Survey: How payers use nonpayer generated data to make formulary decisions


External, non-payer generated data can inform formulary decision-making-if payers know their strengths and weaknesses.

Assessing new and investigational drugs’ potential value for formulary decision-making will require payers to become more familiar with manufacturers’ models and other external data, according to panelists at an October 19 session of the Academy of Managed Care Pharmacy (AMCP) 2017 Nexus in Dallas.

“Measuring ‘value’ in healthcare has gone mainstream,” said Ami Gopalan, PharmD, MBA, vice president, director, payer access solutions at Precision for Value, in Chicago. “There’s desire to move away from volume across multiple stakeholders.”

“I think it’s pretty evident that the current volume approach is not sustainable,” Gopalan said. “Value is an important part of that discussion. But then the question becomes how do you calculate that value?”

Healthcare systems and health plans have access to extensive and detailed administrative and clinical data about their patient populations, but externally-generated data can importantly inform formulary decision-making about recent or pending FDA drug approvals.

Value-analysis tools like Memorial Sloan Kettering Cancer Center’s DrugAbacus and the Institute for Clinical and Economic Review (ICER) Value Assessment Framework are available and new regulatory frameworks are emerging, thanks to the 21st Centuries Cures Act and FDA guidance documents, Gopalan noted.

“We deployed a survey in early July 2017, with both open- and closed-ended questions to assess payer views and use of non-payer generated data for formulary decision-making,” Gopalan reported. Twenty-five health plan, pharmacy benefits managers, and health system pharmacy directors completed the survey.

Survey findings

More than half of the survey respondents reported being “extremely or very interested” in external data for forecasting, medical utilization and cost impacts, and quality and outcomes performance, he reported. Nearly three-quarters of them (72%) reported being very or extremely interested in using external data for drug utilization forecasting.

A range of other clinical, outcomes, and financial data sources exist, Gopalan noted. These include publicly-available and subscription-based clinical information sources and the AMCP Dossiers, real-world outcomes evidence from industry, third-party reviews, and financial data like pricing, budget impact models (BIM), and real-world cost experiences.

But “no single data source provides a comprehensive look across all attributes of formulary decision-making,” Gopalan noted.

For drug efficacy information, nearly half of respondents (46%) reported using publicly-available drug information and 44% reported using the AMCP Dossiers. Another 36% reported subscription-based drug information services being among their top go-to sources for formulary decision-making data.

“External data is most often utilized to inform clinical UM [utilization management] and savings opportunities,” Gopalan reported. About 60% of respondents reported using external data to derive clinical utilization management insights and pharmacy or medical economic savings opportunities, he said.

For nonclinical information, 100% of respondents use publicly available drug information and 88% use subscription-based drug information, Gopalan reported. Seventy-two percent use AMCP Dossiers. More than half use third-party reviews like ICER (64%) reports.

But whereas 60% use internally-derived real-world experience data for formulary decisions, only 32% use manufacturer-provided real-world evidence and only half as many as that (16%) use drug company BIMs, likely reflecting skepticism about possible bias built into such models, Gopalan noted.

Thirty-eight percent of respondents eschew manufacturer-provided BIMs because of insufficient transparency and another 29% reported that they do not use drug company BIMs because of questions about methodology.

Next: Top payer concerns



Top payer concerns

Lack of transparency, bias, and relevance are possible concerns, Gopalan said.

“From the payer side, impact models from different drugs’ manufacturers show that their own drug comes out great,” Gopalan said. “Two key challenges are bias and relevance.”

There are also internal obstacles to using external data, the survey showed. Fully 48% of respondents–nearly half–reported their organizations are “not capable at all,” “somewhat capable,” or only “moderately capable” of effectively analyzing and interpreting external data, for example.

Education is key to addressing payers’ limited internal capacity for analyzing external data, panelist Andrew Cournoyer, RPh, MBA, vice president, director, payer access solutions at Precision for Value in Gladstone, New Jersey.

“If we lack capacity, resources, or education, then educate yourself,” he advised. “Learn the methodologies, limitations, the FDA guidance, and use third-party resources.”

External data should not be ignored.

“We’re looking at a shift away from fee-for-service,” Cournoyer noted. “To really work within this environment, external data is important to close the gap.”     

Using external data allows payers to leverage baseline modeling methodologies in which manufacturers have invested, he noted. Using external BIMs requires an understanding of the assumptions used to build the models, allowing insights into specific populations’ needs, he said.

More payer formulary decision-makers should be including ICER reports in their research, Gopalan suggested.

“ICER reports can be daunting; they can be 600 pages long-not the easiest to read,” she said.

But their “Report-at-a-Glance” synopses spotlight key findings-including, importantly, value based pricing benchmarks, she said. The full report’s executive summary also contains important information, and ICER appendices are a “treasure trove of information,” she was quick to add.

“They organize evidence in tables,” she noted. “Using those can cut a significant amount of time” from the formulary decision-making process.

“Within the overall evidence out there, there’s data that talks about the effectiveness of treatment cycling with agents with similar mechanisms of action,” Gopalan noted. “Perhaps this is an opportunity to look at this section of the executive summary, pull the references cited and see have these already been evaluated by the plan, and ask, should they be to change our approach to this particular category?”




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