Beyond Narrative and Tabular Synthesis: Introducing an Approach–Rationale–Note (ARN) Framework for Thematic Evidence Synthesis in Economic Evaluation Reviews

BACKGROUND: Conventional evidence synthesis in systematic literature reviews (SLRs) of economic evaluations typically provides a narrative description of modelling approaches used across studies and rarely examines the underlying rationale for these choices or their interpretation. This study develops and applies a thematic synthesis approach to analyse modelling decisions reported in economic evaluations. OBJECTIVE: The aim of this study was to introduce and apply an Approach-Rationale-Note (ARN) framework for thematic evidence synthesis in economic evaluation SLRs and demonstrate its application using economic evaluations of treatments for spinal muscular atrophy (SMA). METHODS: Evidence from a previously conducted SLR of economic evaluations of SMA treatments was synthesised using a deductive thematic approach. The ARN framework structured the analysis by distinguishing modelling approaches, their rationales, and contextual observations relevant to interpretation. Analytical domains and dimensions were developed iteratively to enable comparison of modelling decisions across studies, with their selection guided by the review question and the methodological issues identified in the evidence base. RESULTS: Substantial variation in modelling approaches was observed across key ARN domains, including model structure, health state definitions, treatment effect assumptions, extrapolation methods, and the handling of uncertainty. While several studies adopted similar modelling approaches, the rationales provided for these choices varied considerably. Health technology assessment (HTA) sources frequently highlighted uncertainty related to long-term outcomes, treatment durability, and survival extrapolation. CONCLUSIONS: A structured thematic synthesis of modelling decisions enables comparison not only of the approaches used in economic evaluations but also of the underlying reasoning behind those choices. The ARN framework provides a transparent and complementary approach for examining methodological decision making in economic modelling studies and may support improved interpretation of modelling assumptions in HTA and related evidence syntheses.