Catálogo de publicaciones - libros

Clinical guidelines are becoming more and more important as a means to improve the quality of care by supporting medical staff. Modelling guidelines in a computer-processable form is a prerequisite for various computer applications, to improve the quality of guidelines and to support their application. However, transforming the original text into a formal guideline representation is a difficult task requiring both the skills of a computer scientist and medical knowledge.

To bridge this gap, we have designed an intermediate representation called the MHB. It is a between informal representations such as free text and tables and more formal representations such as Asbru, GLIF, or PROforma. Obtaining an MHB representation from free text should be easier than modelling in a more formal representation because the vague expressions found in the guideline do not need to be replaced by precise information immediately.

One of the biggest issues in guideline dissemination nowadays is the need of adapting guidelines themselves to the application contexts, and to keep them up to date. In this paper, we propose a computer-based approach to facilitate the adaptation task. In particular, we focus on the management of two different levels of authors (users and supervisors), and of the history of the guideline versions.

Guidelines, care pathways, and other representations of high quality clinical practice can now be formalized and distributed in executable form. It is widely recognized that the ability to apply knowledge at the point of care creates an opportunity to influence clinicians’ behavior, encouraging compliance with evidence-based standards and improving care quality. The ability to share formal knowledge may also enable the medical community to build on work done by others and reduce content development costs. We propose a Medical Knowledge Repository and content model that supports assembly of components into new applications. Some types of resources that may be included in such a repository are defined, and a frame-based representation for indexing and structuring the components is described. The domain of breast cancer is used as a case study for demonstrating the feasibility of the approach.

In this paper, we propose a formal theory to describe the development of medical guideline text in detail, but at a sufficiently high level abstraction, in such way that essential elements of the guidelines are highlighted. We argue that because of the fragmentary nature of medical guidelines, an approach where details in guideline text are omitted is justified. The different aspects of a guideline are illustrated and discussed by a number of examples from the Dutch breast cancer guideline. Furthermore, we discuss how the theory can be used to detect flaws in the guideline text at an early stage in the guideline development process and consequently can be used to improve the quality of medical guidelines.

Clinical Guidelines are a major tool for improving the quality of medical care. A major current research direction is automating the application of guidelines at the point of care. To support that automation, several requirements must be fulfilled, such as specification in a machine-interpretable format, and connection to an electronic patent record. We propose an innovative approach to guideline application, which capitalizes on our The DeGeL framework includes a new hybrid model for incremental specification of free-text guidelines, using several intermediate representations. The new approach was implemented, in the case of the Asbru guideline ontology, as the system. Spock’s hybrid application engine supports the application of guidelines represented at an intermediate format. Spock uses the IDAN mediator for answering complex queries referred to heterogeneous clinical data repositories. Spock was evaluated in a preliminary fashion by applying several guidelines to sample patient data.

The UK National Health Service (NHS) is currently undergoing an intensive review into the way patient care is designed, delivered and recorded. One important element of this is the development of care pathways (clinical guidelines) that provide a reasoned plan of care for each patient journey, based on locally-agreed, evidence-based best practice. The ability to generate, critique, and continually evaluate and modify plans of patient care is considered important and challenging, but in the case of computerised systems, the possibilities are exciting. In this paper we outline the case for incorporating AI Planning technology in the generation, evaluation and manipulation of care plans. We demonstrate that an integrative approach to its adoption in the clinical guideline domain is called for. The PRO Clinical Guideline Modelling Language is used to demonstrate the issues involved.

Formalizing Clinical Practice Guidelines for subsequent computer-supported processing is a cumbersome, challenging, and time-consuming task. But currently available tools and methods do not satisfactorily support this task.

We propose a new multi-step approach using Information Extraction and Transformation. This paper addresses the Information Extraction task. We have developed several heuristics, which do not take Natural Language Understanding into account. We implemented our heuristics in a framework to apply them to several guidelines from the specialty of otolaryngology. Our evaluation shows that a heuristic-based approach can achieve good results, especially for guidelines with a major portion of semi-structured text.

Evidence-based clinical guidelines require frequent updates due to research and technology advances. The quality of guideline updates can be improved if the knowledge underlying the guideline text is explicitly modelled using the so-called , mappings between a text fragment and a formal representation of its corresponding medical knowledge.

Ontology-driven extraction of linguistic patterns is a method to automatically reconstruct the control knowledge captured in guidelines, which facilitates a more effective modelling and authoring of clinical guidelines. We illustrate by examples the use of a method for generating and searching for linguistic guideline patterns in the text of a guideline for treatment of breast cancer, and provide a general evaluation of usefulness of these patterns in the modelling of the guideline analyzed.

Medical guidelines can significantly improve quality of medical care and reduce costs. But how do we get sound and well-structured guidelines? This paper investigates the use of quality indicators that are formulated by medical institutions to evaluate medical care. The main research questions are (i) whether it is possible to those indicators in a specific knowledge representation language for medical guidelines, and (ii) whether it is possible to whether such guidelines do indeed satisfy these indicators. In a case study on two real-life guidelines (Diabetes and Jaundice) we have studied 35 indicators, that were developped independently from these guidelines. Of these 25 (71%!) suggested anomalies in one of the guidelines in our case study.

The National Cancer Institute’s Thesaurus (NCIT) has been created with the goal of providing a controlled vocabulary which can be used by specialists in the various sub-domains of oncology. It is intended to be used for purposes of annotation in ways designed to ensure the integration of data and information deriving from these various sub-domains, and thus to support more powerful cross-domain inferences. In order to evaluate its suitability for this purpose, we examined the NCIT’s treatment of the kinds of entities which are fundamental to an ontology of colon carcinoma. We here describe the problems we uncovered concerning classification, synonymy, relations and definitions, and we draw conclusions for the work needed to establish the NCIT as a reference ontology for the cancer domain in the future.