Transforming legacy approaches to understanding drug costs: An Interview with HealthPlanView’s Nicole Espinoza

Dr. Patti Peeples, CEO of HealthEconomics.Com, sat down with Nicole Espinoza, Vice President of Knowledge Management at Pharmspective, a Healthcare Knowledge Management Company and the organization behind a new platform, HealthPlanView™, designed to address transparency around the true patient cost associated with pharmaceuticals. Disclaimer: This interview is paid for by Pharmspective and HealthPlanView™.

Dr. Peeples:  We are seeing an upsurge in companies developing approaches to understand drug pricing and access to treatment, catalyzed by the growth in specialty pharmaceuticals, expansion of step therapy, and imposition of strict utilization criteria at the health insurer level. What was the rationale behind the creation of HealthPlanView™ and what is your primary mission?

Ms. Espinoza:  The healthcare landscape has evolved significantly in the past few years, in part due to the explosion of specialty pharmaceuticals and other high cost drugs prescribed for chronic or life-threatening conditions. Our parent company, Pharmspective, works at the nexus of this healthcare ecosystem and uses digital app technology to create transparency around the evolving healthcare landscape and with a particular focus on the true cost of accessing and remaining on treatment.

Our latest innovation is HealthPlanView™, which – at its core – is a platform designed to dramatically increase transparency about the true cost burden assumed by patients and payers from treatment initiation through maintenance therapy.

Why is this important? We believe that formulary tier has become a poor proxy for the cost of treatment because of the complexity of insurer benefit designs and medical policy criteria.  As you note, health insurers have expanded their use of step edits and utilization management restrictions over the past few years. The intent of these types of benefit designs is to drive prescribing of lower cost (or cost-effective) therapy prior to allowing reimbursement for more expensive treatments.  HealthPlanView™ provides transparency around the true patient cost associated with each prescription to facilitate greater clarity to patients, payers, providers, and pharmaceutical manufacturers about the access and cost barriers that matter most.

Formulary tier has become a poor proxy for the cost of treatment because of the complexity of insurer benefit designs and medical policy criteria

Nicole Espinoza, HealthPlanView™

Dr. Peeples: How exactly does HealthPlanView™ provide cost transparency to these stakeholders?

Ms. Espinoza: We know that reimbursement of pharmaceuticals is incredibly confusing, complicated by the litany of insurer benefit designs that patients must choose from.  These benefit designs layer on deductions for pharmacy and medical costs, copays for prescription drugs and doctors’ visits, and exclusions for certain treatments.  By providing more granular understanding on these nuances in benefit designs, HealthPlanView™ can create a view of the differences in patient out-of-pocket costs that are unique to each patient, payer, and treatment.  In a nutshell, we increase transparency around all of the elements that impact the patient cost burden, something that has not been done before.

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Dr. Peeples: How has our industry managed this challenge of identifying true patient costs prior to this new tool? In other words, what have we been doing and what are the negative consequences associated with this lack of knowledge or lack of transparency?

Ms. Espinoza: For many years, legacy formulary tools have been focused on providing only formulary tier-level information as a proxy for cost and – in some cases – high-level utilization management data. We believe that distinctions such as “Preferred with a Step Edit” do not provide enough granularity to inform key decision makers’ understanding of how favorable or unfavorable access to a specific product is and the true impact of the cost burden associated with that product. 

Our goal is to 1) enhance understanding of drug utilization criteria such as specific diagnosis, testing, age, exclusion stipulations, and products prioritized for use prior to treatment initiation; 2) Create a level of transparency that can help users understand distinctions in these criteria across payers and between similar medications, and 3) provide specifics about the costs incurred as patients move from treatment initiation through maintenance therapy.

To put it another way, previous formulary tools have a blind spot in that they cannot bridge the gap between formulary placement and the likelihood that a patient will actually fill a prescription. Incorporating the details of a plan’s benefit design (which, of course, changes annually) has allowed us to create calculation algorithms in both Commercial insurance and Medicare to assess drug cost to the patient for each prescription filled across an entire year. By aggregating monthly out-of-pocket patient cost based on benefit design, enrollment, and policy data in our web-based platform, we are able to provide deeper insights.

At the manufacturer level, we understand that payer-facing departments, such as Managed Markets and Key Accounts strategy, need to be able to distinguish between access- and affordability-based nuances like deductibles, out-of-pocket maximums, and cost-sharing that are specific to each health plan. Without accounting for these nuances, patients that were once believed to have favorable access to a drug might realistically not be able to afford that medication and might ultimately not fill that prescription. This, of course, leads to poorer health outcomes and all of us – society, providers, payers, biopharma, and most importantly, patients themselves – have a goal to improve patient outcomes.

