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1.  A Graphical Framework for Specification of Clinical Guidelines at Multiple Representation Levels 
Formalization of a clinical guideline for purposes of automated application and quality assessment mainly involves conversion of its free-text representation into a machine comprehensible representation, i.e., a formal language, thus enabling automated support. The main issues involved in this process are related to the collaboration between the expert physician and the knowledge engineer. We introduce GESHER - a graphical framework for specification of clinical guidelines at multiple representation levels. The GESHER architecture facilitates incremental specification through a set of views adapted to each representation level, enabling this process to proceed smoothly and in a transparent fashion, fostering extensive collaboration among the various types of users. The GESHER framework supports specification of guidelines at multiple representation levels, in more than one specification language, and uses the DeGeL digital guideline library architecture as its knowledge base. The GESHER architecture also uses a temporal abstraction knowledge base to store its declarative knowledge, and a standard medical-vocabularies server for generic specification of key terms, thus enabling reuse of the specification at multiple sites.
PMCID: PMC1560835  PMID: 16779126
2.  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.
PMCID: PMC1560650  PMID: 16779161
3.  Patient Safety in Guideline-Based Decision Support for Hypertension Management: ATHENA DSS 
The Institute of Medicine recently issued a landmark report on medical error.1 In the penumbra of this report, every aspect of health care is subject to new scrutiny regarding patient safety. Informatics technology can support patient safety by correcting problems inherent in older technology; however, new information technology can also contribute to new sources of error. We report here a categorization of possible errors that may arise in deploying a system designed to give guideline-based advice on prescribing drugs, an approach to anticipating these errors in an automated guideline system, and design features to minimize errors and thereby maximize patient safety. Our guideline implementation system, based on the EON architecture, provides a framework for a knowledge base that is sufficiently comprehensive to incorporate safety information, and that is easily reviewed and updated by clinician-experts.
PMCID: PMC419409
4.  Patient safety in guideline-based decision support for hypertension management: ATHENA DSS. 
The Institute of Medicine recently issued a landmark report on medical error.1 In the penumbra of this report, every aspect of health care is subject to new scrutiny regarding patient safety. Informatics technology can support patient safety by correcting problems inherent in older technology; however, new information technology can also contribute to new sources of error. We report here a categorization of possible errors that may arise in deploying a system designed to give guideline-based advice on prescribing drugs, an approach to anticipating these errors in an automated guideline system, and design features to minimize errors and thereby maximize patient safety. Our guideline implementation system, based on the EON architecture, provides a framework for a knowledge base that is sufficiently comprehensive to incorporate safety information, and that is easily reviewed and updated by clinician-experts.
PMCID: PMC2243380  PMID: 11825183
5.  How can information extraction ease formalizing treatment processes in clinical practice guidelines? A method and its evaluation☆ 
Formalizing clinical practice guidelines (CPGs) for a subsequent computer-supported processing is a challenging, but burdensome and time-consuming task. Existing methods and tools to support this task demand detailed medical knowledge, knowledge about the formal representations, and a manual modeling. Furthermore, formalized guideline documents mostly fall far short in terms of readability and understandability for the human domain modeler.
Methods and material:
We propose a new multi-step approach using information extraction methods to support the human modeler by both automating parts of the modeling process and making the modeling process traceable and comprehensible. This paper addresses the first steps to obtain a representation containing processes which is independent of the final guideline representation language.
We have developed and evaluated several heuristics without the need to apply natural language understanding and implemented them in a framework to apply them to several guidelines from the medical subject of otolaryngology. Findings in the evaluation indicate that using semi-automatic, step-wise information extraction methods are a valuable instrument to formalize CPGs.
Our evaluation shows that a heuristic-based approach can achieve good results, especially for guidelines with a major portion of semi-structured text. It can be applied to guidelines irrespective to the final guideline representation format.
