Cost-effectiveness of artificial intelligence aided vessel occlusion detection in acute stroke: an early health technology assessment
Open accessAbstract
Background: Limited evidence is available on the clinical impact of artificial intelligence (AI) in radiology. Early health technology assessment (HTA) is a methodology to assess the potential value of an innovation at an early stage. We use early HTA to evaluate the potential value of AI software in radiology. As a use-case, we evaluate the cost-effectiveness of AI software aiding the detection of intracranial large vessel occlusions (LVO) in stroke in comparison to standard care. We used a Markov based model from a societal perspective of the United Kingdom predominantly using stroke registry data complemented with pooled outcome data from large, randomized trials. Different scenarios were explored by varying missed diagnoses of LVOs, AI costs and AI performance. Other input parameters were varied to demonstrate model robustness. Results were reported in expected incremental costs (IC) and effects (IE) expressed in quality adjusted life years (QALYs). Results: Applying the base case assumptions (6% missed diagnoses of LVOs by clinicians, $40 per AI analysis, 50% reduction of missed LVOs by AI), resulted in cost-savings and incremental QALYs over the projected lifetime (IC: − $156, − 0.23%; IE: + 0.01 QALYs, + 0.07%) per suspected ischemic stroke patient. For each yearly cohort of patients in the UK this translates to a total cost saving of $11 million. Conclusions: AI tools for LVO detection in emergency care have the potential to improve healthcare outcomes and save costs. We demonstrate how early HTA may be applied for the evaluation of clinically applied AI software for radiology.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Hill et al. and van Leeuwen et al. used lifetime QALY projections based on stroke or atrial fibrillation risk reduction.
“Hill et al.26 and van Leeuwen et al.37 used lifetime QALY projections based on stroke or atrial fibrillation risk reduction.”
From Systematic review of cost effectiveness and budget impact of artificial intelligence in healthcare (2025) · cites this paper as van Leeuwen et al.37
The Methods (Model structure and Health outcome) describe a lifetime model with outcomes expressed in QALYs. The Results report projected lifetime QALY gains from AI-assisted detection of previously missed large-vessel occlusions, not from reducing stroke or atrial-fibrillation risk. This verdict concerns van Leeuwen et al. only. (LLM, conf=0.88)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 21 · Cited by 70
Research works printed but not linked: 20
- [1]van Leeuwen KG Schalekamp S Rutten MJCM van Ginneken B de Rooij M Artificial intelligence in Radiology: 100 commercially available products and their scientific evidence Eur Radiol 2021 10.1007/s00330-021-07892-z 33856519 PMC8128724 · DOI · Paper page
- [2]Aronsson M Persson J Blomstrand C Wester P Levin L-Å Cost-effectiveness of endovascular thrombectomy in patients with acute ischemic stroke Neurology 2016 86 1053 1059 10.1212/WNL.0000000000002439 26873954 · DOI
- [3]Berkhemer OA Fransen PSS Beumer D A randomized trial of intraarterial treatment for acute ischemic stroke N Engl J Med 2015 372 11 20 10.1056/NEJMoa1411587 25517348 · DOI
- [4]Goyal M Menon BK van Zwam WH Endovascular thrombectomy after large-vessel ischaemic stroke: a meta-analysis of individual patient data from five randomised trials Lancet 2016 387 1723 1731 10.1016/S0140-6736(16)00163-X 26898852 · DOI
- [8]Amukotuwa SA Straka M Smith H Automated detection of intracranial large vessel occlusions on computed tomography angiography Stroke 2019 50 2790 2798 10.1161/STROKEAHA.119.026259 31495328 · DOI
- [9]Amukotuwa SA Straka M Dehkharghani S Bammer R Fast automatic detection of large vessel occlusions on CT angiography Stroke 2019 50 3431 3438 10.1161/STROKEAHA.119.027076 31679501 PMC6878187 · DOI
- [10]Hassan AE Ringheanu VM Rabah RR Preston L Tekle WG Qureshi AI Early experience utilizing artificial intelligence shows significant reduction in transfer times and length of stay in a hub and spoke model Interv Neuroradiol 2020 10.1177/1591019920953055 32847449 PMC7645178 · DOI
