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Methods and tools to support the computerisation of clinical practice guidelines: a short introduction.

motivation
In a paper commissioned by OpenClinical in 2002, Yuval Shahar describes the need for guideline-based decision support tools as part of a fully integrated healthcare information system infrastructure:
"There is a clear need for effective guideline-support tools at the point of care and at the point of critiquing, which will relieve the current information overload on both care providers and administrators. To be effective, these tools need to be grounded in the patient's record, must use standard medical vocabularies, should have clear semantics, must facilitate knowledge maintenance and sharing, and need to be sufficiently expressive to explicitly capture the design rational (process and outcome intentions) of the guideline's author, while leaving flexibility at application time to the attending physician and their own preferred methods" [Shahar, 2002].
methods for specifying electronic guidelines
A number of methods to support the computerisation of guidelines have been or are being developed by the Health Informatics community. Guideline-based decision support systems aim to enable the latest clinical knowledge to be accessible and usable at the point of care and so make significant contributions to quality and safety in healthcare.

A number of these methods are based on guideline models which are capable of formalising medical knowledge as electronic applications that can be executed (or enacted) to generate patient-specific recommendations for clinical decisions and actions. Such methods employ different representation formalisms and computational techniques, for example:

A study, co-ordinated by Mor Peleg of Haifa University and Samson Tu of Stanford University, was carried out in 2002 to compare six computer-interpretable guideline models (Asbru, EON, GLIF, GUIDE, PRODIGY and PROforma). Full details of the paper, published in JAMIA in 2002, can be found in this section.

Other current methods for representing clinical knowledge take a different approach by structuring guidelines on the basis of XML guideline document models. Methods in this category include GEM, Stepper and HGML.

The DeGeL (Digital electronic Guideline Library) infrastructure of methods and tools represents a hybrid approach: it is capable of supporting both markup and formal, executable methods of representating clinical guidelines.

This section of OpenClinical aims to provide information on all methods and tools designed to support the specification of electronic clinical guideline applications for use in healthcare.


references

Mor Peleg. Guideline and Workflow Models. In: Medical Decision-Making: Computational Approaches to Achieving Healthcare Quality and Safety, Robert A. Greenes (ed.), Elsevier/Academic Press, 2006.

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" Clinical guidelines aim to improve quality of care, decrease unjustified practice variations, and save costs. In order for guidelines to affect clinicians' behavior, they should provide patient-specific decision support during patient encounters. Specifying guidelines in computer-interpretable guideline (CIG) formalisms that could provide automatic inference based on patient data may achieve this goal. The knowledge contained in guidelines is difficult to formalize due to the fact that despite efforts made to improve the quality of narrative guidelines, evidence-based recommendations are often incomplete and vague, and do not constitute a full care process. Several methodologies have been developed to support the transition from narrative guidelines into CIG implementations. They include (1) methodologies for marking-up narrative guideline elements in order to assess a guideline's quality and completeness and map it to CIG formalisms and (2) CIG formalisms. Many CIG formalisms exist, differing in their goals, computation model, the elements used to structure guideline knowledge, and the degree to which they support workflow integration. Specifying a narrative guideline as a CIG is a difficult task, yet the resulting application cannot be easily shared by different institutions and software systems. Therefore, sharing encoded knowledge is a challenging goal. The specification of standard methods to support such sharing is a major focus in the field. The road to achieving wide-spread use of guideline-based decision-support systems is long and difficult. This chapter reviews the current state-of-the-art in guideline-based decision support research and considers likely future directions that can be taken to reach the ultimate goal. "

Mulyar N, van der Aalst WM, Peleg M. A Pattern-based Analysis of Clinical Computer-Interpretable Guideline Modeling Languages. J Am Med Inform Assoc. 2007 Aug 21;

[PubMed]   []

" OBJECTIVE Languages used to specify computer interpretable guidelines (CIGs) differ in their approaches to addressing particular modeling challenges. The main goals of this paper are: 1) to examine the expressive power of CIG modeling languages; and 2) to define the differences, from the control-flow perspective, between process languages in workflow management systems and modeling languages used to design clinical guidelines. DESIGN The pattern-based analysis was applied to guideline modeling languages Asbru, EON, GLIF, and PROforma. We focused on control-flow and left other perspectives out of consideration. MEASUREMENTS We evaluated the selected CIG modeling languages and identified their degree of support of 43 control-flow patterns. We used a set of explicitly defined evaluation criteria to determine whether each pattern is supported directly, indirectly or not at all. RESULTS PROforma offers direct support for 22 of 43 patterns, Asbru 20, GLIF 17, and EON 11. All four directly support. Basic Control-flow patterns, Cancellation patterns, and some Advance Branching and Synchronization patterns. None support Multiple Instances patterns. They offer varying levels of support for Synchronizing Merge patterns and State-based patterns. Some support a few scenarios not covered by the 43 control-flow patterns. CONCLUSION CIG modeling languages are remarkably close to traditional workflow languages from the control-flow perspective, but cover many fewer workflow patterns. CIG languages offer some flexibility that supports modeling of complex decisions and provide ways for modeling some decisions not covered by workflow management systems. Workflow management systems may be suitable for clinical guideline applications. "

Peleg M, Tu S, Bury J, Ciccarese P, Fox J, Greenes RA, Hall R, Johnson PD, Jones N, Kumar A, Miksch S, Quaglini S, Seyfang A, Shortliffe EH, Stefanelli M. Comparing computer-interpretable guideline models: a case-study approach. J Am Med Inform Assoc. 2003 Jan-Feb;10(1):52-68.

