Reimbursement for medical technologies has always been a complicated process involving coding, coverage and payment. These three components of reimbursement must be coordinated among a series of stakeholders –manufacturers, physicians, facilities and patients. This dynamic has gotten even more complicated in recent years as health care reform has heated up, with increasing scrutiny of comparative effectiveness, cost effectiveness and value propositions.
However, no matter how tortuous the path to durable coverage and adequate payment for a new technology, the bedrock, the ground zero, of the entire reimbursement process relies on the clinical evidence of safety and effectiveness. It starts with FDA clearance of approval process, and then ramps up as the CPT advisory panel considers applications for new codes, and then ramps up again as payers consider whether the data meets their (typically) more stringent evidence requirement. All of these steps require clinical data, and this same clinical data is a perquisite for any type of health economic analysis. Quite simply there will be no cost effectiveness or value if the clinical data does not first demonstrate safety and efficacy.
The key issue to understand is that there is not one single evidence requirement. Specifically, stakeholders implicitly juggle the following factors as they consider the evidence requirement:
- Target population (i.e. children, elderly);
- Disease (i.e. oncology vs. benign conditions)
- Technology category (i.e. diagnostic vs. therapeutic technology);
- Target payer (i.e. commercial vs. Medicare);
- Presence of competing technologies; and
- Past experience with technology (i.e. overturn of an existing negative coverage policy vs. creation of a new policy).
As a brief example, typically the payer evidence requirement is more lenient for vulnerable populations, particularly children, and for life-threatening disease, most prominently cancer.
Diagnostic technologies often have a complex evidence requirement which may consist of data showing not only that the technology can alter the management of the patient, but also ultimately improve health outcomes. In this situation, the diagnostic technology is tied to a therapeutic outcome, which may involve follow-up for months to years after the diagnosis.
In the case of competing technologies, payers may want a head to head comparison of the two technologies, particularly if the new technology claims to be better or is accompanied by a request for increased payment.
Finally, payers often establish an evidence requirement based on the initial data presented to FDA, or the data in from the pivotal trial. A negative initial coverage policy may provide boiler-plate language along the lines of “additional randomized trials are required to validate the promising outcomes in this initial trial.” In this situation, positive coverage may require getting payers to revise their evidence requirement and accept the weight of the literature rather than looking to individual trials.
Therefore, for a successful produce launch, it will be crucial to anticipate the regulatory, CPT coding and payer evidence requirement. Once this is understood, the manufacturer can consider such things as whether the proposed pivotal trial for the purpose of regulatory approval will be adequate to support a positive coverage policy or how to overlay the clinical data with a cost effectiveness analysis or other health economic analysis to address the needs of emerging stakeholders. Depending on where the manufacturer is in the product launch pathway, next steps could include development of a payer communication strategy, organization of a field team, and training of the sales force.
This blog post is the first in a series focused on the key reimbursement issues in this fluid health care environment. Successive posts will provide a discussion of individual issues illustrated by real-life case studies. We are hoping that our readers will provide further comment or questions to provide an interactive discussion.
About the Author:
The posts are written by the staff of Argenta Advisors, a reimbursement consulting firm that is a recognized leader in the field of health policy and reimbursement for the life science industry. Argenta provides a comprehensive range of healthcare and reimbursement consulting services throughout the medical technology lifecycle, from policy to practice.
This article represents a good starting point to begin a lively discussion about reimbursement of medical devices and medical and surgical procedures – to add more detail to what has been said, coverage refers to the terms and conditions under which a payer will or will not provide payment for a specific procedure. The decision for or against coverage of a new procedure is directly related to the presence, or lack thereof, of valid scientific evidence available in well-designed clinical trials published in the United States peer-reviewed medical literature to validate the safety and effectiveness of a procedure to substantially improve health outcomes of patients over existing technologies.
I know this will be a controversial statement which I hope engenders input from many – as former Head of the Department of Coverage and Reimbursement at Aetna for 7 years, I believe that cost-effectiveness analysis should not be considered when a coverage decision is being considered and that the decision should be a purely clinical decision based on scientific evidence – my reasoning is this – a new medical device or new procedure is found to be more cost-effective than existing medical devices or procedures – what is the Health Plan to do with that information – they cannot steer physicians toward the lower cost medical device or procedure because that would be practicing medicine, which Health Plans are not allowed to do – if a Health Plan makes a coverage decision based on cost and the provider uses the medical device or procedure because it cost less, if a patient has any complications or death, the family could sue the physician and Health Plan for using a medical device or procedure based on cost and not clinical scientific evidence.