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Model Formulation |
Affiliations of the authors: Yale Center for Medical Informatics, Yale University School of Medicine, New Haven, CT (RNS, GM, AE); Yale New Haven Hospital, New Haven, CT (ET)
Correspondence and reprints: Richard N. Shiffman, MD, MCIS, Yale Center for Medical Informatics, 300 George Street, Suite 501, New Haven, CT 06511; e-mail: <richard.shiffman{at}yale.edu>.
Received for publication: 08/22/03; accepted for publication: 05/03/04.
Objective: A gap exists between the information contained in published clinical practice guidelines and the knowledge and information that are necessary to implement them. This work describes a process to systematize and make explicit the translation of document-based knowledge into workflow-integrated clinical decision support systems.
Design: This approach uses the Guideline Elements Model (GEM) to represent the guideline knowledge. Implementation requires a number of steps to translate the knowledge contained in guideline text into a computable format and to integrate the information into clinical workflow. The steps include: (1) selection of a guideline and specific recommendations for implementation, (2) markup of the guideline text, (3) atomization, (4) deabstraction and (5) disambiguation of recommendation concepts, (6) verification of rule set completeness, (7) addition of explanations, (8) building executable statements, (9) specification of origins of decision variables and insertions of recommended actions, (10) definition of action types and selection of associated beneficial services, (11) choice of interface components, and (12) creation of requirement specification.
Results: The authors illustrate these component processes using examples drawn from recent experience translating recommendations from the National Heart, Lung, and Blood Institute's guideline on management of chronic asthma into a workflow-integrated decision support system that operates within the Logician electronic health record system.
Conclusion: Using the guideline document as a knowledge source promotes authentic translation of domain knowledge and reduces the overall complexity of the implementation task. From this framework, we believe that a better understanding of activities involved in guideline implementation will emerge.
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