF—the CP ontology was developed that can be executed to support the diagnosis and management of co-morbid CHF and AF in a general practice setting. We have developed a decision support framework termed COMET (Co-morbidity Ontological Modeling & ExecuTion) that can handle three patient care scenarios, (i) patient has CHF; (ii) patient has AF; and (iii) patient develops a co-morbidity of both AF and CHF. COMET is accessible by web and is designed for GPs. COMET has been evaluated, both by simulated cases and by health professionals (GP and specialist), for its ability to handle single disease and comorbid care scenarios based on patient data and related constraints. The output at every phase is compared with the expected output as per single disease or comorbid management. Our results show that the resultant sequence of plans and their outcomes are comparable to the CP knowledge. Also, our ontology was able to handle any updates in the CP knowledge as advised by the domain experts