Aims and strategy for the implementation of machine learning in evidence synthesis in the Cluster for Reviews and Health Technology Assessments for 2021-2022
Report
|Published
This report describes suggestions for a strategic approach to meeting the continued need for innovation, evaluation, and implementation of ML for health technology assessments, systematic reviews, and other evidence syntheses.
Key message
In 2020-2021, a team in the Cluster for Reviews and Health Technology Assessments, Division for Health Services at the Norwegian Institute of Public Health (NIPH) ran a project on machine learning (ML) related to the conduct of evidence syntheses. Part of the work involved creating a vision and proposals for expanding ML activities in 2021-2022.
This report describes the team’s suggestion for a strategic approach to meeting the continued need for innovation, evaluation, and implementation of ML for health technology assessments, systematic reviews, and other evidence syntheses. We propose a vision and goals, and a novel and flexible team structure. We divide activities into innovation, evaluation, and implementation, and present a risk assessment to inform the roll-out of a future team working on ML activities.
