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PP145 Using Health Technology Assessment To Drive Guideline Development

Published online by Cambridge University Press:  03 January 2019

Abstract

Introduction:

Clinical practice guidelines (CPGs) are a key vehicle for converting evidence into action. CPGs can be produced by various methods: de novo, adaptation, adoption, or a combination of these. Deciding whether and how to develop a guideline can be challenging. Health technology assessment (HTA) researchers from the Institute of Health Economics developed a multi-step decisional algorithm highlighting the decision nodes in the initial phase of guideline development where HTA products and expertise can be valuable in demystifying these decisions.

Methods:

A literature search was conducted for articles comparing methods of developing CPGs, with particular focus on finding a priori criteria for deciding when to use one method versus another.

Results:

The published literature is sparse and there are no specific criteria available for deciding when to use one method of development versus another. The proposed multi-step algorithm identifies similar steps in the production of all types of CPGs: the set-up phase; establishing the need for a new CPG in consultation with a guideline development group and local stakeholders; developing research question(s); conducting searches for suitable existing guidelines; and finalizing the guideline. HTA can help set the health question(s) and identify and screen existing CPGs. When CPGs are not available, HTA methods are implemented to update the evidence in a blend of de novo and adaptation processes by reviewing umbrella reviews, systematic reviews, and primary studies. Quality appraisal of existing guidelines and syntheses of evidence in a rapid review fashion help determine whether there are enough studies to support the guideline scope.

Conclusions:

Deciding which method of guideline development to employ requires ample methodological expertise, an intimate knowledge of the clinical practice environment, and access to detailed contextual information. The proposed multi-step algorithm shows how to successfully leverage HTA resources to support CPG production and move research evidence into practice.

Type
Poster Presentations
Copyright
Copyright © Cambridge University Press 2018 

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