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Use of Decision-Analytic Modelling to Assess the Cost-Effectiveness of Diagnostic Imaging of the Spine, Shoulder, and Knee: A Scoping Review
journal contributionposted on 2023-04-04, 00:08 authored by S Docking, L Gao, Z Ademi, C Bonello, R Buchbinder
Background: Limited evidence is available on the cost-effectiveness of diagnostic imaging for back, neck, knee, and shoulder complaints. Decision analytic modelling may be an appropriate method to synthesise evidence from multiple sources, and overcomes issues with trial-based economic evaluations. Objective: The aim was to describe the reporting of methods and objectives utilised in existing decision analytic modelling studies that assess the cost-effectiveness of diagnostic imaging for back, neck, knee, and shoulder complaints. Methods: Decision analytic modelling studies investigating the use of any imaging modality for people of any age with back, neck, knee, or shoulder complaints were included. No restrictions on comparators were applied, and included studies were required to estimate both costs and benefits. A systematic search (5 January 2023) of four databases was conducted with no date limits imposed. Methodological and knowledge gaps were identified through a narrative summary. Results: Eighteen studies were included. Methodological issues were identified relating to the poor reporting of methods, and measures of effectiveness did not incorporate changes in quantity and/or quality of life (cost-utility analysis in only ten of 18 studies). Included studies, particularly those investigating back or neck complaints, focused on conditions that were of low prevalence but have a serious impact on health (i.e. cervical spine trauma, cancer-related back pain). Conclusions: Future models should pay particular attention to the identified methodological and knowledge gaps. Investment in the health technology assessment of these commonly utilised diagnostic imaging services is needed to justify the current level of utilisation and ensure that these services represent value for money.