Showing papers presented at "Knowledge Representation for Health-Care in 2014"

Towards a Conceptual Model for Enhancing Reasoning about Clinical Guidelines: A case-study on Comorbidity

Abstract: Computer-Interpretable Guidelines (CIGs) are representations of Clinical Guidelines (CGs) in computer interpretable languages CIGs have been pointed as an alternative to deal with the various limitations of paper based CGs to support healthcare activities Although the improvements offered by existing CIG languages, the complexity of the medical domain requires advanced features in order to reuse, share, update, combine or personalize their contents We propose a conceptual model for representing the content of CGs as a result from an iterative approach that take into account the content of real CGs, CIGs languages and foundational ontologies in order to enhance the reasoning capabilities required to address CIG use-cases In particular, we apply our approach to the comorbidity use-case and illustrate the model with a realistic case study (Duodenal Ulcer and Transient Ischemic Attack) and compare the results against an existing approach

Semantic Representation of Evidence-Based Clinical Guidelines

Abstract: Evidence-based Clinical Guidelines (EbCGs) are document or recommendation which have been created using the best clinical research findings of the highest value to aid in the delivery of optimum clinical care to patients. In this paper, we propose a lightweight formalism of evidence-based clinical guidelines by introducing the Semantic Web Technology for it. With the help of the tools which have been developed in the Semantic Web and Natural Language Processing (NLP), the generation of the formulations of evidence-based clinical guidelines become much easy. We will discuss several usecases of the semantic representation of EbCGs, and argue that it is potentially useful for the applications of the semantic web technology on the medical domain.

Preliminary Result on Finding Treatments for Patients with Comorbidity

Abstract: According to some research, comorbidity is reported in 35 to 80 % of all ill people [1] Multiple guidelines are needed for patients with comorbid diseases However, it is still a challenging problem to automate the application of multiple guidelines to patients because of redundancy, contraindicated, potentially discordant recommendations In this paper, we propose a mathematical model for the problem It formalizes and generalizes a recent approach proposed by Wilk and colleagues We also demonstrate that our model can be encoded, in a straightforward and simple manner, in Answer Set Programming (ASP) – a class of Knowledge Representation languages Our preliminary experiment also shows our ASP based implementation is efficient enough to process the examples used in the literature

Using First-Order Logic to Represent Clinical Practice Guidelines and to Mitigate Adverse Interactions

Abstract: Clinical practice guidelines (CPGs) were originally designed to help with evidence-based management of a single disease and such single disease focus has impacted research on CPG computerization. This computerization is mostly concerned with supporting different representation formats and identifying potential inconsistencies in the definitions of CPGs. However, one of the biggest challenges facing physicians is the application of multiple CPGs to comorbid patients. While various research initiatives propose ways of mitigating adverse interactions in concurrently applied CPGs, there are no attempts to develop a generalized framework for mitigation that captures generic characteristics of the problem, while handling nuances such as precedence relationships. In this paper we present our research towards developing a mitigation framework that relies on a first-order logic-based representation and related theorem proving and model finding techniques. The application of the proposed framework is illustrated with a simple clinical example.

META-GLARE: A Meta-System for Defining Your Own CIG System: Architecture and Acquisition

Abstract: Clinical practice guidelines (CPGs) play an important role in medical practice, and computerized support to CPGs is now one of the most central areas of research in Artificial Intelligence in medicine. In recent years, many groups have developed different computer-assisted management systems of Computer Interpretable Guidelines (CIGs). From one side, there are several commonalities between different approaches; from the other side, each approach has its own peculiarities and is geared towards the treatment of specific phenomena. In our work, we propose a form of generalization: instead of defining “yet another CIG system”, we propose a META-GLARE, a “meta”-system (or, in other words, a shell) to define new CIG systems. From one side, we try to capture the commonalities, by providing (i) a general tool for the acquisition, consultation and execution of hierarchical directed graphs (representing the control flow of actions in CIGs), parameterized over the types of nodes and of arcs constituting it, and (ii) a library of different elementary components of guidelines nodes (actions) and arcs, in which each type definition involves the specification of how objects of this type can be acquired, consulted and executed. From the other side, we provide generality and flexibility, by allowing free aggregations of such elementary components to define new primitive node and arc types. In this paper, we first propose META-GLARE general architecture and then, for the sake of brevity, we will focus only on the acquisition issue.

