ABSTRACT
Objectives: Because existing publication guidelines and checklists have limitations when used to assess the quality of cost-effectiveness analysis, we developed a novel quality assessment tool for cost-effectiveness analyses, differentiating methods and reporting quality and incorporating the relative importance of different quality attributes.
Methods: We defined 15 quality domains from a scoping review and identified 72 methods and reporting quality attributes (36 each). After designing a best-worst scaling survey, we fielded an online survey to researchers and practitioners to estimate the relative importance of the attributes in February 2021. We analyzed the survey data using a sequential conditional logit model. The final tool included 48 quality attributes deemed most important for assessing methods and reporting quality (24 each), accompanied by a free and web-based scoring system.
Results: A total of 524 participants completed the methodology section, and 372 completed both methodology and reporting sections. Quality attributes pertaining to the "modeling" and "data inputs and evidence synthesis" domains were deemed most important for methods quality, including "structure of the model reflects the underlying condition and intervention's impact" and "model validation is conducted." Quality attributes pertaining to "modeling" and "Intervention/comparator(s)" domains were considered most important for reporting quality, including "model descriptions are detailed enough for replication." Despite its growing prominence, "equity considerations" were not deemed as important as other quality attributes.
Conclusions: The Criteria for Health Economic Quality Evaluation tool allows users to differentiate methods and reporting as well as quantifies the relative importance of quality attributes. Alongside other considerations, it could help assess and improve the quality of cost-effectiveness evidence to inform value-based decisions.
Keywords: cost-effectiveness; economic evaluations; evidence; priority setting; quality assessment.