- [11]Grutters JPC, Govers T, Nijboer J, Tummers M, van der Wilt GJ, Rovers MM (2019) Problems and promises of health technologies: the role of early health economic modeling. Int J Health Policy Manag 8:575–582. 10.15171/ijhpm.2019.36 PMC6819627 31657184 · DOI
- [12]Ijzerman MJ Steuten LMG Early assessment of medical technologies to inform product development and market access Appl Health Econ Health Policy 2011 9 331 347 10.2165/11593380-000000000-00000 21875163 · DOI
- [13]Powers WJ Rabinstein AA Ackerson T Guidelines for the Early Management of Patients With Acute Ischemic Stroke: 2019 Update to the 2018 Guidelines for the Early Management of Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association Stroke 2019 50 e344 e418 10.1161/STR.0000000000000211 31662037 · DOI
- [15]McMeekin P White P James MA Price CI Flynn D Ford GA Estimating the number of UK stroke patients eligible for endovascular thrombectomy Eur Stroke J 2017 2 319 326 10.1177/2396987317733343 29900409 PMC5992738 · DOI
- [16]Becks MJ Manniesing R Vister J Brain CT perfusion improves intracranial vessel occlusion detection on CT angiography AJNR Am J Neuroradiol 2019 46 124 129 10.1016/j.neurad.2018.03.003 29625153 · DOI
- [17]Fasen BACM Heijboer RJJ Hulsmans F-JH Kwee RM CT angiography in evaluating large-vessel occlusion in acute anterior circulation ischemic stroke: factors associated with diagnostic error in clinical practice AJNR Am J Neuroradiol 2020 41 607 611 10.3174/ajnr.A6469 32165362 PMC7144646 · DOI
- [18]Pennlert J Eriksson M Carlberg B Wiklund PG Long-term risk and predictors of recurrent stroke beyond the acute phase Stroke 2014 45 1839 1841 10.1161/STROKEAHA.114.005060 24788972 · DOI
- [19]Lobotesis K Veltkamp R Carpenter IH Claxton LM Saver JL Hodgson R Cost-effectiveness of stent-retriever thrombectomy in combination with IV t-PA compared with IV t-PA alone for acute ischemic stroke in the UK J Med Econ 2016 19 785 794 10.1080/13696998.2016.1174868 27046347 · DOI
- [20]Luengo-Fernandez R Yiin GSC Gray AM Rothwell PM Population-based study of acute- and long-term care costs after stroke in patients with AF Int J Stroke 2013 8 308 314 10.1111/j.1747-4949.2012.00812.x 22568484 PMC6016735 · DOI
- [24]Mulder MJHL Jansen IGH Goldhoorn R-JB Time to endovascular treatment and outcome in acute ischemic stroke Circulation 2018 138 232 240 10.1161/CIRCULATIONAHA.117.032600 29581124 · DOI
- [25]Bandettini-di-Poggio M Finocchi C Brizzo F Management of acute ischemic stroke, thrombolysis rate, and predictors of clinical outcome Neurol Sci 2019 40 319 326 10.1007/s10072-018-3644-3 30430315 · DOI
- [26]Dijkland SA Voormolen DC Venema E Utility-weighted modified rankin scale as primary outcome in stroke trials Stroke 2018 49 965 971 10.1161/STROKEAHA.117.020194 29535271 PMC5895119 · DOI
- [27](2012) Methods for the development of NICE public health guidance (third edition). National Institute for Health and Clinical Excellence, United Kingdom 27905711
- Authors
- van Leeuwen, K. G., Meijer, F. J. A., Schalekamp, S., Rutten, M. J. C. M., van Dijk, E. J., van Ginneken, B., Govers, T. M., & de Rooij, M.
- Affiliations
- Radboud University Medical Center (NL)
- ORCID
- Venue
- Insights into Imaging
- Published
- 2021-09-25
- Volume
- 12
- Issue
- 1
- Pages
- 133-133
- ISSN
- 1869-4101 (ISSN-L)
- PMC
- PMC8464539
- OpenAlex
- W3203487754
- Cited by
- 70
- References
- 21
- Citations by year
- 2026: 11 · 2025: 23 · 2024: 21 · 2023: 11 · 2022: 3 · 2021: 1
- FWCI
- 6.87
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Insights into Imaging (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Radboud Repository (Radboud University) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Health Sciences › Medicine › Epidemiology › Acute Ischemic Stroke Management
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- artificial intelligence, large vessel occlusion, acute ischemic stroke, cost-effectiveness, early health technology assessment, artificial intelligence in radiology, Markov model, quality-adjusted life years, missed diagnosis, emergency stroke care, stroke registry data
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
