Creating interoperable guidelines: requirements of vocabulary standards in immunization decision support.

Interoperable support of electronic health records and clinical decision support technology are central to the vision of sustainable information infrastructure. Efforts to implement interoperable clinical guidelines for immunization practice have been sparse. We used the SAGE knowledge workbench to develop a knowledge base to provide immunization decision support in primary care. We translated the written clinical guideline into a structured decision logic format. The semantic content to completely capture CDC clinical decision logic required 197 separate concepts but was completely captured with SNOMED CT and LOINC. Although 88% of concepts employed precoordinated codes, 6% of guideline concepts required expanded vocabulary services employing Boolean logical definition using two or more SNOMED concepts. Postcoordination requirements were modest, representing just 6% of guideline semantic concepts. We conclude that creation of interoperable knowledge bases employing clinical vocabulary standards is achievable and realistic. Employment of information model (HL7 RIM) and vocabulary (SNOMED CT, LOINC) standards is a necessary and feasible requirement to achieve interoperability in clinical decision support.

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.

Structuring order sets for interoperable distribution.

A major portion of patient care planning occurs during the process of writing orders. Computerized order entry can present collections of predefined orders to the user during the ordering process. These order sets are useful for promoting standards of care, and provide one element of structured clinical knowledge to be used by Computerized Provider Order Entry (CPOE) systems at the point of care. Since the creation, confirmation and maintenance of order sets is resource intensive, sharing order sets is a useful goal. We describe a standard representation of order sets that supports maintenance, sharing and interoperation of pre-defined order sets. A dialogue within the HL7 community seeks to harmonize this proposal with the Clinical Document Architecture and the HL7 Reference Information Model.

Use of declarative statements in creating and maintaining computer-interpretable knowledge bases for guideline-based care.

Developing computer-interpretable clinical practice guidelines (CPGs) to provide decision support for guideline-based care is an extremely labor-intensive task. In the EON/ATHENA and SAGE projects, we formulated substantial portions of CPGs as computable statements that express declarative relationships between patient conditions and possible interventions. We developed query and expression languages that allow a decision-support system (DSS) to evaluate these statements in specific patient situations. A DSS can use these guideline statements in multiple ways, including: (1) as inputs for determining preferred alternatives in decision-making, and (2) as a way to provide targeted commentaries in the clinical information system. The use of these declarative statements significantly reduces the modeling expertise and effort required to create and maintain computer-interpretable knowledge bases for decision-support purpose. We discuss possible implications for sharing of such knowledge bases.

Modeling guidelines for integration into clinical workflow.

The success of clinical decision-support systems requires that they are seamlessly integrated into clinical workflow. In the SAGE project, which aims to create the technological infra-structure for implementing computable clinical practice guide-lines in enterprise settings, we created a deployment-driven methodology for developing guideline knowledge bases. It involves (1) identification of usage scenarios of guideline-based care in clinical workflow, (2) distillation and disambiguation of guideline knowledge relevant to these usage scenarios, (3) formalization of data elements and vocabulary used in the guideline, and (4) encoding of usage scenarios and guideline knowledge using an executable guideline model. This methodology makes explicit the points in the care process where guideline-based decision aids are appropriate and the roles of clinicians for whom the guideline-based assistance is intended. We have evaluated the methodology by simulating the deployment of an immunization guideline in a real clinical information system and by reconstructing the workflow context of a deployed decision-support system for guideline-based care. We discuss the implication of deployment-driven guideline encoding for sharability of executable guidelines.