Samina Raza Abidi

Semantic Web Framework for Knowledge-Centric Clinical Decision Support Systems

Lately, there have been considerable efforts to computerize Clinical Practice Guidelines (CPG) so that they can be executed via Clinical Decision Support Systems (CDSS) at the point of care. We present a Semantic Web framework to both model and execute the knowledge within a CPG to develop knowledge-centric CDSS. Our approach entails knowledge modeling through a synergy between multiple ontologies---i.e. a domain ontology, CPG ontology and patient ontology. We develop decision-rules based on the ontologies, and execute them with a proof engine to derive CPG-based patient specific recommendations. We present a prototype of our CPG-based CDSS to execute the CPG for Follow-up after Treatment for Breast Cancer.

Towards the Merging of Multiple Clinical Protocols and Guidelines via Ontology-Driven Modeling

Decision support systems based on computerized Clinical Protocols (CP) and Clinical Practice Guidelines (CPG) fall short when dealing with patient co-morbidites, as this demands the concurrent merging of multiple CP/CPG. We present an ontology-based approach for the merging of CPG and CP at two levels---i.e. knowledge modeling level and knowledge execution level. We have developed specialized ontological modeling constructs to facilitate merging of CPG and CP. We demonstrate the merging of multiple location-specific CP and disease-specific CPG.

A Conceptual Framework for Ontology Based Automating and Merging of Clinical Pathways of Comorbidities

In this paper we present a conceptual framework for ontology based knowledge representation and merging of Clinical Pathways (CP) of comorbidities. Paper based CP are static documents which do not have adaptability to accommodate dynamic changes in a patients conditions, particularly in case of co-morbidity, since most CP are focused on a single disease management. Our approach to computerize and merge CP of comorbidities for decision support purpose include; 1. Representation of comorbidity CP as OWL ontologies, 2. Merging ontologies along common tasks, 3. Execution of merged ontology using OWL reasoner to provide CP mediated decision support, 4. Evaluation of recommendations by instantiating the ontology with comorbidity scenarios. Most challenging and unique aspect of this research is that it involves the dynamic integration of computerized CP of two concurrent comorbid diseases, whilst maintaining clinical pragmatics and medical correctness. We believe that Semantic Web has enormous potential to achieve this goal.

Exploiting Semantic Web Technologies to Develop OWL-Based Clinical Practice Guideline Execution Engines

Computerizing paper-based CPG and then executing them can provide evidence-informed decision support to physicians at the point of care. Semantic web technologies especially web ontology language (OWL) ontologies have been profusely used to represent computerized CPG. Using semantic web reasoning capabilities to execute OWL-based computerized CPG unties them from a specific custom-built CPG execution engine and increases their shareability as any OWL reasoner and triple store can be utilized for CPG execution. However, existing semantic web reasoning-based CPG execution engines suffer from lack of ability to execute CPG with high levels of expressivity, high cognitive load of computerization of paper-based CPG and updating their computerized versions. In order to address these limitations, we have developed three CPG execution engines based on OWL 1 DL, OWL 2 DL and OWL 2 DL + semantic web rule language (SWRL). OWL 1 DL serves as the base execution engine capable of executing a wide range of CPG constructs, however for executing highly complex CPG the OWL 2 DL and OWL 2 DL + SWRL offer additional executional capabilities. We evaluated the technical performance and medical correctness of our execution engines using a range of CPG. Technical evaluations show the efficiency of our CPG execution engines in terms of CPU time and validity of the generated recommendation in comparison to existing CPG execution engines. Medical evaluations by domain experts show the validity of the CPG-mediated therapy plans in terms of relevance, safety, and ordering for a wide range of patient scenarios.

Ontology-Based Modeling of Breast Cancer Follow-up Clinical Practice Guideline for Providing Clinical Decision Support

Breast cancer is the most common cancer among women in Canada. There are identified incentives to the transfer of breast cancer follow-up care to family physicians after primary treatment has been completed by oncologists at the tertiary care centers. This paper presents a semantic web approach to develop a clinical decision support system to support family physicians to provide breast cancer follow-up care. Our approach involved the computerization and execution of a breast cancer follow-up clinical practice guideline. The computerization of the clinical practice guideline led to the development of a breast cancer ontology. We present our breast cancer ontology which models the knowledge inherent within the breast cancer follow-up clinical practice guideline - the breast cancer ontology serves as the knowledge source to determine patient-specific recommendations. In this paper, we discuss the ontology engineering process that highlights the specification of our breast cancer ontology in terms of clinical concepts and the relationships between the concepts expressed as OWL classes and properties, using the protege ontology development tool.

