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SAGE Objectives and Approach SAGE Technology and Progress Clinical Practice Guidelines Useful Links


 

SAGE Guideline Model Attributes

  • Sufficient to encode guideline knowledge needed to provide situation-specific decision support and to maintain linked explanatory resource information for the end-user

  • Uses standardized components that allow interoperability of guideline execution elements with the standard services provided within vendor clinical information systems


  • Includes organizational knowledge to capture workflow information and resources needed to provide decision-support in enterprise setting


  • Is sufficiently well structured so that the bulk of guideline knowledge can be encoded, through a guideline workbench, by clinicians with basic understanding of the guideline model


SAGE Guideline Model Architecture

The SAGE Guideline Model will contain various attributes that will work together to produce an effective means for encoding medical guidelines:

Recommendation Sets - A subset of guideline content tailored to the workflow, roles, entities and actions within a specific healthcare enterprise. When encoding the guideline for SAGE, an enterprise team of clinical experts must interpret the guideline statements and create one or more plans that will support the guideline goals in the specific work environment of their health care organization. To achieve this, the recommendation set employs four "nodes": Context, Decision, Action, and Route.

1. Context Node- Specifies and declares the assumptions made about the health care enterprise work model that are otherwise implicit in every instance of a guideline implementation; their defining attributes specify their trigger events, clinical setting, and patient state. For example, a context node can specify that a physician in an emergency department triggers the guideline interaction by beginning an order entry session and identifying the diagnosis as acute neurological deficit.

2. Action Node- Models one or more information system activities employed in support of a recommendation set; they can include support for messaging to system devices like Inbox reminders or workstation reminders.

3. Decision Node
- Describes the acquisition of some data (directly from the patient EMR or interactively by asking
the clinician) and the employment of a decision model to evaluate branching logic.

4. Routing Node
- Synchronizes multiple activity paths.

The graphic above represents a sample recommendation set based on the guideline from the Institute for Clinical Systems Improvement (ICSI) for triage and treatment of acute ischemic stroke. This guideline focuses upon rapid evaluation of the patient with acute neurologic deficit, a search for contra-indications to tissue plasminogen activator (tPA), and administration of tPA to selected eligible patients.

The recommendation set consists of two sessions (set of one or more interactions between user and SAGE/CIS symbiote). Context Node 1 specifies the context of an emergency department physician triage examination, while Context Node 2 depicts the inpatient physician daily order sessions in the treatment of the stroke. More specifically, Context Node 1 specifies that a physician in the Emergency Department (ED) triggers the guideline interaction by beginning an order entry session and identifying the diagnosis as acute neurologic deficit. Node 2 is triggered as the inpatient physician initiates daily order sessions for management of the patient admitted with a stroke diagnosis.

Action Nodes 1 - 3 model the use of order sets to be employed in the stroke protocol. In the example above Action Node 1 is a protocol order set for rapid evaluation in the emergency department. Action Nodes 2 and 3 contain order set specifications for stroke admission orders in the setting of treatment without and with tPA, respectively. Since all context, action and decision nodes may have associated scheduling constraints, the execution sequence may be interrupted, with explicit time management, as in the successive delivery of Day 1 and Day 2 order sets in this example.

In Decision Node 1, a user decision that the patient does not have a stroke leads to exit from the guideline scenario. In Decision Node 2, assessment of tPA contraindications determines whether the patient is eligible for tPA. Each decision node, in addition to scheduling features, has two or more concluding states and a bound decision model which may employ an argumentation structure, a neural or Bayesian network, or other methods determined by the needs of the guideline.

The Routing Node in the example above is where the two care plans merge ("with" or "without tPA"), and both of the activity paths are synchronized to the stage where the patient can be discharged.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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