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An evidence-based framework for identifying technologies of no or low-added value (NLVT)

Published online by Cambridge University Press:  13 December 2019

María Eugenia Esandi
Affiliation:
Departamento de Economía, Universidad Nacional del Sur, Bahia Blanca, Argentina Instituto de Investigaciones Epidemiológicas de la Academia Nacional de Medicina de Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina
Iñaki Gutiérrez-Ibarluzea*
Affiliation:
Osteba, Ministry for Health, Basque Government, Vitoria-Gasteiz, Spain BIOEF, Basque Foundation for Health Innovation and Research, Barakaldo, Spain
Nora Ibargoyen-Roteta
Affiliation:
Osteba, Ministry for Health, Basque Government, Vitoria-Gasteiz, Spain
Brian Godman
Affiliation:
Strathclyde Institute of Pharmacy and Biomedical Sciences, Strathclyde University, Glasgow, UK Division of Clinical Pharmacology, Karolinska University Hospital Huddinge, Karolinska Institute, Stockholm, Sweden Department of Public Health and Pharmacy and Pharmacy Management, School of Pharmacy, Sefako Health Sciences University, Pretoria, South Africa
*
Author for correspondence: Iñaki Gutiérrez-Ibarluzea, E-mail: igutierrezibarluzea@bioef.org

Abstract

Objective

To synthetize the state of the art of methods for identifying candidate technologies for disinvestment and propose an evidence-based framework for executing this task.

Methods

An interpretative review was conducted. A systematic literature search was performed to identify secondary or tertiary research related to disinvestment initiatives and/or any type of research that specifically described one or more methods for identifying potential candidates technologies, services, or practices for disinvestment. An iterative and critical analysis of the methods described alongside the disinvestment initiatives was performed.

Results

Seventeen systematic reviews on disinvestment or related terms (health technology reassessment or medical reversal) were retrieved and methods of 45 disinvestment initiatives were compared. On the basis of this evidence, we proposed a new framework for identifying these technologies based on the wide definition of evidence provided by Lomas et al. The framework comprises seven basic approaches, eleven triggers and thirteen methods for applying these triggers, which were grouped in embedded and ad hoc methods.

Conclusions

Although identification methods have been described in the literature and tested in different contexts, the proliferation of terms and concepts used to describe this process creates considerable confusion. The proposed framework is a rigorous and flexible tool that could guide the implementation of strategies for identifying potential candidates for disinvestment.

Type
Method
Copyright
Copyright © Cambridge University Press 2019

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