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1 – 1 of 1Paule Poulin, Lea Austen, Catherine M. Scott, Cameron D. Waddell, Elijah Dixon, Michelle Poulin and René Lafrenière
When introducing new health technologies, decision makers must integrate research evidence with local operational management information to guide decisions about whether and under…
Abstract
Purpose
When introducing new health technologies, decision makers must integrate research evidence with local operational management information to guide decisions about whether and under what conditions the technology will be used. Multi‐criteria decision analysis can support the adoption or prioritization of health interventions by using criteria to explicitly articulate the health organization's needs, limitations, and values in addition to evaluating evidence for safety and effectiveness. This paper seeks to describe the development of a framework to create agreed‐upon criteria and decision tools to enhance a pre‐existing local health technology assessment (HTA) decision support program.
Design/methodology/approach
The authors compiled a list of published criteria from the literature, consulted with experts to refine the criteria list, and used a modified Delphi process with a group of key stakeholders to review, modify, and validate each criterion. In a workshop setting, the criteria were used to create decision tools.
Findings
A set of user‐validated criteria for new health technology evaluation and adoption was developed and integrated into the local HTA decision support program. Technology evaluation and decision guideline tools were created using these criteria to ensure that the decision process is systematic, consistent, and transparent.
Practical implications
This framework can be used by others to develop decision‐making criteria and tools to enhance similar technology adoption programs.
Originality/value
The development of clear, user‐validated criteria for evaluating new technologies adds a critical element to improve decision‐making on technology adoption, and the decision tools ensure consistency, transparency, and real‐world relevance.
Details