PMCID: PMC2858817  PMID: 16962747
Information extraction and integration; Clinical practice guidelines; Computer-interpretable guidelines; Guideline representation; Treatment processes; Time-oriented information; Otolaryngology
6.  Ontological approach for safe and effective polypharmacy prescription 
The intake of multiple medications in patients with various medical conditions challenges the delivery of medical care. Initial empirical studies and pilot implementations seem to indicate that generic safe and effective multi-drug prescription principles could be defined and reused to reduce adverse drug events and to support compliance with medical guidelines and drug formularies. Given that ontologies are known to provide well-principled, sharable, setting-independent and machine-interpretable declarative specification frameworks for modeling and reasoning on biomedical problems, we explore here their use in the context of multi-drug prescription. We propose an ontology for modeling drug-related knowledge and a repository of safe and effective generic prescription principles. To test the usability and the level of granularity of the developed ontology-based specification models and heuristic we implemented a tool that computes the complexity of multi-drug treatments, and a decision aid to check the safeness and effectiveness of prescribed multi-drug treatments.
PMCID: PMC3540569  PMID: 23304299
7.  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.
PMCID: PMC1480281  PMID: 14728241
8.  Architecture for a multipurpose guideline execution engine. 
Integration of guideline knowledge into the clinical workflow is essential, for improving adherence to guidelines. Guidelines in structured formats can be utilized by computer programs to provide decision support in clinical information systems, as well as to facilitate workflow. We have designed an architecture for a flexible guideline execution engine that can be utilized in clinical decision support applications. The engine may be utilized for other applications such as referral management, medical education, and conducting clinical trials. The engine executes guidelines that are defined in an extension of the Guideline Interchange Format (GLIF). GLIF was extended to support representation of constructs that are essential to the execution of the guideline. A prototype of the engine was implemented based on this architecture. The engine is being utilized in two clinical applications that draw on guidelines for decision support. The engine was also used for developing an educational application aimed at testing knowledge of guideline recommendations.
PMCID: PMC2232598  PMID: 10566450
9.  An architecture for a distributed guideline server. 
A number of barriers exist which prevent the widespread integration of practice guidelines with electronic medical record systems. These include dependencies on clinical databases, as well as problems with converting existing guideline specifications into computable rules. We are developing the MBTA (Modeling Better Treatment Advice) practice guideline system which uses a distributed client-server architecture and an object-oriented data representation to support practice guidelines usable by different electronic medical record systems. We describe the structure and organization of MBTA, focusing on how an open systems design, combined with principles of guideline implementation, can be used to provide a general purpose guideline server for use by a variety of clinical workstations.
PMCID: PMC2579090  PMID: 8563275
10.  Developing Nursing Computer Interpretable Guidelines: a Feasibility Study of Heart Failure Guidelines in Homecare. 
AMIA Annual Symposium Proceedings  2013;2013:1353-1361.
Homecare is the fastest growing healthcare sector and evidence based information systems are critically needed. Nurses provide most of the care in homecare setting, yet there is a lack of knowledge on the feasibility of applying existing methodologies to generate computer interpretable nursing guidelines for home care. This study examined the feasibility of encoding homecare nursing heart failure guideline into a computer interpretable format. First, we achieved experts’ consensus on the relevant guideline. Then, after training on the graphical tool for gradual knowledge specification (Gesher), we generated a comprehensive, hierarchical and time-oriented computer interpretable guideline using one of the guideline modeling languages (Asbru). The final guideline included 167 recommendations and experts’ evaluation confirmed the adequacy of guideline knowledge representation. Future work should expand the applicability of our methodology and tools to nursing specialties other than heart failure and develop methods for comprehensive quality evaluation of the resulting guidelines.
PMCID: PMC3900150  PMID: 24551412
11.  An ontological approach for the development of shareable guidelines. 
Computer-based clinical guidelines and protocols are being increasingly applied in diverse areas. Although there is still little standardization to facilitate sharing, various parties are engaged in the development of shareable guideline representation formalisms and corresponding decision support systems. This paper mentions some of these developed representations, discusses their pros en cons, and demonstrates and discusses a new approach, which combines common elements from earlier-developed formalisms with new ones to improve the reusability and shareability of developed guidelines. An ontological representation is presented that formalizes guidelines in terms of domain-specific knowledge and employed generic strategies that use this domain-specific knowledge in order to solve particular guideline tasks. Furthermore, a framework is described that supports this representation and three examples are shown of guidelines of various granularity and complexity that were developed by means of this approach.