Conformance Analysis of the Execution of Clinical Guidelines with Basic Medical Knowledge and Clinical Terminology

Abstract: Clinical Guidelines (CGs) are developed for specifying the “best” clinical procedures for specific clinical circumstances. However, a CG is executed on a specific patient, with her peculiarities, and in a specific context, with its limitations and constraints. Physicians have to use Basic Medical Knowledge (BMK) in order to adapt the general CG to each specific case, even if the interplay between CGs and the BMK can be very complex, and the BMK should rely on medical terminological knowledge. In this paper, we focus on a posteriori analysis of conformance, intended as the adherence of an observed execution trace to CG and BMK knowledge. A CG description in the GLARE language is mapped to Answer Set Programming (ASP); the BMK and conformance rules are also represented in ASP. The BMK relies on the SNOMED CT terminology and additional (post-coordinated) concepts. Conformance analysis is performed in Answer Set Programming and identifies non-adherence situations to the CG and/or BMK, pointing out, in particular, discrepancies from one knowledge source that could be justified by another source, and discrepancies that cannot be justified.

An Algorithm for Guideline Transformation: From BPMN to PROforma

Abstract: In healthcare domain, business process modelling technologies are able to support clinical processes recommended in guidelines. It has been shown that BPMN is intuitively understood by all stakeholders, including domain experts. However, if we want to develop any computer system using clinical guidelines, we need them in an executable format. Thus, we need computer-interpretable guidelines. Although there are several formalisms tailored to capture medical processes, encoding a guideline in any of them is not as intuitive. We propose an automatic transformation from a guideline represented in BPMN to a computer-interpretable formalism, in this case, PROforma. To tackle this problem, we have studied the approaches that transform graph-oriented languages into block-oriented languages. We have adapted the solution to our specific-domain problem and to our target language, PROforma, which has features of both, graph and block-oriented paradigms.

Training Residents in the Application of Clinical Guidelines for Differential Diagnosis of the Most Frequent Causes of Arterial Hypertension with Decision Tables

Abstract: Arterial hypertension (AH) is an abnormal high blood pressure in the arteries with many possible etiologies. Differential diagnosis of the causes of AH is a complex clinical process that requires the simultaneous consideration of many clinical practice guidelines.

Exploiting the Relation Between Environmental Factors and Diseases: A Case Study on Chronic Obstructive Pulmonary Disease

Abstract: The raise of chronic diseases poses a challenge for the health care sector worldwide. In many cases, diseases are affected by an environmental component that, until now, could be hardly controlled. However, with the recent advances in information and communication technologies applied to cities, it becomes possible to collect real-time environmental data and use them to provide chronic patients with recommendations able to adapt to the changing environmental conditions.

Assessment of Clinical Guideline Models Based on Metrics for Business Process Models

Abstract: The formalisation of clinical guidelines is a long and demanding task which usually involves both clinical and IT staff. Because of the features of guideline representation languages, a clear understanding of the final guideline model may prove complicated for clinicians. In this context, an assessment of the understandability of the guideline model becomes crucial. In the field of Business Process Modelling (BPM) there is research on structural metrics and their connection with the quality of process models, concretely with understandability and modifiability. In this paper we adapt the structural metrics that have been proposed in the field of BPM in terms of the features of a specific guideline representation language, which is PROforma. Additionally, we present some experiments consisting in the application of these adapted metrics to the assessment of guideline models described in PROforma. Although it has not been possible to draw meaningful conclusions on the overall quality of the models, our experiments have served to shed light on important aspects to be considered, such as the hierarchical decomposition of processes.

Knowledge-Intensive Medical Process Similarity

Abstract: Process model comparison and similar processes retrieval are key issues to be addressed in many real world situations, and particularly relevant ones in medical applications, where similarity quantification can be exploited to accomplish goals such as conformance checking, local process adaptation analysis, and hospital ranking.

A Process-Oriented Methodology for Modelling Cancer Treatment Trial Protocols

Abstract: Cancer-patient management in the context of a multi-center treatment trial requires following a complex detailed process involving multispecialty patient treatment as well as study-related tasks, described in free-text protocol documents. We present a process-oriented approach for modelling clinical trial treatment protocols (CTTPs) to be used for enabling applications that support protocol-based care process delivery, monitoring and analysis. This modelling approach provides an intuitive visual representation of the protocol document catering for change management, intra-center and national adaptations to the master protocol, and multi-level share-ability. The methodology can be re-used in CTTPs of different cancer domains due to the similarity of the CTTPs in terms of required content.