Machine Learning-Assisted Health Economics and Policy Reviews: A Comparative Assessment.

Journal: Applied health economics and health policy
Published Date: Mar 28, 2025

Abstract

INTRODUCTION: The growth of scientific literature in health economics and policy represents a challenge for researchers conducting literature reviews. This study explores the adoption of a machine learning (ML) tool to enhance title and abstract screening. By retrospectively assessing its performance against the manual screening of a recent scoping review, we aimed to evaluate its reliability and potential for streamlining future reviews.

Authors

  • Ludovico Cavallaro
    Center for Research on Health and Social Care Management (CERGAS), SDA Bocconi School of Management, Via Sarfatti, 10, 20136, Milan, MI, Italy.
  • Vittoria Ardito
    Center for Research on Health and Social Care Management (CERGAS), SDA Bocconi School of Management, Milan, Italy.
  • Michael Drummond
    Center for Research on Health and Social Care Management (CERGAS), SDA Bocconi School of Management, Via Sarfatti, 10, 20136, Milan, MI, Italy.
  • Oriana Ciani
    Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Porto, Portugal.

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