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Computerized Clinical Practice Guidelines Systems Review

Two detailed reports about CPGs systems has been published in 2004 on JAMIA [A] and on Artificial Intelligence in Medicine [B]. I introduce the following systems:

  1. Asbru [1] is being collaboratively developed at Ben Gurion University and the Vienna University of Technology. It is a time-oriented, intention-based, skeletal-plan specification language that is used to represent clinical protocols [2]. Skeletal plans capture the essence of a procedure, but leave room for execution-time flexibility in the achievement of particular intentions. Asbru’s developers have enriched skeletal plans by (1) characterizing plan attributes such as intentions, conditions, and effects, (2) adding a rich set of ordering of plans, and (3) defining temporal dimensions of states and plans. Uncertainty in temporal scope and parameters can be expressed by bounding intervals.
  2. EON [3] was developed at Stanford University and provides a suite of models and software components for creating guideline-based applications. It views the guideline model as the core of an extensible set of models, such as a model for performing temporal abstractions. EON uses a task-based approach to define decision-support services that can be implemented using alternative techniques [4]. Its guideline execution server uses formalized clinical guidelines and patient data to generate situation-specific recommendations. A temporal data mediator supports queries involving temporal abstractions and temporal relationships. A third component provides explanation services for other components [5].
  3. GLIF [6] the Guideline Interchange Format version 3, has been collaboratively developed by groups at Columbia, Stanford and Harvard Universities (the InterMed Collaboratory). GLIF stresses the importance of sharing guidelines among different institutions and software systems. GLIF tries to build on the most useful features of other guideline models, and to incorporate standards that are used inhealth care. Its expression language was originally based on the Arden Syntax [7] and its default medical data model is based on the HL7 Reference Information Model (RIM) [8]. A subsequent object-oriented language, GELLO [9], is being refined for consideration as an HL7 standard.
  4. PRODIGY [10] was developed at the University of Newcastle upon Tyne. It provides support for chronic disease management in primary care. The PRODIGY project’s aim is to produce the simplest, most readily comprehensible model necessary to represent this class of guidelines. Teams of clinicians have used Protégé’s knowledge engineering environment [11] to encode three complex chronic –disease management guidelines. Over 150 guidelines encoded in PRODIGY’s simpler Release One model have been translated into the current model. Two vendors have integrated identical PRODIGY components into their clinical information systems for general practitioners [12].
  5. PROforma [13] was developed at the Advanced Computation Laboratory of Cancer Research, UK. It combines logic programming and object-oriented modeling and is formally grounded in the R2L Language [14]. One aim of the PROforma project is to explore the expressiveness of a deliberately minimal set of modeling constructs. PROforma supports four task types: actions, compound plans, decisions, and enquiries. All types share attributes describing goals, control flow, preconditions, and post-conditions. The simple task ontology should make it easier to demonstrate soundness and to teach the language to encoders.
  6. GASTON [15, 16] was developed by a joint effort of the Department of medical Informatics of Maastricht University and the Signal Processing Systems group of the Eindhoven University of Technology. The guideline representation formalism uses a frame-based model as an underlying mechanism. The formalism is non-monolithic, meaning that it can be extended with additional classes to capture new guideline characteristics. Similar to the GLIF, EON and Guide approaches, the Gaston guideline authoring environment represents and visualizes guidelines by temporally sequenced graphs (flowcharts) of frame instances from the guideline model.
  7. GLARE [17] was developed by the Dipartimento di Informatica, Università del Piemonte Orientale "Amedeo Avogadro", Alessandria, Italy, in co-operation with the Laboratorio di Informatica Clinica, Azienda Ospedaliera S. Giovanni Battista, Torino, Italy. The formalism consists of a limited, but very focused and clearly understandable set of primitives. It is made up of different types of actions: plans (i.e. composite actions, hierarchically decomposable in their sub-actions) and atomic actions. Atomic actions can be queries, decisions, work actions and conclusions. All actions are linked by control relations (e.g. sequence, alternative, repetition), defining their order of execution.
  8. SAGE & Guide will be introduced later on as both enable the integration with the workflow of care process.