[PubMed]    [PubMed Central]

[Supplementary documentation on OC]

" OBJECTIVES: Many groups are developing computer-interpretable clinical guidelines (CIGs) for use during clinical encounters. CIGs use "Task-Network Models" for representation but differ in their approaches to addressing particular modeling challenges. We have studied similarities and differences between CIGs in order to identify issues that must be resolved before a consensus on a set of common components can be developed. DESIGN: We compared six models: Asbru, EON, GLIF, GUIDE, PRODIGY, and PROforma. Collaborators from groups that created these models represented, in their own formalisms, portions of two guidelines: the American College of Physicians-American Society of Internal Medicine's guideline for managing chronic cough and the Sixth Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. MEASUREMENTS: We compared the models according to eight components that capture the structure of CIGs. The components enable modelers to encode guidelines as plans that organize decision and action tasks in networks. They also enable the encoded guidelines to be linked with patient data-a key requirement for enabling patient-specific decision support. RESULTS: We found consensus on many components, including plan organization, expression language, conceptual medical record model, medical concept model, and data abstractions. Differences were most apparent in underlying decision models, goal representation, use of scenarios, and structured medical actions. CONCLUSION: We identified guideline components that the CIG community could adopt as standards. Some of the participants are pursuing standardization of these components under the auspices of HL7. "

de Clercq PA, Blom JA, Korsten HH, Hasman A. Approaches for creating computer-interpretable guidelines that facilitate decision support. Artif Intell Med. 2004 May;31(1):1-27.

[PubMed]   [ScienceDirect]

" During the last decade, studies have shown the benefits of using clinical guidelines in the practice of medicine. Although the importance of these guidelines is widely recognized, health care organizations typically pay more attention to guideline development than to guideline implementation for routine use in daily care. However, studies have shown that clinicians are often not familiar with written guidelines and do not apply them appropriately during the actual care process. Implementing guidelines in computer-based decision support systems promises to improve the acceptance and application of guidelines in daily practice because the actions and observations of health care workers are monitored and advice is generated whenever a guideline is not followed. Such implementations are increasingly applied in diverse areas such as policy development, utilization management, education, clinical trials, and workflow facilitation. Many parties are developing computer-based guidelines as well as decision support systems that incorporate these guidelines. This paper reviews generic approaches for developing and implementing computer-based guidelines that facilitate decision support. It addresses guideline representation, acquisition, verification and execution aspects. The paper describes five approaches (the Arden Syntax, GuideLine Interchange Format (GLIF), PROforma, Asbru and EON), after the approaches are compared and discussed. "

Wang D, Peleg M, Tu SW, Boxwala AA, Greenes RA, Patel VL, Shortliffe EH. Representation primitives, process models and patient data in computer-interpretable clinical practice guidelines: a literature review of guideline representation models. Int J Med Inform. 2002.

[SMI ]
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"Representation of clinical practice guidelines in a computer interpretable format is a critical issue for guideline development, implementation and evaluation. We studied eleven types of guideline representation models that can be used to encode guidelines in computer- interpretable formats. We have consistently found in all reviewed models that primitives for representation of actions and decisions are necessary components of a guideline representation model. Patient states and execution states are important concepts that closely relate to each other. Scheduling constraints on representation primitives can be modeled as sequences, concurrences, alternatives, and loops in a guideline’s application process. Nesting of guidelines provides multiple views to a guideline with different granularities. Integration of guidelines with electronic medical records can be facilitated by the introduction of a formal model for patient data. Data collection, decision, patient state, and intervention constitute four basic types of primitives in a guideline’s logic flow. Decisions clarify our understanding on a patient’s clinical state, while interventions lead to the change from one patient state to another."
Greenes RA, Peleg M, Boxwala A, Tu S, Patel V, Shortliffe EH. Sharable computer-based clinical practice guidelines: rationale, obstacles, approaches, and prospects. Medinfo 2001;10(Pt 1):201-5.