PMCID: PMC2244001  PMID: 11079866
12.  Using GEM-encoded guidelines to generate medical logic modules. 
Among the most effective strategies for changing the process and outcomes of clinical care are those that make use of computer-mediated decision support. A variety of representation models that facilitate computer-based implementation of medical knowledge have been published, including the Guideline Elements Model (GEM) and the Arden Syntax for Medical Logic Modules (MLMs). We describe an XML-based application that facilitates automated generation of partially populated MLMs from GEM-encoded guidelines. These MLMs can be further edited and shared among Arden-compliant information systems to provide decision support. Our work required three steps: (a) Knowledge extraction from published guideline documents using GEM, (b) Mapping GEM elements to the MLM slots, and (c) XSL transformation of the GEM-encoded guideline. Processing of a sample guideline generated 15 MLMs, each corresponding to a conditional or imperative element in the GEM structure. Mechanisms for linking various MLMs are necessary to represent the complexity of logic typical of a guideline.
PMCID: PMC2243667  PMID: 11825147
13.  Semantic Clinical Guideline Documents 
Decision-support systems based on clinical practice guidelines can support physicians and other health-care personnel in the process of following best practice consistently. A knowledge-based approach to represent guidelines makes it possible to encode computer-interpretable guidelines in a formal manner, perform consistency checks, and use the guidelines directly in decision-support systems.
Decision-support authors and guideline users require guidelines in human-readable formats in addition to computer-interpretable ones (e.g., for guideline review and quality assurance). We propose a new document-oriented information architecture that combines knowledge-representation models with electronic and paper documents. The approach integrates decision-support modes with standard document formats to create a combined clinical-guideline model that supports on-line viewing, printing, and decision support.
PMCID: PMC1560832  PMID: 16779037
14.  A virtual medical record for guideline-based decision support. 
A major obstacle in deploying computer-based clinical guidelines at the point of care is the variability of electronic medical records and the consequent need to adapt guideline modeling languages, guideline knowledge bases, and execution engines to idiosyncratic data models in the deployment environment. This paper reports an approach, developed jointly by researchers at Newcastle and Stanford, where guideline models are encoded assuming a uniform virtual electronic medical record and guideline-specific concept ontologies. For implementing a guideline-based decision-support system in multiple deployment environments, we created mapping knowledge bases to link terms in the concept ontology with the terminology used in the deployment systems. Mediation components use these mapping knowledge bases to map data in locally deployed medical record architectures to the virtual medical record. We discuss the possibility of using the HL7 Reference Information Model (RIM) as the basis for a standardized virtual medical record, showing how this approach also complies with the European pre-standard ENV13606 for electronic healthcare record communication.
PMCID: PMC2243604  PMID: 11825198
15.  Embedding the Guideline Elements Model in Web Ontology Language 
The Guideline Elements Model (GEM) uses XML to represent the heterogeneous knowledge contained in clinical practice guidelines. GEM has important applications in computer aided guideline authoring and clinical decision support systems. However, its XML representation format could limit its potential impact, as semantic web ontology languages, such as OWL, are becoming major knowledge representation frameworks in medical informatics. In this work, we present a faithful translation of GEM from XML into OWL. This translation is intended to keep the knowledge model of GEM intact, as this knowledge model has been carefully designed and has become a recognized standard. An OWL representation would make GEM more applicable in medical informatics systems that rely on semantic web. This work will also be the initial step in making GEM a guideline recommendation ontology.
PMCID: PMC2815420  PMID: 20351934
16.  On Implementing Clinical Decision Support: Achieving Scalability and Maintainability by Combining Business Rules and Ontologies. 
We present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engine that executes declarative if-then rules stored in a rule-base referencing objects and methods in a business object model. The rules engine executes object methods by invoking services implemented on the clinical data repository. Specialized inferences that support classification of data and instances into classes are identified and an approach to implement these inferences using an OWL based ontology engine is presented. Alternative representations of these specialized inferences as if-then rules or OWL axioms are explored and their impact on the scalability and maintenance of the system is presented. Architectural alternatives for integration of clinical decision support functionality with the invoking application and the underlying clinical data repository; and their associated trade-offs are discussed and presented.
