DeGeL: a clinical-guidelines library and automated guideline-support tools.

Using machine-interpretable clinical guidelines to support evidence-based medicine promotes the quality of medical care. In this chapter, we present the Digital Electronic Guidelines Library (DeGeL), a comprehensive framework, including a Web-based guideline repository and a suite of tools, to support the use of automated guidelines for medical care, research, and quality assessment. Recently, we have developed a new version (DeGeL.NET) of the digital library and of its different tools. We intend to focus in our exposition on DeGeL's major tools, in particular for guideline specification in a Web-based and stand alone fashion (Uruz and Gesher), tools for search and retrieval (Vaidurya and DeGeLookFor) and for run time application (Spock); and to explain how these tools are combined within the typical lifecycle of a clinical guideline.

A quantitative assessment of a methodology for collaborative specification and evaluation of clinical guidelines.

We introduce a three-phase, nine-step methodology for specification of clinical guidelines (GLs) by expert physicians, clinical editors, and knowledge engineers and for quantitative evaluation of the specification's quality. We applied this methodology to a particular framework for incremental GL structuring (mark-up) and to GLs in three clinical domains. A gold-standard mark-up was created, including 196 plans and subplans, and 326 instances of ontological knowledge roles (KRs). A completeness measure of the acquired knowledge revealed that 97% of the plans and 91% of the KR instances of the GLs were recreated by the clinical editors. A correctness measure often revealed high variability within clinical editor pairs structuring each GL, but for all GLs and clinical editors the specification quality was significantly higher than random (p<0.01). Procedural KRs were more difficult to mark-up than declarative KRs. We conclude that given an ontology-specific consensus, clinical editors with mark-up training can structure GL knowledge with high completeness, whereas the main demand for correct structuring is training in the ontology's semantics.

Runtime application of Hybrid-Asbru clinical guidelines.

Clinical guidelines are a major tool in improving the quality of medical care. However, to support the automation of guideline-based care, several requirements must be filled, such as specification of the guidelines in a machine-interpretable format and a connection to an Electronic Patient Record (EPR). For several different reasons, it is beneficial to convert free-text guidelines gradually, through several intermediate representations, to a machine-interpretable format. It is also realistic to consider the case when an EPR is unavailable. We propose an innovative approach to the runtime application of intermediate-represented Hybrid-Asbru guidelines, with or without an available EPR. The new approach capitalizes on our extensive work on developing the Digital electronic Guideline Library (DeGeL) framework. The new approach was implemented as the Spock system. For evaluation, three guidelines were specified in an intermediate format and were applied to a set of simulated patient records designed to cover prototypical cases. In all cases, the Spock system produced the expected output, and did not produce an unexpected one. Thus, we have demonstrated the capability of the Spock system to apply guidelines encoded in the Hybrid-Asbru intermediate representation, when an EPR is not available.

Applying Hybrid-Asbru clinical guidelines using the Spock system.

Clinical Guidelines are a major tool for improving the quality of medical care. Currently, a major 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 Digital electronic Guidelines Library (DeGeL). 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 Spock system. Spock's hybrid application engine supports application of guideline represented at an intermediate format. Spock was evaluated in a preliminary fashion by applying several guidelines to sample patient data.

The Digital electronic Guideline Library (DeGeL): a hybrid framework for representation and use of clinical guidelines.

We propose to present a poster (and potentially also a demonstration of the implemented system) summarizing the current state of our work on a hybrid, multiple-format representation of clinical guidelines that facilitates conversion of guidelines from free text to a formal representation. We describe a distributed Web-based architecture (DeGeL) and a set of tools using the hybrid representation. The tools enable performing tasks such as guideline specification, semantic markup, search, retrieval, visualization, eligibility determination, runtime application and retrospective quality assessment. The representation includes four parallel formats: Free text (one or more original sources); semistructured text (labeled by the target guideline-ontology semantic labels); semiformal text (which includes some control specification); and a formal, machine-executable representation. The specification, indexing, search, retrieval, and browsing tools are essentially independent of the ontology chosen for guideline representation, but editing the semi-formal and formal formats requires ontology-specific tools, which we have developed in the case of the Asbru guideline-specification language. The four formats support increasingly sophisticated computational tasks. The hybrid guidelines are stored in a Web-based library. All tools, such as for runtime guideline application or retrospective quality assessment, are designed to operate on all representations. We demonstrate the hybrid framework by providing examples from the semantic markup and search tools.

A framework for a distributed, hybrid, multiple-ontology clinical-guideline library, and automated guideline-support tools.

Clinical guidelines are a major tool in improving the quality of medical care. However, most guidelines are in free text, not in a formal, executable format, and are not easily accessible to clinicians at the point of care. We introduce a Web-based, modular, distributed architecture, the Digital Electronic Guideline Library (DeGeL), which facilitates gradual conversion of clinical guidelines from text to a formal representation in chosen target guideline ontology. The architecture supports guideline classification, semantic markup, context-sensitive search, browsing, run-time application, and retrospective quality assessment. The DeGeL hybrid meta-ontology includes elements common to all guideline ontologies, such as semantic classification and domain knowledge; it also includes four content-representation formats: free text, semi-structured text, semi-formal representation, and a formal representation. These formats support increasingly sophisticated computational tasks. The DeGeL tools for support of guideline-based care operate, at some level, on all guideline ontologies. We have demonstrated the feasibility of the architecture and the tools for several guideline ontologies, including Asbru and GEM.

A distributed, collaborative, structuring model for a clinical-guideline digital-library.

The Digital Electronic Guideline Library (DeGeL) is a Web-based framework and a set of distributed tools that facilitate gradual conversion of clinical guidelines from free text, through semi-structured text, to a fully structured, executable representation. Thus, guidelines exist in a hybrid, multiple-format representation The three formats support increasingly sophisticated computational tasks. The tools perform semantic markup, classification, search, and browsing, and support computational modules that we are developing, for run-time application and retrospective quality assessment. We describe the DeGeL architecture and its collaborative-authoring authorization model, which is based on (1) multiple medical-specialty authoring groups, each including a group manager who controls group authorizations, and (2) a hierarchical authorization model based on the different functions involved in the hybrid guideline-specification process. We have implemented the core modules of the DeGeL architecture and demonstrated distributed markup and retrieval using the knowledge roles of two guidelines ontologies (Asbru and GEM). We are currently evaluating several of the DeGeL tools.