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PP108 Novel Approaches For Fair And Reasonable Value-Based Recommendations

Published online by Cambridge University Press:  03 January 2019

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Abstract

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Introduction:

Stakeholders from the innovation field in Québec (Canada) have collectively stressed the need to formalize the process for evaluating innovative technologies in the province. In the context of innovation, and more so for non-pharmaceutical technologies where the pace of development is rapid and the lifecycle short, evidence supporting the added value can be limited and uncertainties are common. Therefore, pragmatic approaches are needed to guide recommendations and to assure that the process is rigorous, transparent and fair.

Methods:

Inspired by international experiences, the Institut national d'excellence en santé et services sociaux (INESSS) has developed a novel framework, where four types of recommendations are possible (introduction, refusal, limited or conditional introduction). The starting point is an evaluation of the technology's added value, for the patient, the population and the healthcare system, and the identification of uncertainties. The value of addressing uncertainty with further research is assessed, based on the value-of-information theory, and the distinct characteristics of medical devices are taken into account (e.g. learning curve effect, irrecoverable costs and incremental innovation). Those elements interact to support the formulation of recommendations by INESSS’ advisory committee.

Results:

The development of the framework was an iterative process supported by the use of the preliminary framework for the assessment of several innovative technologies. Challenges with its use were identified, and led to methodological and operational improvements. So far, the experience with the framework is positive and stakeholders confirm its relevance to support fair and reasonable recommendations for innovations.

Conclusions:

In the rapidly changing landscape of innovation, HTA has to adapt to the challenges of assessing technologies in a context of promise and uncertainties. The framework developed by INESSS is a tool for supporting timely and fair value-based decision-making, which will benefit the healthcare system, and the patients and population it serves.

Type
Poster Presentations
Copyright
Copyright © Cambridge University Press 2018