PMCID: PMC1839410  PMID: 17238374
17.  GLIF3: the evolution of a guideline representation format. 
The Guideline Interchange Format (GLIF) is a language for structured representation of guidelines. It was developed to facilitate sharing clinical guidelines. GLIF version 2 enabled modeling a guideline as a flowchart of structured steps, representing clinical actions and decisions. However, the attributes of structured constructs were defined as text strings that could not be parsed, and such guidelines could not be used for computer-based execution that requires automatic inference. GLIF3 is a new version of GLIF designed to support computer-based execution. GLIF3 builds upon the framework set by GLIF2 but augments it by introducing several new constructs and extending GLIF2 constructs to allow a more formal definition of decision criteria, action specifications and patient data. GLIF3 enables guideline encoding at three levels: a conceptual flowchart, a computable specification that can be verified for logical consistency and completeness, and an implementable specification that can be incorporated into particular institutional information systems.
PMCID: PMC2243832  PMID: 11079963
18.  Versioning computer-interpretable guidelines: Semi-automatic modeling of ‘Living Guidelines’ using an information extraction method☆ 
Clinical practice guidelines (CPGs) are means to provide evidence-based medical knowledge. In order to make up-to-date “best” scientific evidence available these documents need to be updated on an ongoing basis. An effective method to accomplish this aim is offered by the so-called “living guidelines”: Living guidelines are documents presenting up-to-date and state-of-the-art knowledge to practitioners. To have guidelines implemented by computer-support they have to be formalized in a computer-interpretable form in a first step. Due to the complexity of such formats the formalization process is burdensome and time-consuming. Automating parts of the modeling process and, consequently, modeling updates of these guideline documents are demanded.
Methods and material
The LASSIE methodology supports this task by formalizing guidelines in several steps from the textual form to the guideline representation language Asbru using a document-centric approach. LASSIE uses information extraction techniques to semi-automatically accomplish these steps. We apply LASSIE to support the implementation of living guidelines.
Based on a living guideline published by the Scottish Intercollegiate Guidelines Network (SIGN) we show that adaptations of previously formalized guidelines can be accomplished easily and fast. Thereby, the different versions of guideline documents are compared and updates are identified. Due to the traceable formalization method of linking text parts and their corresponding formal models, we are able to inherit unchanged models from previously formalized versions. Thus, we only need to formalize updated text parts using the semi-automatic formalization method LASSIE.
We propose a simple, time-saving, but effective method called LASSIE to formalize new guideline versions of previously formalized CPGs. Furthermore, models that have been added or modified by knowledge engineers in previous versions can also be transferred easily. This will result in a faster implementation of new guideline versions also known as living guidelines to provide up-to-date knowledge necessary for accomplishing the daily work of health care professionals.
PMCID: PMC2859225  PMID: 18950994
Information extraction; Clinical practice guidelines; Living guidelines; Computer-interpretable guidelines; Guideline representation; Treatment processes; Asthma
19.  Technical aspects of quality assurance in radiation oncology 
The technical aspects of quality assurance (QA) in radiation oncology as practice in the United States will be reviewed and updated in the spirit of offering the experience to the radiation oncology communities in the Asia-Pacific region. The word “technical” is used to express the organisational components or processes and not the materials within the QA program. A comprehensive QA program in radiation oncology will have an official statement declaring the quality plan for effective patient care services it provides in a document. The QA program will include all aspects of patient care: physical, clinical, and medical aspects of the services. The document will describe the organisational structure, responsibilities, checks and procedures, and resources allocated to ensure the successful implementation of the quality of patient management. Regulatory guidelines and guidelines from accreditation agencies should be incorporated in the QA program to ensure compliance. The organisational structure will have a multidisciplinary QA committee that has the authority to evaluate continuously the effectiveness of the QA program to provide prompt corrective recommendations and to request feedback as needed to monitor the response. The continuous monitoring aspects require meetings to be held at regular intervals with the minutes of the meetings officially recorded and documented. To ensure that a QA program is effective, the program itself should be audited for quality at regular intervals at least annually. It has been recognised that the current QA program has not kept abreast with the rapid implementation of new and advanced radiation therapy technologies with the most recent in image-based radiation therapy technology. The societal bodies (ASTRO and AAPM) and federal agency (NCI) acknowledge this inadequacy and have held workshops to address this issue. The challenges for the societal bodies and federal agency are numerous that include (a) the prescriptive methodology used may not be appropriate for currently implemented new technologies, (b) resources are becoming scarce, (c) advanced radiation therapy technologies have been introduced too rapidly, (d) advances in radiation therapy technologies have become too sophisticated and specialised with each therapy modality having its own separate set of equipment, for example its own dose planning software, computer system and dose delivery systems requiring individualised QA procedures. At the present time, industrial engineers are being recruited to assist in devising a methodology that is broad-based and more process-oriented risk-based formulation of QA in radiation oncology.