Updated news about methods and tools to support the computerization of clinical practice guidelines are constantly published by OpenClinical. OpenClinical website (www.openclinical.org) provides an increasingly comprehensive set of resources on advanced knowledge management methods, technologies and applications for healthcare (methods and tools for representing computerised clinical guidelines). It is a non-profit organisation co-ordinated by an international group from leading research and teaching organisations.

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References

[A] Peleg M, Tu S, Bury J, Ciccarese P. et al.
Comparing models of decision and action for guideline-based decision support: a case-study approach.
JAMIA 2003; vol. 1 ,n.10, 52-68

[B] Clercq, P.A. de; Blom, J.A.; Korsten, H.H.M.; Hasman, A.
Approaches for creating computer-interpretable guidelines that facilitate decision support.
Art. Intell. Med. 31, nr. 1, 2004, pp. 1-27. SPS-40 [06.01]

[1] Shahar, Y., Miksch, S., and Johnson, P.
The Asgaard project: A task-specific framework for the application and critiquing of time-oriented clinical guidelines.
Artificial Intelligence in Medicine (14): 29-51, 1998.

[2] Seyfang A, Kosara R, Miksch S.
Asbru's Reference Manual, Version 7.3
Vienna University of Technology, Institute of SoftwareTechnology, Vienna; 2002. Report No.: Asgaard-TR-2002-1.

[3] Tu SW, Musen MA.
A Flexible Approach to Guideline Modeling.
Proc AMIA Symp. 1999:420-424.

[4] Tu SW, Musen MA.
From Guideline Modeling to Guideline Execution: Defining Guideline-Based Decision-Support Services.
Proc AMIA Annu Symp. 2000:863-867.

[5] Tu SW, Musen MA.
Modeling Data and Knowledge in the EON Guideline Architecture.
Proc Medinfo: 280-284.

[6] Peleg M, Boxwala A, Ogunyemi O, et al.
GLIF3: The Evolution of a Guideline Representation Format.
Proc AMIA Annu Fall Symp. 2000:645-649.

[7] Hripcsak G, Ludemann P, Pryor TA, Wigertz OB, Clayton PD.
Rationale for the Arden Syntax.
Comput Biomed Res. 1994;27(4):291-324.

[8] Schadow G, Russler DC, Mead CN, McDonald CJ.
Integrating Medical Information and Knowledge in the HL7 RIM.
Proc AMIA Annu Fall Symp. 2000:764-768.

[9] Ogunyemi O, Zeng Q, Boxwala A.
Object-oriented guideline expression language (GELLO) specification
Brigham and Women's Hospital, Harvard Medical School, 2002. Decision Systems Group Technical Report DSG-TR-2002-001.

[10] Johnson PD, Tu SW, Booth N, Sugden B, Purves IN.
Using Scenarios in Chronic Disease Management Guidelines for Primary Care.
Proc AMIA Annu Fall Symp. 2000:389-393.

[11] Grosso WE, Eriksson H, Fergerson R, Gennari JH, Tu SW, Musen MA.
Knowledge Modeling at the Millennium (The Design and Evolution of Protege-2000).
Proc 12th Banff Knowledge Acquisition for Knowledge-Based Systems Workshop. Canada; 1999:7-4-1 to 7-4-36.

[12] Johnson P, Tu S, Jones N.
Achieving reuse of computable guideline systems.
Medinfo. 2001;10(Pt 1):99-103.

[13] Fox J, Johns N, Rahmanzadeh A, Thomson R.
PROforma: A method and language for specifying clinical guidelines and protocols.
Proc Medical Informatics Europe; Amsterdam; 1996.

[14] Fox J, Das S.
Safe and Sound.
In: Safe and Sound: AAAI Press; 2000.<(p>

[15] De Clercq PA, Blom JA, Hasman A, Korsten HHM.
Design and implementation of a framework to support the development of clinical guidelines.
Int J Med Inf 2001;64(2- 3):285-318.

[16] De Clercq PA, Blom JA, Hasman A, Korsten HH.
GASTON: an architecture for the acquisition and execution of clinical guideline-application tasks.
Med Inform Internet Med. 2000 Oct-Dec;25(4):247-63.<(p>

[17] Terenziani P, Mastromonaco F, Molino G, Torchio M.
Executing clinical guidelines: temporal issues.
Proc AMIA Symp. 2000;:848-52.