Synthesizing quantitative and qualitative information on multiple comparisons of health interventions to facilitate knowledge transfer: an example from an EUnetHTA multi-HTA. (9th February 2022)

• Record Type: Journal Article
• Authors: Formoso, Giulio; Jeroncic, Ana; Bonvicini, Laura; Djuric, Olivera; Erdos, Judit; Pezzarossi, Annamaria; Ballini, Luciana
• Is Part Of: International journal of technology assessment in health care. Volume 38:Number 1(2022)
• Publication Date: 2022-02-09
• Subjects: Information synthesis -- Systematic reviews -- Knowledge transfer -- Multiple interventions -- Clinical relevance; Medical technology -- Periodicals; Technology assessment -- Periodicals; 610.28
• DOI: 10.1017/S0266462322000046
• Languages: English
• ISSNs: 0266-4623

Abstract

Abstract: Objective: Presenting an approach to synthesize quantitative and qualitative information from systematic reviews of multiple health interventions. Methods: Within the context of an EUnetHTA multi-health technology assessment of twenty-three surgical techniques, we developed synthetic single tables, using color gradients and abbreviations, with information on which technologies had been compared, estimates of the size of differences for available comparisons, their clinical relevance, and certainty of the related evidence. Results: The proposed methodology provided, through a single depiction, information normally included in multiple figures/tables such as network plots, league tables, and summary of findings tables. Conclusion: Transferring information on benefits, risks, and certainty of the available evidence on health interventions may be challenging, especially when assessing multiple treatments: more pieces of information need to be integrated in order to show an overall picture for each of the chosen outcomes, and usual reporting tools may be targeted to researchers more than to different kinds of decision makers. While more in-depth layers of information can always be added to satisfy needs of different audiences, the proposed tools could favor a quick interpretation of articulated scientific data by both decision makers and researchers.