DECISION-MAKING PROCESSES

Robinson-Beale said most health plans have a technology assessment committee that reviews available information from peer-reviewed sources as well as third-party organizations to decide whether reimbursement is warranted. They will also look at what is generally accepted practice, in particular off-label use of a treatment. Typically, the studies they review are the same as were used to inform the FDA's decision on granting marketing approval for a therapy, but health plans may reach different conclusions, in part because they must assess the cost of a treatment compared to the cost of standard treatment. Moreover, each health plan conducts its own review process, creating an array of funding policies.

For example, in the case of TMS, the FDA concluded that TMS was appropriate after one failed trial of an antidepressant. Different health plans reached different conclusions: One decided to cover TMS after the fourth failed antidepressant trial; another stipulated that TMS would be covered only in patients who had adverse effects from antidepressant therapy, or who could not tolerate antidepressant treatment, or who preferred TMS as an alternative to ECT. Coverage decisions also differ by region, adding to the disparity across the country. In addition, Robinson-Beale said, a decision by the Centers for Medicare & Medicaid Services (CMS) ripples across the reimbursement landscape because it covers approximately 100 million people in the United States, and their associated health care expenditure (CMS, 2015). Other payers thus have to validate why they will not cover something that CMS covers.

Health plans also have to consider how other parameters of treatment affect reimbursement decisions, said Robinson-Beale, such as the dose, duration, and frequency of treatment required for a beneficial effect. For TMS, frequently raised questions include whether TMS is more efficacious than antidepressant medications, and if so, for which patients.

Cost plays an important role in reimbursement decisions, particularly with the high cost of some newer technologies and pharmaceutical products such as biologics that can cost hundreds of thousands of dollars per year per patient, according to Robinson-Beale. To reach decisions on covering these new technologies, health plans may require very good comparative analyses of cost versus efficacy with standard treatments, she said. Indeed, Eric Liebler, vice president of scientific, medical, and governmental affairs at electroCore, suggested that cost may have a positive impact on reimbursement for neurostimulatory devices because the costs of these devices may be materially less than some of the new pharmaceutical therapies coming out today.

Practice guidelines are another important factor in coverage decisions, said Robinson-Beale, but the American Psychiatric Association has provided very little detail regarding TMS other than to mention it as a possible treatment for depression, without identifying a clear target population. The American Medical Association also presents a potential roadblock to reimbursement because it issues Current Procedural Terminology (CPT) codes, which physicians need in order to be reimbursed. According to Ross Jaffe, managing director of Versant Ventures, it can take 2 to 5 years after FDA approval to obtain a CPT code, and the process is heavily influenced by specialty societies such as national medical societies or professional interest medical associations.

IMPROVING THE EVIDENCE BASE FOR REIMBURSEMENT

As noted by Robinson-Beale, the key issue for payers is whether a treatment is medically necessary and whether there is sufficient evidence to support that determination. Most of that evidence comes from peer-reviewed journals; however, she maintained that data analysis in published research studies may not be designed to demonstrate effectiveness or comparative effectiveness to standard treatment or in certain subpopulations. For example, many randomized clinical trials exclude patients with co-morbidities, thus failing to answer the question of whether a treatment will be effective in real-life populations. These studies may also lack clarity with regard to dosage, frequency, outcome measures, frequency of relapse, etc. Comparative effectiveness studies, such as the one described by Bradley Gaynes in Chapter 4 to evaluate TMS for depression, are also used by payers in determining reimbursement policies. In addition, some insurers have used FDA reports to evaluate treatment effectiveness, although they lack access to the actual data for further analysis. Administrative claims may provide additional data with regard to outcomes.

Other sources of evidence for payers include consensus guidelines from expert groups or observational data from large registries across heterogeneous populations. Robinson-Beale noted that in the absence of conclusive, comprehensive data, decisions on coverage and reimbursement must be made with gaps in information, resulting in a diversity of interpretations. She said payers would prefer to see comparative effectiveness of a treatment against the standard of care rather than sham treatments, as well as objective efficacy analysis that includes cost as a factor. If researchers and other data sources were able to answer key questions that are important to that application of a technology in real life practice, health plans would have more opportunity to make clear decisions on medical policy, and less of an opportunity to reject coverage reimbursement, she said.

IMPACT OF NON-REIMBURSEMENT

The disparity of coverage across different health systems limits patient access to innovative and potentially beneficial treatments and leads to fragmented and inconsistent care, said Mary Hailey, vice president of health policy and government relations at Neuronetics. It also impedes business development if there is no market for a new device, said John Reppas.

Reppas added that when the value of a technology is the ability to deliver individualized treatment, reimbursement decisions may be further complicated because payers have been slow to value patient-centric aspects of non-invasive approaches. In fact, they may focus instead on the additional costs that will arise from a higher level of patient engagement.

Hailey said the standards that devices must meet to gain coverage continue to rise over the years; several other workshop participants commented on inconsistencies (a “double standard”) between the regulatory and reimbursement requirements for devices compared to drugs. For example, Thomas Insel asked if there is a separate standard for medicine versus behavioral health, citing the insulin pump, a much more expensive device that has received positive reimbursement decisions from CMS and most insurers. Robinson-Beale attributed this disparity to the fact that medical devices enjoy a longer history of acceptance, whereas behavioral devices are relatively new, requiring a new way of thinking on the part of those making decisions. Another factor that may explain a lower level of acceptance for behavioral indications such as depression is the lack of clarity regarding how neurostimulation fits in with existing psychotherapy and pharmacotherapy approaches, said Robinson-Beale. Liebler added that more objective measures are often available for outcomes “below the head,” whereas behavioral outcomes are often more subjective.

Robinson-Beale suggested that as mental illness becomes better defined from a neuro-circuitry perspective, devices will be driven into accepted practice. She said this has started as the American Psychiatric Association working in conjunction with the NIMH on such projects such as the Research Domain Criteria (RDoC) project.¹

However, she also predicted that as these devices move into the consumer market and people come to believe that neurostimulation can safely be delivered over the counter, the medically reimbursed landscape may change dramatically.

Footnotes

1

See http://www​.nimh.nih.gov​/research-priorities/rdoc/index.shtml (accessed June 1, 2015).