PMCID: PMC3097727  PMID: 21611011
quality assurance; radiation therapy; treatment planning
20.  A multi-layered framework for disseminating knowledge for computer-based decision support 
There are several challenges in encoding guideline knowledge in a form that is portable to different clinical sites, including the heterogeneity of clinical decision support (CDS) tools, of patient data representations, and of workflows.
We have developed a multi-layered knowledge representation framework for structuring guideline recommendations for implementation in a variety of CDS contexts. In this framework, guideline recommendations are increasingly structured through four layers, successively transforming a narrative text recommendation into input for a CDS system. We have used this framework to implement rules for a CDS service based on three guidelines. We also conducted a preliminary evaluation, where we asked CDS experts at four institutions to rate the implementability of six recommendations from the three guidelines.
The experience in using the framework and the preliminary evaluation indicate that this approach has promise in creating structured knowledge, to implement in CDS systems, that is usable across organizations.
PMCID: PMC3241169  PMID: 22052898
Knowledge bases; Translational research - application of biological knowledge to clinical care; developing/using clinical decision support (other than diagnostic) and guideline systems; knowledge acquisition and knowledge management; clinical informatics; clinical decision support; semantic web; Manning Maddux; bioinformatics; datamining; predictive modeling; developing/using computerized provider order entry; knowledge representations; classical experimental and quasi-experimental study methods (lab and field); designing usable (responsive) resources and systems; statistical analysis of large datasets; visualization of data and knowledge; knowledge representations; knowledge acquisition and knowledge management; distributed systems; agents; software engineering: architecture; developing and refining ehr data standards (including image standards); data models; data exchange; controlled terminologies and vocabularies; communication and integration across care settings (inter- and intra-enterprise); knowledge bases; knowledge representations; uncertain reasoning and decision theory; designing usable (responsive) resources and systems; personal health records and self-care systems; knowledge acquisition and knowledge management; demonstrating return on it investment; other specific ehr applications (results review; medication administration; disease progression
21.  The SAGE Guideline Model: Achievements and Overview 
The SAGE (Standards-Based Active Guideline Environment) project was formed to create a methodology and infrastructure required to demonstrate integration of decision-support technology for guideline-based care in commercial clinical information systems. This paper describes the development and innovative features of the SAGE Guideline Model and reports our experience encoding four guidelines. Innovations include methods for integrating guideline-based decision support with clinical workflow and employment of enterprise order sets. Using SAGE, a clinician informatician can encode computable guideline content as recommendation sets using only standard terminologies and standards-based patient information models. The SAGE Model supports encoding large portions of guideline knowledge as re-usable declarative evidence statements and supports querying external knowledge sources.
PMCID: PMC1975799  PMID: 17600098
22.  Evaluation of User Interface and Workflow Design of a Bedside Nursing Clinical Decision Support System 
Clinical decision support systems (CDSS) are important tools to improve health care outcomes and reduce preventable medical adverse events. However, the effectiveness and success of CDSS depend on their implementation context and usability in complex health care settings. As a result, usability design and validation, especially in real world clinical settings, are crucial aspects of successful CDSS implementations.
Our objective was to develop a novel CDSS to help frontline nurses better manage critical symptom changes in hospitalized patients, hence reducing preventable failure to rescue cases. A robust user interface and implementation strategy that fit into existing workflows was key for the success of the CDSS.
