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AMCP Spring 2014

Payer Evidence Requirements for New Drugs: Trends and Impact

The call has been made-loud and clear: payers want more comparative evidence research (CER) for coverage decision making. However, the primary source for common research results-the biopharmaceutical industry-has been highly scrutinized by payers as a suitable source.
The call has been made—loud and clear: payers want more comparative evidence research (CER) for coverage decision making. However, the primary source for common research results—the biopharmaceutical industry—has been highly scrutinized by payers as a suitable source. Since it is unlikely that payers themselves will fund large-scale CER research, what can manufacturers do to make their research studies more palatable to payers? Katya Svoboda, MBA, MPH, Partner, Percipient LLC, Somerville, New Jersey, and Nathan White, CPC, director, NucleusX Market Access, Atlanta, Georgia, conducted a survey-based investigation to find out.


Mr White explained that outcomes research generally falls into 1 of 3 domains: (1) clinical, (2) economic, and (3) humanistic. For the purposes of the research, the outcomes research discussed is that which is available postlaunch, and is above and beyond the research results required for US Food and Drug Administration (FDA) drug approval.

Outside the United States, health technology assessment organizations play a large role in determining access to products after launch (eg, the UK’s National Institute for Health and Clinical Excellence). In the United States, there is little real-life use of outcomes data, and it does not impact drug pricing, said Mr White. Part of the reason is the quality (and quantity) of CER evidence in the United States is unsatisfactory. Several organizations are charged with improving outcomes evidence development through research, support, or guidance (eg, Agency for Healthcare Research and Quality [AHRQ], Patient Centered Outcomes Research Institute [PCORI], Academy of Managed Care Pharmacy [AMCP], Comparative Effectiveness Research Collaborative Initiative [CER-CI]).


Ms Svoboda described the findings of the research, which surveyed 20 payers, 4 advisors to health technology assessment committees, and 5 health economic outcomes research (HEOR) and managed markets executives from the pharmaceutical industry. “Payers don’t believe that phase 3 trials represent real-world use of medications. The lack of these outcomes data may or may not hurt coverage decisions, according to the study participants,” said Ms Svoboda, but they did indicate that the existing data do not allow for more informed decisions.


The payers suggest making pharmaceutical company–derived study results more applicable and actionable, perhaps by conducting head-to-head comparisons, “although they understand the manufacturers’ risk in doing this research and why it is not done,” noted Ms Svoboda. However, she emphasized that head-to-head study was the highest rated form of outcomes data for payers, followed by studies of health care resource utilization. Research involving quality of life were found to have the lowest value, according to payers.


Although patient-reported outcomes (PROs) can be useful, and the FDA has approved several products on PRO end points or with PRO labeling claims (eg, recently, tofacinib for rheumatoid arthritis), payers don’t weigh this information heavily. Not surprisingly, the payers surveyed rarely conduct their own new HEOR analyses, and it is done on an as-needed basis only, Ms Svoboda reported. “Seventy-five percent of the payers interviewed do not use manufacturers’ budget impact models in their coverage decision making, citing the low credibility of the model (ie, they are seemingly always positive for their product).”


Overall, payer needs for HEOR are not being met. The gaps are the result of lack of credibility of manufacturer-generated data, payers having insufficient resources to conduct their own research or critically evaluate existing manufacturer-generated research, lack of value placed on humanistic data, and study populations that do not reflect health plan membership. Manufacturers, on the other hand, understand the importance of including outcomes end points, but need to weigh their risk in doing so, which include delays in submission timelines and the risk of negative outcomes.


Mr White concluded that “manufacturers must improve the quality of outcomes data, including the transparency and quality of economic analyses. They also need to allow payers to conduct their own due diligence of the validity of these models. He suggested that payers pool their resources to form regional coalitions to jointly analyze health outcomes data. They can also provide more input into public and private efforts to create health outcomes study design standards.

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