Those in Managed Markets and Key Accounts strategy need to be able to distinguish between access- and affordability-based nuances like deductibles, out-of-pocket maximums, and cost sharing that are specific to each health plan.

Nicole Espinoza, HealthPlanView™

In a nutshell, by providing greater transparency into true drug cost burden to patients and payers, HealthPlan View™ hopes to provide substantial context to inform understanding of the barriers to and decisions surrounding treatment choices.

Dr. Peeples: Benefit, formulary and product pricing is always changing. How does your insight tool keep up with these changes?

Ms. Espinoza: HealthPlanView™ is updated annually with Commercial and Medicare plan lists and benefit design details. Currently, the tool reflects 2019 data. On a quarterly basis, coinciding with P&T schedules, formulary data is updated. Additional updates are implemented if there are large M&A events or new product entries into a therapeutic area. Ad-hoc updates are available to any market basket requested by customers.

Dr. Peeples: What is your hope for how HealthPlanView™ will affect the business of healthcare, and specifically pharmaceuticals?

Ms. Espinoza: We believe that HealthPlanView™ will fundamentally transform pharmaceutical manufacturer contracting with payers by clearly distinguishing whether payers are easing access to treatment or simply acting as a conduit to patients with the financial resources to afford treatment.  We believe that this will alter the level of rebate incentives provided to a payer by considering the attractiveness of benefit designs offered by each insurer and the role that these designs play in the prescription volume being generated. The platform will also help customer-facing representatives and reimbursement support teams explain the challenges of benefit designs and the role of reimbursement support programs to providers.

For more information, visit The company welcomes requests for a complementary demo.

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Closing Gaps in Real-World Evidence through Data Linkage

Interview with Dr. Kevin Haynes, Principal Scientist, HealthCore-NERI.

Dr. Patti Peeples, CEO of HealthEconomics.Com, sat down with Dr. Kevin Haynes, Principal Scientist at HealthCore-NERI, to discuss closing gaps in real-world evidence through data linkage. The mission of HealthCore-NERI is to provide clarity that empowers decision makers to act with precision to improve quality, safety, and affordability in health care. HealthCore-NERI works with life science companies, payers and providers, and government and academic organizations to provide real-world evidence in support of a wide variety of health care decisions.

Dr. Peeples: Why is fragmentation in health care so important to health care researchers, and specifically real-world evidence?

Dr. Haynes: The fact that patients can seek care across health care systems, may move across geographies over time, and may change health plans fragments the patient journey within the health system. This fragmentation within the US health care system creates fragmentation of health care data and this data fragmentation inhibits our ability to generate high-quality evidence. In my opinion, the biggest gap to close is a gap in data. When we close the data gap, then we can begin to close the gaps in evidence. The same gaps in data that prevent us from generating high-quality evidence also create gaps in care. These gaps are closing as Health Information Exchanges, all-payer claims databases, and data integration with prescription dispensing records feed back into electronic medical record systems. As these data gaps close, our ability to generate high-quality evidence will improve. One area of data fragmentation is in the patient journey across health care systems creating a long-term fragmentation. As people traverse a lifetime of follow up periods, we traverse periods of our lives moving from childhood to college and early careers. This creates a fluid space of data moving across health plans as jobs, spouse, and life circumstances change our insurance coverage and access to health care systems. Today we need to be developing the infrastructure to be able to address these research issues moving forward. This is a long-term game as fragmentation of health care delivery currently has an impact on our ability to conduct observational comparative effectiveness research over a lifetime. Another area of fragmentation is cross-sectional data fragmentation which occurs as we seek care across health systems. For example in cancer we invariably fragment care as we instruct patients to seek a second opinion. As such tests and work up may be contained within one health system’s electronic records and treatment and longitudinal follow-up may be contained in a second health system’s electronic record.

Dr. Peeples: What are some of the biggest issues among stakeholders (providers, payers, patients, researchers, policy makers)?

Dr. Haynes: The biggest issue for stakeholders is data privacy and the governance required to manage the use of data for various purposes. There is clear governance with regards to HIPPA and other privacy considerations that govern the research aspects of data. Often the use of observational data at the institutional level notes loss of confidentiality as the only risk to the patient, and ensures that all data will be stored on secure servers with limited access. However, we are in an era now where we need to link to other data sources to close gaps in data fragmentation. This creates a need to utilize protected health information or personal identifiable information which may increase the risk to study participants in observational research. Therefore, we need to implement the technology to improve data privacy.