[PubMed]
[Abstract - SMI] [Paper - SMI]

" Clinical practice guideline automation at the point of care is of growing interest, yet most guidelines are authored in unstructured narrative form. Computer-based execution depends on a formal structured representation, and also faces a number of other challenges at all stages of the guideline lifecycle: modeling, authoring, dissemination, implementation, and update. This is because of the multiplicity of conceptual models, authoring tools, authoring approaches, intended applications, implementation platforms, and local interface requirements and operational constraints. Complexity and time required for development and structure are also huge obstacles. These factors argue for convergence on a common shared model for representation that can be the basis of dissemination. A common model would facilitate direct interpretation or mapping to multiple implementation environments. GLIF (GuideLine Interchange Format) is a formal representation model for guidelines, created by the InterMed Collaboratory as a proposed basis for a shared representation. GLIF currently addresses the process of authoring and dissemination; the InterMed team's major focus now is on tools to facilitate these tasks and the mapping to clinical information system environments. Because of limitations in what can be done by a single team with finite resources, however, and the variety of additional perspectives that need to be accommodated, the InterMed team has determined that further development of a shared representation would be best served as an open process in which the world community is engaged. Under the auspices of the HL7 Decision Support Technical Committee, a GLIF Special Interest Group has been established, which is intended to be a forum for collaborative refinement and extension of a standard representation that can support the needs of the guideline lifecycle. Significant areas for future work will need to include demonstrations of effective means for incorporating guide-lines at point of care, reconciliation of functional requirements of different models and identification of those most important for supporting practical implementation, im-proved means for authoring and management of complexity, and methods for automatically analyzing and validating syntax, semantics, and logical consistency of guidelines. "
S. W. Tu & M. A. Musen. Representation Formalisms and Computational Methods for Modeling Guideline-Based Patient Care. First European Workshop on Computer-based Support for Clinical Guidelines and Protocols, Leipzig, Germany, 125-142. 2000.

[SMI]    []

" This paper (1) presents a set of patient-care tasks for which a computer-interpretable representation of clinical practice guideline and protocols can provide assistance, (2) surveys the formalisms and computational methods that have been proposed in relation to these tasks, and (3) describes a multi-method paradigm that we have been developing in the EON project to support these patient-care tasks. "
D. A. Wang, M. Peleg, S. Tu, E. H. Shortliffe, & R. A. Greenes Representation of Clinical Practice Guidelines For Computer-based Implementations Medinfo, London, UK, 2001.

[SMI]   []

" Representation of clinical practice guidelines is a critical issue for computer-based guideline development, implementation and evaluation. We studied eight types of computer-based guideline models. Typical primitives for these models include decisions, actions, patient states and execution states. We also find temporal constraints and nesting to be important aspects of guideline structure representation. Integration of guidelines with electronic medical records is facilitated by the introduction of formal models of patient data. Patient states and execution states are closely related to one another. Interrelationship among data collection, decisions, patient states and interventions in a guideline's logic flow varies in different guideline representation models. "
P Elkin, M Peleg, R Lacson et al. Toward Standardization of Electronic Guidelines. MD Computing, Vol. 17, No. 6, 2000, pp. 39-44.

[SMI]    []

" We describe approaches to electronic guideline representation and classify them into 3 groups: rule-based, decision analysis, markup, and multi-step guidelines modeled as a hierarchical set of nested guideline tasks. We also describe the relationships and influences among the various representation methods and present current trends and future directions in the field of electronic guideline representation. "

Tu SW, Campbell J, Musen MA. The structure of guideline recommendations: a synthesis. AMIA Annu Symp Proc. 2003;:679-83.

[PubMed]   [PubMed Central]

" We propose that recommendations in a clinical guideline can be structured either as collections of decisions that are to be applied in specific situations or as processes that specify activities that take place over time. We formalize them as "recommendation sets" consisting of either Activity Graphs that represent guideline-directed processes or Decision Maps that represent atemporal recommendations or recommendations involving decisions made at one time point. We model guideline processes as specializations of workflow processes and provide possible computational models for decision maps. We evaluate the proposed formalism by showing how various guideline-modeling methodologies, including GLIF, EON, PRODIGY3, and Medical Logic Modules can be mapped into the proposed structures. The generality of the formalism makes it a candidate for standardizing the structure of recommendations for computer-interpretable guidelines. "

references: standards and computer-interpretable guidelines

Biondich PG, Downs SM, Carroll AE, Shiffman RN, McDonald CJ. Collaboration between the medical informatics community and guideline authors: fostering HIT standard development that matters. AMIA Annu Symp Proc. 2006;:36-40.

[PubMed]   [PubMed Central]

" Clinical guideline authors, health information technology (HIT) standards development organizations, and information system implementers all work to improve the processes of healthcare, but have long functioned independently towards realizing these goals. This has led to clinical standards of care that often poorly align with the functional and technical HIT standards developed to realize them.We describe the shortcomings and inefficiencies inherent in this current process and introduce two national initiatives that attempt to unite these communities. The mission of these two initiatives is to create examples of unambiguous, decidable, and executable clinical guidelines which both utilize and inform HIT terminology and logical expression standards. All of the products of this work aim to facilitate enterprise-wide guideline implementation and create a rising tide which lifts all ships. "

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page history
Entry on OpenClinical: 2002
Last main update: 29 August 2005
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