Headroom analysis in early evaluation of diagnostic technologies not expected to result in QALY gain: The case of complex paediatric neurology

The headroom method was introduced for the very early evaluation of the potential value of new technologies. It allows for establishing a ceiling price for technologies to still be cost-effective by combining the maximum effect a technology might yield, the maximum willingness-to-pay (WTP) for this effect, and potential downstream expenses and savings. Although the headroom method is QALY-based, not all innovations are expected to result in QALY gain. This paper explores the feasibility and usefulness of the headroom method in the evaluation of technologies that are unlikely to result in QALY gain. This will be illustrated with the diagnostic trajectory of complex paediatric neurology (CPN). Our headroom analysis showed a large room for improvement in the current diagnostic trajectory of CPN in terms of diagnostic yield. Combining this with a maximum WTP value for an additional diagnosis and the potential downstream expenses and savings, resulted in a total headroom of €14,088. This indicates that a new technology in this particular diagnostic trajectory, might be cost-effective as long as its costs do not exceed €14,088. The headroom method seems a useful tool in the very early evaluation of medical technologies, also in cases when an immediate QALY gain is unlikely. It allows for allocating health care resources to those technologies that are most promising. It should be kept in mind however, that the headroom assumes an optimistic scenario, and for that reason cannot guarantee future cost-effectiveness. It might be most useful for ruling out those technologies that are unlikely to be cost-effective.

[1]  J. Veltman,et al.  The diagnostic pathway in complex paediatric neurology: a cost analysis. , 2015, European journal of paediatric neurology : EJPN : official journal of the European Paediatric Neurology Society.

[2]  A. Schuh,et al.  Issues surrounding the health economic evaluation of genomic technologies. , 2013, Pharmacogenomics.

[3]  R. Reading,et al.  Diagnostic exome sequencing in persons with severe intellectual disability , 2013 .

[4]  Gimon de Graaf,et al.  A method for the early health technology assessment of novel biomarker measurement in primary prevention programs , 2012, Statistics in medicine.

[5]  Maarten J. IJzerman,et al.  Early Bayesian modeling of a potassium lab-on-a-chip for monitoring of heart failure patients at increased risk of hyperkalaemia , 2012 .

[6]  Bonny Parkinson,et al.  Integrating Health Economics Into the Product Development Cycle , 2011, Medical decision making : an international journal of the Society for Medical Decision Making.

[7]  H. McAteer The use of health economics in the early evaluation of regenerative medicine therapies , 2011 .

[8]  Richard Lilford,et al.  Early-stage valuation of medical devices: the role of developmental uncertainty. , 2010, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[9]  J. Rizzo,et al.  Understanding the medical and nonmedical value of diagnostic testing. , 2010, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[10]  Carol A. Marra,et al.  Valuing the benefit of diagnostic testing for genetic causes of idiopathic developmental disability: willingness to pay from families of affected children , 2009, Clinical genetics.

[11]  Laura Vallejo-Torres,et al.  Integrating health economics modeling in the product development cycle of medical devices: A Bayesian approach , 2008, International Journal of Technology Assessment in Health Care.

[12]  K. Payne,et al.  Economic methods for valuing the outcomes of genetic testing: beyond cost-effectiveness analysis , 2008, Genetics in Medicine.

[13]  Peter Wood,et al.  Cost‐effectiveness analysis at the development phase of a potential health technology: examples based on tissue engineering of bladder and urethra , 2007, Journal of tissue engineering and regenerative medicine.

[14]  Richard J. Lilford,et al.  Investing in new medical technologies: A decision framework , 2007 .

[15]  Thomas Bodenheimer,et al.  High and Rising Health Care Costs. Part 2: Technologic Innovation , 2005, Annals of Internal Medicine.

[16]  A. Girling,et al.  HEADROOM APPROACH TO DEVICE DEVELOPMENT: CURRENT AND FUTURE DIRECTIONS , 2015, International Journal of Technology Assessment in Health Care.

[17]  A. M. Chapman,et al.  Early HTA to Inform Medical Device Development Decisions - The Headroom Method , 2014 .