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Cost-effectiveness analysis of new generation coronary CT scanners for difficult-to-image patients

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Abstract

Aims

New generation dual-source coronary CT (NGCCT) scanners with more than 64 slices were evaluated for patients with (known) or suspected of coronary artery disease (CAD) who are difficult to image: obese, coronary calcium score > 400, arrhythmias, previous revascularization, heart rate > 65 beats per minute, and intolerance of betablocker. A cost-effectiveness analysis of NGCCT compared with invasive coronary angiography (ICA) was performed for these difficult-to-image patients for England and Wales.

Methods and results

Five models (diagnostic decision model, four Markov models for CAD progression, stroke, radiation and general population) were integrated to estimate the cost-effectiveness of NGCCT for both suspected and known CAD populations. The lifetime costs and effects from the National Health Service perspective were estimated for three strategies: (1) patients diagnosed using ICA, (2) using NGCCT, and (3) patients diagnosed using a combination of NGCCT and, if positive, followed by ICA. In the suspected population, the strategy where patients only undergo a NGCCT is a cost-effective option at accepted cost-effectiveness thresholds. The strategy of using NGCCT in combination with ICA is the most favourable strategy for patients with known CAD. The most influential factors behind these results are the percentage of patients being misclassified (a function of both diagnostic accuracy and the prior likelihood), the complication rates of the procedures, and the cost price of a NGCCT scan.

Conclusion

The use of NGCCT might be considered cost-effective in both populations since it is cost-saving compared to ICA and generates similar effects.

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Adapted from Briggs et al. [8]

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Acknowledgments

The authors acknowledge the clinical advice and expert opinion provided by: Ruth Clarke, Trainee Consultant Radiographer, Mid Yorkshire NHS Trust; Francesca Pugliese, Senior Lecturer and Consultant Radiologist, Barts and the London NHS Trust; Ramesh De Silva, Consultant Interventional Cardiologist, Bedford hospital NHS Trust; Carl Roobottom, Professor of Radiology and Consultant Radiologist, Plymouth Hospitals NHS Trust; Leo Hofstra, Professor of Cardiology, University Hospital Maastricht, the Netherlands. Furthermore, we would like acknowledge Valerie Fone, Trust Imaging Services Manager, Royal Brompton and Harefield NHS Foundation Trust who provided NHS cost information for cardiac CT. Thanks to Mark Sculpher, Centre for Health Economics, University of York, UK, for making the CE-MARC, EUROPA and York Radiation Models available.

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Authors and Affiliations

  1. Institute for Medical Technology Assessment, Erasmus University Rotterdam, Rotterdam, The Netherlands

    L. T. Burgers, W. K. Redekop, S. K. Lhachimi & J. L. Severens

  2. Institute of Health Policy and Management, Erasmus University Rotterdam, Rotterdam, The Netherlands

    L. T. Burgers, W. K. Redekop, M. J. Al, S. K. Lhachimi & J. L. Severens

  3. Research Group for Evidence-Based Public Health, BIPS -Leibniz-Institute für Prevention Research und Epidemiology, Bremen, Germany

    S. K. Lhachimi

  4. Kleijnen Systematic Reviews Ltd, York, UK

    N. Armstrong & M. Westwood

  5. Centre for Health Economics, University of York, York, UK

    S. Walker & C. Rothery

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  1. L. T. Burgers
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  8. M. Westwood
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  9. J. L. Severens
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Corresponding author

Correspondence to L. T. Burgers.

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Funding

This report was funded by the NIHR Health Technology Assessment Programme (Project No. 10/107/01) and commissioned on behalf of NICE. It will be published in full in Health Technology Assessment, Vol. 17, No. 9. See the HTA Programme website (http://www.hta.ac.uk) for further project information. The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the Department of Health.

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Burgers, L.T., Redekop, W.K., Al, M.J. et al. Cost-effectiveness analysis of new generation coronary CT scanners for difficult-to-image patients. Eur J Health Econ 18, 731–742 (2017). https://doi.org/10.1007/s10198-016-0824-z

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  • DOI: https://doi.org/10.1007/s10198-016-0824-z

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