The medical device industry is moving towards a connected care model with IoMT, creating an increased role for device manufacturers in the reimbursement process. Accurate measurement of how and when a device is used are essential for RPM and RTM CPT billing. By managing connected devices, manufacturers have access to key information beyond that collected by Patient Monitoring providers. In this blog, we explore how reimbursement strategy affects product adoption and why.
Join BioT CEO, Daniel Adler and expert Dr Michael Drues as they discuss how the effective measurement of reimbursements relies on input from device manufacturers and what steps are needed to bring medical devices in line with this new reality.
Getting your product cleared by the FDA is an essential part of bringing your product to market. However, it’s only a small part of the reimbursement puzzle. Receiving reimbursement coverage from CMS and insurance companies is significantly more complicated than passing the FDA. Bringing a product to market that does not have reimbursement coverage will significantly reduce the sellability of your product.
The product development process should not only just consider the requirements for FDA clearance, but also how the product fits within existing reimbursement codes. Having applicable reimbursement codes will accelerate time to market and improve chances for market adoption.
Many manufacturers assume that if their solution requires an FDA De NOVO pathway then they will need to create a new CPT code. This is not necessarily the case. Just because a product is innovative does not mean that it cannot fit into an existing CPT code. CPT codes that define the outcome as opposed to the process are particularly relevant. (For example, a solution that provides AI-powered screening might be innovative enough to require De Novo clearance but the procedure might be covered by existing CPT codes for screening procedures.)
On the other hand, just because a product could be covered by an existing CPT, does not mean that it should be. A new CPT code might enable higher billing rates and so more revenue generated by the product.
Choosing which CPT to apply to a solution is a strategic decision that should be a key part of product development. At the end of the day, a product that sells is a product that can generate revenue for end users.
Your reimbursement strategy needs to take into account more than just finding an applicable CPT code. Successful reimbursement requires that applications are accepted by insurers. Manufacturers should be supporting each stage of the reimbursement process. As a result, the strategy should:
1. Integrate seamlessly into the healthcare organization's own reimbursement processes;
2. Provide the necessary information required to submit a reimbursement claim;
3. Improve compliance with reimbursement requirements;
4. Automate reimbursement process to reduce workload and claims denials.
Research has shown that about 30% of reimbursement claims are denied even though 63% of those claims should have been recoverable. The main cause for these denials is human error and missing data. The cost resulting from these denials is approximately $8.6B in appeals-related administrative costs (or $118 per claim).
Medical devices designed with an automated reimbursement process can be expected to improve the adaptation rate of the device by dramatically reducing both the workload and human error, resulting in higher claims acceptance rate. Automated reimbursement processes can include:
Allocating the relevant CPT code can also be automated once the reimbursement criteria have been met.
It should be noted that by automating the reimbursement process, an additional challenge is created; How to meet constantly changing reimbursement requirements?
With the complexity of changing reimbursement landscape, many manufacturers are choosing to use cloud platforms that include automated reimbursement. By partnering with experts in healthcare data collection and storage, manufacturers are able to offer a reimbursement process that is cost-effective, more efficient, time-saving, and will answer any new challenges that may arise.
The terms ‘real-world data’ and ‘real world evidence’ are often used interchangeably. However, they refer to two different aspects of data collection. ‘Real-world data’ is all of the evidence collected regardless of its reliability. This could include patient-reported outcomes or patient feedback. ‘Real-world evidence is a subset of the ‘real-world data’. Real-world evidence is the data that has sufficient quality to be reproduced and is considered to be of a higher standard. This could include data on device usage collected by the device and stored in the cloud.
In recognition of the important role that ‘real world evidence’ can play, 3 years ago the FDA began accepting real-world evidence as part of the approval process for additional indications, or, label expansion.
The FDA requires clinical data for submission for label expansion. Currently, there are two options for presenting clinical evidence: 1) evidence collected from clinical trials; 2) the use of ‘real world evidence’ collected from a device that is already on the market and used for a specific indication. In this case, the real-world evidence: must have enough data, collected over time, from a diverse demographic and have the ability to be replicated.
The same standards that apply for label expansion should be applied to reimbursement. Real-world evidence, which by definition is reliable evidence, should also be an accepted standard for reimbursement.
Regarding product design, adding connectivity for post-market data collection (as real-world evidence) will simplify the label expansion submission process, cut costs and save time.
In health care, Fee-for-service (FFE) is an unbundled payment model, each service is paid for separately. Given that payment is dependent on the quantity of care, rather than the quality of care, it actually incentivizes physicians to provide more treatments and discourages the efficiencies of integrated care. This can be to the detriment of patient care as it discourages consideration of evidence of treatment efficacy. This results in an increased cost of services and poor patient care.
The value-based is a healthcare delivery model in which providers are paid based on patient health outcomes. The incentive is based on rewards for patients’ improved health, reduction of the incidence of chronic disease, and evidence-based proof of the patients’ healthier life. The benefits of value-based care systems are lower costs, better patient outcomes, reduced risks, and higher patient satisfaction.
The American healthcare system is shifting from FFS to Value-based care and this will be reflected in the reimbursement requirements and process. Healthcare providers will be required to submit evidence on patient outcomes and patient satisfaction, as well as objective data.
The Value-based care model will require the collection and documentation of patient data, evidence (i.e., an indication of the improvement of patient condition or adherence to treatment protocol), and the use of patient-reported outcomes measures (i.e., questionnaires to prove improved patient condition after treatment). We can also expect an increased demand for patient-based care; treatment based on reported results in combination with algorithms, and preventive care from providers equipped with tools to prevent further deterioration.
Connected medical devices are the most efficient tools to collect real-world evidence and patient data as well as improve adherence to treatment protocol (the device enables follow-up and notification capabilities), enable remote monitoring of patients, provide patient-based care, and prevent deterioration.
Given that the transition from FFS to value-based care is still in the early stages and guidelines are not yet clear, using a medical-grade cloud platform is the safest way to ensure future compliance with reimbursement requirements and simple integration of supporting features (i.e automatic PROMs tools).