Laura Vallejo-Torres1, Lotte Steuten2, Bonny Parkinson3, Alan J Girling4, Martin J Buxton3. 1. University College London, Department of Epidemiology and Public Health, Multidisciplinary Assessment of Technology Centre for Healthcare (LV-T) 2. University of Twente, Department of Health Technology and Services Research, Multidisciplinary Assessment of Technology Centre for Healthcare (LS) 3. Brunel University, Health Economics Research Group, Multidisciplinary Assessment of Technology Centre for Healthcare (BP, MB) 4. University of Birmingham, Public Health Epidemiology and Biostatistics, Multidisciplinary Assessment of Technology Centre for Healthcare (AG)
Abstract
BACKGROUND: The probability of reimbursement is a key factor in determining whether to proceed with or abandon a product during its development. The purpose of this article is to illustrate how the methods of iterative Bayesian economic evaluation proposed in the literature can be incorporated into the development process of new medical devices, adapting them to face the relative scarcity of data and time that characterizes the process. METHODS: A 3-stage economic evaluation was applied: an early phase in which simple methods allow for a quick prioritization of competing products; a mid-stage in which developers synthesize the data into a decision model, identify the parameters for which more information is most valuable, and explore uncertainty; and a late stage, in which all relevant information is synthesized. A retrospective analysis was conducted of the case study of absorbable pins, compared with metallic fixation, in osteotomy to treat hallux valgus. RESULTS: The results from the early analysis suggest absorbable pins to be cost-effective under the beliefs and assumptions applied. The outputs from the models at the mid-stage analyses show the device to be cost-effective with a high probability. Late-stage analysis synthesizes evidence from a randomized controlled trial and informative priors, which are based on previous evidence. It also suggests that absorbable pins are the most cost-effective strategy, although the uncertainty in the model output increased considerably. CONCLUSIONS: This example illustrates how the method proposed allows decisions in the product development cycle to be based on the best knowledge that is available at each stage.
BACKGROUND: The probability of reimbursement is a key factor in determining whether to proceed with or abandon a product during its development. The purpose of this article is to illustrate how the methods of iterative Bayesian economic evaluation proposed in the literature can be incorporated into the development process of new medical devices, adapting them to face the relative scarcity of data and time that characterizes the process. METHODS: A 3-stage economic evaluation was applied: an early phase in which simple methods allow for a quick prioritization of competing products; a mid-stage in which developers synthesize the data into a decision model, identify the parameters for which more information is most valuable, and explore uncertainty; and a late stage, in which all relevant information is synthesized. A retrospective analysis was conducted of the case study of absorbable pins, compared with metallic fixation, in osteotomy to treat hallux valgus. RESULTS: The results from the early analysis suggest absorbable pins to be cost-effective under the beliefs and assumptions applied. The outputs from the models at the mid-stage analyses show the device to be cost-effective with a high probability. Late-stage analysis synthesizes evidence from a randomized controlled trial and informative priors, which are based on previous evidence. It also suggests that absorbable pins are the most cost-effective strategy, although the uncertainty in the model output increased considerably. CONCLUSIONS: This example illustrates how the method proposed allows decisions in the product development cycle to be based on the best knowledge that is available at each stage.
Authors: Christian E H Boehler; Gimon de Graaf; Lotte Steuten; Yaling Yang; Fabienne Abadie Journal: BMC Med Inform Decis Mak Date: 2015-09-04 Impact factor: 2.796