At iMTA we are involved in the development and economic evaluation of many medical devices. Our involvement in the development allows us to perform ‘headroom analyses’ for pricing strategies. In the economic evaluations we identify which stakeholder profits most from introduction of the device. We have worked with CT scanners, MRI scanners, sleep position trainers, biomarkers, telemonitoring for cardiac care, stents, heart valves, light therapy, and diabetes pumps.
Key achievements in the field of medical devices
A particular challenge in estimating cost-effectiveness of medical devices is that the economic evaluation is often performed right before or after market access, while newer devices become available during, or right after the HTA study. This issue requires timely as well as fast assessments, without losing quality.
iMTA worked on several high quality economic evaluations, some for NICE, some for industry. In most instances, open surgery was compared to endovascular procedures, for example for TAVI, EVAR, FEVAR and BEVAR procedures. QALY estimates as well as costs were often modelled from intermediate outcomes using Markov models. We also published a key article on modelling issues in cardiovascular diseases and potential solutions.
Cost-effectiveness results can be used to identify optimal pricing strategies in a given HTA reimbursement context. A good example was our 1-year cost-effectiveness study of four hypothetical add-on diagnostic tests in early inflammatory arthritis patients at risk for reumatoid arthritis. We found that the available headroom of a new test varied between 170 Euro and 350 Euro depending on the test performance and patients that were tested with the add-on test, given a willingness-to-pay threshold of 20,000 Euro per QALY.more info →
To populate cost-effectiveness models, iMTA performed systematic reviews of CEAs for Stents, ICDs, TAVI, EVAR and lifestyle interventions. Our main conclusion from these reviews: effectiveness is often well demonstrated but divergent methods for estimating cost-effectiveness cause a wide range of cost per QALY outcomes.more info →
As we often work with biomarker tests, we often make a decision-tree to identify false-positive and true-positive patient responders to the test, followed by a Markov model to assess costs and effects.
A great example is our decision analytic model for CT scans versus heart catheterization. Both methods were used to identify heart problems in patients. While heart catheterization is more costly, invasive and involves an increased stroke risk, a CT scan involves radiation exposure. All these elements could be modelled at iMTA to identify the optimal strategy.more info →