Exploiting OWL reasoning services to execute ontologically-modeled clinical practice guidelines

Ontology-based modeling of Clinical Practice Guidelines (CPG) is a well-established approach to computerize CPG for execution in clinical decision support systems. Many CPG computerization approaches use the Web Ontology Language (OWL) to represent the CPGs knowledge, but they do not exploit its reasoning services to execute the CPG. In this paper, we present our CPG execution approach that leverages OWL reasoning services to execute CPG. In this way, both CPG knowledge representation and execution semantics are maintained within the same formalism. We have developed three different OWL-based CPG execution engines using OWL-DL, OWL 2 and SWRL. We evaluate the efficacy of our execution engines by executing an existing OWL based CPG. We also present a comparison of the execution capabilities of our three CPG execution engines.

Ontology-based knowledge modeling to provide decision support for comorbid diseases

Handling comorbid diseases in a decision support framework is a challenging problem as it demands the synthesis of clinical procedures for two or more diseases whilst maintaining clinical pragmatics. In this paper we present a knowledge management approach for handling comorbid diseases by the systematic alignment of the Clinical Pathways (CP) of comorbid diseases. Our approach entails: (a) knowledge synthesis to derive disease-specific CP from evidence-bases sources; (b) knowledge modeling to abstract medical and procedural knowledge from the CP; (c) knowledge representation to computerize the CP in terms of a CP ontology; and (d) knowledge alignment by aligning multiple CP to develop a unified CP knowledge model for comorbid diseases. We present the COMET system that provides decision support to handle comorbid cardiac heart failure and atrial fibrillation.

Operationalizing Prostate Cancer Clinical Pathways: An Ontological Model to Computerize, Merge and Execute Institution-Specific Clinical Pathways

The computerization of paper-based Clinical Pathways (CP) can allow them to be operationalized as a decision-support and care planning tool at the point-of-care. We applied a knowledge management approach to computerize the prostate cancer CP for three different locations. We present a new prostate cancer CP ontology that features the novel merging of multiple CP based on the similarities of their diagnostic-treatment concepts, whilst maintaining the unique aspects of each specific CP, to realize a common unified CP model. In this paper we will highlight the main components of our prostate cancer CP ontology, and discuss the concept of CP branching and merging nodes. We conclude that our computerized CP can be executed through a logic-based engine to realize a point-of-care decision-support system for managing prostate cancer care.

Using OWL Ontologies for Clinical Guidelines Based Comorbid Decision Support

In this paper we present an ontology-based clinical decision-support framework for handling comorbidities by alignment of ontology modeled clinical practice guidelines (CPG). Our knowledge management approach to develop clinical decision support systems for co-morbid conditions entails: (a) knowledge synthesis to derive disease-specific clinical pathways (CP) from evidence-bases sources, (b) knowledge modeling to abstract medical and procedural knowledge from the CP, (c) knowledge representation to computerize the CP in terms of a CP ontology, and (d) knowledge alignment by aligning multiple CP to develop a unified CP knowledge model for co morbid diseases. We present the COMET (Co-morbidity Ontological Modeling & ExecuTion) system that provides decision support to handle co morbid chronic heart failure and a trial fibrillation. COMET is web-accessible and is designed for family practitioners.

An intelligent info-structure for composing and pushing personalised healthcare information over the Internet

Provides a technology-enriched solution to Web-mediated patient empowerment initiatives via the implementation of an intelligent information structure that features (1) the dynamic composition of personalized healthcare information (PHI) conforming to an individuals EMR (electronic medical record) based health profile; and (2) proactive Internet-based delivery of PHI. Healthcare information personalization is achieved via profile-specific selection and template-specific aggregation of multiple, fine-grained, pre-authored, generic, topic-specific healthcare information content. The use of intelligent constraint satisfaction techniques ensure the medical correctness of the dynamically composed PHI document. The application of Internet-based push technology allows the PHI document to be pushed to the individuals e-mail account, thus guaranteeing the timely availability of high-quality health maintenance information.