Dr. Peeples: With the fragmentation of health care across health systems, what do you see as the opportunities to overcome these data fragmentation challenges to enhance real-world evidence?

Dr. Haynes: There is tremendous opportunity as there is a lot going on in the data linkage space as people develop relationships with patients. For example, researchers involved in PCORnet’s Patient or People Powered Research Networks (PPRNs), the NIH’s All of Us, and other commercial ventures – are developing relationships with patients. They are able to get and seek, not only the consent, but also the authorization to link data across resources to develop the evidence that is needed. When researchers have access to patients, it is important to obtain sufficient patient authorization to conduct these linkage activities. Other opportunities exist in the space of protecting patient privacy in observational research, such as creating privacy protection record linkage.

Dr. Peeples: How do we do the data linkage? Are there specific use cases that have been successful?   

Dr. Haynes: One must either obtain patient consent through a relationship with the patient or utilize privacy-preserving record linkage strategies. For example, patients participating in PCORnet’s ADAPTABLE study, which seeks to identify the most appropriate dose of aspirin for secondary prevention of cardiovascular morbidity – have consented to participate. The study is therefore able to outreach and obtain authorization from participants to allow their health plan to share limited longitudinal information to help address one of the data gaps with regards to this study. Among PCORnet’s demonstration studies is a large obesity observational study looking at the effect of pediatric antibiotic exposure on the microbiome and the effect of weight gain at 5 and 10 years. This study is involving hundreds of thousands of patients. Considering the impossibility of obtaining the consent of or relationship with all patients, researchers are employing privacy-preserving record linkage to facilitate linkage of health plan pharmacy claims with clinical data.

Dr. Peeples: Patient privacy is of vital importance in the conduct of data linkage. How do you conduct the research and ensure patients their privacy is not being breached? What changes have occurred over time? What do you do that is a higher bar than is necessary, if anything?

Dr. Haynes: We as researchers need to develop the trust with our patients, especially patients who are recruited and enrolled in clinical trials where we have a relationship with the patient, to seek the necessary authorizations to do these linkages. We must also ensure that these linkages are used only for that intended purpose. As such, there is a need for governance around data use. When we have a relationship with the patient, we have an obligation to educate and inform patients in things like the ADAPTABLE study, the All of Us study, potential patient registries, and others, to inform patients of the importance of the linkage and that the linkage activities will be governed in such a way as to protect patient privacy. We also have a societal obligation to ensure that any linkage activities utilizing privacy-preserving record linkage modalities protect patients and their privacy.

Dr. Peeples: Expanding on the concept of data linkage, are there disease or therapeutic areas that are particularly challenging? Or areas where this data linkage has shown success?  

Dr. Haynes: There are tremendous opportunities and areas that are particularly challenging in this space of linkage. These challenges focus on both linking longitudinally and on linking over defined time periods to get deep clinical data. One example is in the opioids space where many states have prescription drug monitoring programs (PDMP). These programs are designed to capture all of the opioid prescriptions such that providers can access this resource and ensure that they have a complete picture of exposure to opioids across health systems. Pharmacists have an opportunity to assess this system to evaluate opioid utilizations beyond their pharmacy. These systems are designed to close a gap in care. However, one challenge is that these systems are not able to be utilized by health plans to potentially close gaps in evidence. The high-quality exposure information from state PDMP and the high quality outcome data from health plans would provide an opportunity to address evidence in the opioid epidemic.

Dr. Peeples: What are the ultimate rewards of linked data resources for RWE?  

Dr. Haynes: The most important thing from an epidemiologic standpoint to linked data is to reduce what we call information bias. There are several forms of information bias, including misclassification. Therefore, capturing outcomes or exposures of interest and knowing that you have complete capture is vital to the conduct of real-world data analysis.

Dr. Kevin Haynes, PharmD, MSCE, is a Principal Scientist at HealthCore-NERI. He is the Principal Investigator on two Patient Centered Outcomes Research Institute (PCORI) awards and the site Principal Investigator for HealthCore within the FDA Sentinel Initiative as well as a Data Core Co-Lead on Sentinel. At HealthCore-NERI, Dr. Haynes is currently responsible for developing responses to proposals and providing clinical pharmacoepidemiology expertise to various projects. Dr. Haynes has more than 14 years of experience in clinical pharmacy, clinical research, epidemiology, pharmacoepidemiology, surveillance, medical informatics, and project management. In addition, he has extensive experience collaborating with the Food and Drug Administration as well as multiple investigators on pharmacoepidemiology projects.

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