Designing a Complex Intervention Using Early Model-Based Cost-Effectiveness Analysis: A Case Study of an Artificial Intelligence-based Algorithm to Identify Vertebral Fragility Fractures

Garima Dalal, Ji-Hee Youn, Eleni Kariki, Paul Bromiley, Shawn Luetchens, Timothy Cootes, Katherine Payne

Research output: Contribution to journalMeeting Abstractpeer-review

Abstract

Objectives: Understand if, and how, using an artificial intelligence-based algorithm (AI) to identify vertebral fragility fractures (VFFs) from routine computed tomography scans (CT) should be used to maximise added value to patients. Methods: A de-novo decision-analytic model (lifetime horizon; NHS-England perspective) linking a bespoke decision-tree with a published discrete-event simulation (DES) was conceptualised and developed for a cohort of 400,000 individuals aged 70 years. The intervention (ASPIRETM) used AI to identify VFFs from existing CT with referral (to Fracture Liaison Service (FLS) or general practitioner) to start a bisphosphonate. The comparator was the current practice of radiologists identifying VFFs from CT and referral to start a bisphosphonate. Technical validation was completed using TECH-VER criteria. Model input parameters were identified from published literature and structured expert elicitation. For ASPIRETM and current practice the base-case analysis reported: number of VFFs identified; costs (£; 2014); quality-adjusted-life-years (QALYs). Uncertainty was quantified using one-way, two-way, scenario, threshold and probabilistic sensitivity analyses. Results: ASPIRETM identified 47,029 additional VFFs, costing an additional £8,681,804 (95% confidence interval (CI): £8,606,882 to £8,756,726) generating 139 (CI: 137 to 140) QALYs. The incremental cost-effectiveness ratio was £185 per additional VFF identified. All QALY gains (0.00035 per person) were derived from starting a bisphosphonate (the DES component). Threshold analysis showed increasing QALY gains to 0.00108 resulted in £20,000 per QALY gained. Key drivers of cost-effectiveness were: specificity; ASPIRETM unit cost; radiologists’ time averted by ASPIRETM and FLS cost. There was substantial uncertainty in the limited evidence available. Conclusions: Indicative cost-effectiveness analysis shows the importance of embedding ASPIRETM into a complex intervention directing people to effective bone management strategies (fall prevention, exercise and nutrition programmes) in addition to bisphosphonates and have data to show radiologists’ time averted. Importantly, decision-makers must be sufficiently certain in the model-estimated QALY gains from bisphosphonates to understand the potential value of ASPIRETM.
Original languageEnglish
Pages (from-to)S123-S124
JournalValue in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Volume24
Issue numberS1
DOIs
Publication statusPublished - 1 Jun 2021

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