Overcoming the experimental or investigational label

Overcoming the experimental or investigational label

Health plans may classify a company's technology as 'experimental and investigational' if the company has not generated evidence to supplement FDA approval data for their technology and provider adoption rates are high enough to gain the payers' (CMS and commercial) attention.

It is critical for a company to quickly develop a strategy to generate a comprehensive body of evidence to reverse negative coverage decisions if a medical technology has already been classified as experimental and investigational. 

The most effective strategy is to build the following four types of evidence streams: 

  1. Published studies on clinical outcomes 
  2. Economic analyses exhibiting the financial impact (potential savings or even budget neutrality) 
  3. Inclusion of the technology or the related procedure/intervention in treatment guidelines maintained by medical specialty societies 
  4. Direct communications from hospitals, physicians, ACOs and patients requesting access to the technology 

There are specific characteristics of each evidence type that are essential to creating effective evidence capable of reversing an experimental and investigational coverage decision.

Clinical Evidence 

While the ideal outcomes required to prove clinical utility vary by product type and medical specialty, payers often request clinical findings on mortality, complications, reduction in symptoms and reoperations. The required length of follow-up time to measure clinical outcomes can also be dependent on product type; however, payers are more often convinced by studies measuring the long-term impact of a product (one to two years, sometimes longer for certain chronic conditions). Researching positive coverage decisions on the current standard of care or similar medical technologies can identify the outcomes of highest interest as well as the follow up time required to convince individual payers of clinical utility and efficacy. Coverage decisions from multiple health plans should be reviewed as some payers set the bar higher than others when reviewing clinical evidence.  

Multiple methods of study designs and data sources can be utilized to demonstrate clinical evidence including randomized controlled trials (RCTs), meta-analyses, prospective cohort studies, claims data analyses and medical record reviews. A vital component to any of these analyses is adequate sample size. Health plan medical directors often indicate that the total study population (inclusive of all cohorts) should be at least 200-300 patients. While there is some flexibility given to the clinical study of rare diseases, this number is driven from health plan actuaries who require a minimum population to accurately predict the effect a technology will have on their membership. In addition to a sufficient sample size, it is essential to ensure the appropriate patients are included in each cohort. Typically the current standard of care is the most suitable comparator group but further selection criteria may need to be applied in order to guarantee patients in each cohort are truly comparable. Procedures such as propensity matching and/or applying a strict inclusion and exclusion criteria based on patient demographics and diagnoses can be used to select similar patients.  

To demonstrate objectivity, clinicians or other organizations not associated with the company should be responsible for conducting the study and writing any publications on study results. Findings should be published in a peer-reviewed journal that reaches the appropriate audience; for clinical evidence that is a medical journal. Other important factors to consider are the journal’s impact factor, an indication of how the journal compares to similar publication outlets, as well as the total readership.  In some cases, readership may be more important than the journal’s impact factor. 

Economic Evidence 

Similar to clinical evidence, there are multiple methods of conducting economic analyses that can assist with payer coverage, including budget impact models (BIMs), longitudinal analyses, incremental cost effectiveness ratios (ICERs) and micro-costing studies. For example, a cardiac assist device (CAD) manufacturer achieved payer coverage with the assistance of a BIM demonstrating the clinical and economic benefit of their device compared to the current standard of care.  

Economic analyses are most effective when they combine the current standard of care as a comparator along with the use of ‘real world medical record or claims data’ instead of literature sources. Further, all relevant pre- and post-costs including post-acute care, readmission or any medical expenses required before use of the technology (such as pre-operative imaging or diagnostic testing) should be incorporated. While it is important to demonstrate the long-term economic impact of a medical technology, payers prefer technologies with short-term return on investments. However, if the technology will be reimbursed under an existing bundled payment program it should be noted that the payer will incur no additional cost when granting positive coverage. Lastly, studies should be conducted by a physician or third party and published in a peer-reviewed journal with managed care and health plan director readership. 

In addition to the criteria above, the following are valuable considerations for specific analysis types. BIMs intended for payers should culminate in a per-member-per-month (PMPM) impact. Often BIMs result in just pennies of PMPM savings, however the narrative of a superior medical technology improving the health of plan members and resulting in little to no additional PMPM cost (or a potential savings) resonates with payers. Longitudinal analyses, while calculated at the patient level, should take into consideration the episode-of-care relevant to the condition being treated. For example, acute conditions such as a knee replacements should be measured in the treatment timeframe, whereas a chronic condition such as diabetes is often effective to measure on an annual basis. ICER analyses, while popular among payers in other countries, have been slow to gain favorability among U.S. health plans. These analyses can be effective to show the quality adjusted life years (QALYs) gained compared to the current standard of care. Lastly, a micro-costing analysis can be utilized when the clinical outcomes between your medical technology and the current standard of care are similar but there are other efficiencies, for instance a reduction in surgical supplies or operating room time, which lowers the overall cost of care. Multiple researchers may be required to collect data in a micro-costing analysis as it is informative to not only track each step performed in the care process but to gather qualitative information provided by the healthcare professionals performing the tasks. ��

Medical Society Guidelines 

Endorsements from medical specialty societies, such as the American College of Cardiology (ACC) or the American College of Obstetrics and Gynecology (ACOG), can be as impactful as clinical and economic evidence. Health plans often review and incorporate treatment guidelines published by medical specialty societies into coverage decisions. Inclusion of a medical technology in guidelines is a strong source of evidence as they are developed by experts in a specific field who objectively review the treatment options in order to determine a recommended course of disease management. However, unlike health plan coverage decisions, guidelines are often not updated on an annual basis and therefore may require urging from an outside party in order to re-evaluate. As medical societies are organized by physicians it is often helpful to work with a practicing physician when requesting a medical society reassess their guidelines.  

Provider Adoption to Gain Payer Attention 

The last component of creating an effective evidence campaign designed to overturn an experimental and investigational medical policy is harnessing provider adoption trends into an effective communication campaign. This strategy involves encouraging providers to directly contact health plans and request access to the medical technology, with field support/evidence as part of the dialogue. Provider outreach can come from a variety of sources, such as individual physicians, ACOs, medical societies or hospital systems. While manufacturers should encourage providers to contact health plans, they should not assume a formal role in the process, as health plans are very wary of organized campaigns driven by manufacturers.  The more organic the campaign, the better.   

Before manufacturers approach payers with evidence to support the overturning of an experimental and investigational decision, outreach materials should be effectively packaged to clearly describe the technology's value. Often payer dossiers are created to concisely describe available evidence.

For more information on this topic, or to learn how Baker Tilly life sciences and healthcare specialists can help, contact our team.

David A. Gregory

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