Guided by a formal usability evaluation framework, UFuRT (user, function, representation, and task analysis), we developed a high-level specification of the product that captures key usability requirements and is flexible to implement. We interviewed users of the proposed CDSS to identify requirements, listed functions, and operations the system must perform. We then designed visual and workflow representations of the product to perform the operations. The user interface and workflow design were evaluated via heuristic and end user performance evaluation. The heuristic evaluation was done after the first prototype, and its results were incorporated into the product before the end user evaluation was conducted. First, we recruited 4 evaluators with strong domain expertise to study the initial prototype. Heuristic violations were coded and rated for severity. Second, after development of the system, we assembled a panel of nurses, consisting of 3 licensed vocational nurses and 7 registered nurses, to evaluate the user interface and workflow via simulated use cases. We recorded whether each session was successfully completed and its completion time. Each nurse was asked to use the National Aeronautics and Space Administration (NASA) Task Load Index to self-evaluate the amount of cognitive and physical burden associated with using the device.
A total of 83 heuristic violations were identified in the studies. The distribution of the heuristic violations and their average severity are reported. The nurse evaluators successfully completed all 30 sessions of the performance evaluations. All nurses were able to use the device after a single training session. On average, the nurses took 111 seconds (SD 30 seconds) to complete the simulated task. The NASA Task Load Index results indicated that the work overhead on the nurses was low. In fact, most of the burden measures were consistent with zero. The only potentially significant burden was temporal demand, which was consistent with the primary use case of the tool.
The evaluation has shown that our design was functional and met the requirements demanded by the nurses’ tight schedules and heavy workloads. The user interface embedded in the tool provided compelling utility to the nurse with minimal distraction.
PMCID: PMC3628119  PMID: 23612350
clinical decision support systems; user-computer interface; software design; human computer interaction; usability testing; heuristic evaluations; software performance; patient-centered care
23.  An implementation framework for GEM encoded guidelines. 
Access to timely decision support information is critical for delivery of high-quality medical care. Transformation of clinical knowledge that is originally expressed in the form of a guideline to a computable format is one of the main obstacles to the integration of knowledge sharing functionality into computerized clinical systems. The Guideline Element Model (GEM) provides a methodology for such a transformation. Although the model has been used to store heterogeneous guideline knowledge, it is important to demonstrate that GEM markup facilitates guideline implementation. This report demonstrates the feasibility of implementation of GEM-encoded guideline recommendations using Apache Group s Cocoon Web Publishing Framework. We further demonstrate how XML-based programming allows for maintaining the separation of guideline content from processing logic and from presentation format. Finally, we analyze whether the guideline authors original intent has been sufficiently captured and conveyed to the end user.
PMCID: PMC2243348  PMID: 11825181
24.  An intention-based language for representing clinical guidelines. 
Automated support for guideline-based care would be enhanced considerably by a standard representation of clinical guidelines. To faciliate use and reuse, we suggest a representation that includes the explicit intentions of the guideline's author. These intentions include the desirable actions of the care provider and the patient states to be achieved before, during, and after the administration of the guideline. Intentions are temporal patterns of provider actions or patient states to be maintained, achieved, or avoided. We view automated support as a collaborative effort of the health-care provider and an automated assistant and involves several different tasks. We defined the syntax and, the semantics of a text-based language (ASBRU) for representation and annotation of clinical guidelines. The language supports maintenance of the automated assistant's knowledge base and could improve the quality and flexibility of the automated assistant's recommendations. In the ASGAARD project, we are developing reasoning mechanisms that use the ASBRU language for execution and critiquing tasks in conjunction with online electronic patient medical records.
PMCID: PMC2233124  PMID: 8947735
25.  Extending the GuideLine Implementability Appraisal (GLIA) instrument to identify problems in control flow 
Clinical guidelines are usually written as text documents that are meant for human consumption. Implementing clinical guidelines as decision-support systems that deliver patient-specific advice at the point of care could increase the effectiveness of clinical guidelines. Several researchers studied the transition from narrative guidelines to computer-interpretable guidelines and have identified specific barriers to guideline implementation. GuideLine Implementability Appraisal (GLIA) is a comprehensive instrument for identifying such barriers, such that they could be revised. We used the GLIA instrument to appraise a historic thyroid nodule guideline that is now being reviewed by the American Association of Clinical Endocrinologists. Our analysis uncovered new guideline implementation barriers related to control-flow that we integrated into GLIA.
PMCID: PMC3041334  PMID: 21347054

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