It’s Time to Modernize Budget Impact Analyses

Written By Lisa Bloudek

Issue 6

 
 

SCOTT RAMSEY, MD, PHD

Senior Partner and Chief Medical Officer, Curta
Adjunct Professor at the University of Washington, School of Pharmacy, CHOICE Institute
Professor at the University of Washington, School of Medicine

My colleague Anirban Basu and I recently published a paper in Annals of Internal Medicine examining the cost-effectiveness of the new gene therapies for sickle cell disease.1 Our teams built separate disease models and used claims data for sickle cell patients from Medicare and Medicaid to understand the impact of the treatment. While we disagreed about what a value-based price would be, both of our groups agreed on two important issues: the health benefits of these therapies will be huge (excellent value!), but so will the budget impacts (poor affordability!).

So huge, in fact, that neither of us are sure how some payers—particularly state Medicaid plans and smaller self-insured employer plans—will be able to cover these therapies and remain viable, particularly in areas where sickle cell disease is highly prevalent. This led me to wonder whether a more sophisticated budget impact model (BIM) might have been more useful to US payers than our cost-effectiveness analyses. But then I started thinking about how exactly BIMs— as they are currently built—would be helpful. It was a somewhat disappointing thought experiment.

Slouching Towards BIMtopiaa

BIMs are a staple of health insurance plan formulary submission dossiers, and the workhorses of many health outcomes research units. This is not an accident. Two very large specialty societies—ISPOR and AMCP—have published guidance on how manufacturers should prepare BIMs for insurers and health technology assessment groups.2,3 The publications were in response to a problem: lack of standardization. Without an agreed-upon conceptual approach and roadmap for reporting results, BIMs varied widely in approach and quality. Health insurers, for example, could receive vastly different BIMs for a single product: one manufacturer showing one budget outcome for their product while a competitor’s BIM would show a completely different outcome for the same product. In many cases, the BIMs weren’t even consistent in how they showed the budget impact.

So, standardization solved one problem, but over time it has created another one, at least to me: an ossified approach that quickly runs into limits in terms of helping payers and HTA groups figure out the logistics of how to pay for the influx of very high cost treatments for severe diseases (like sickle cell disease), most notably gene therapies, with most or all costs borne upfront and benefits that accrue over years or even a lifetime.

To give a sense of the problem, consider this: 7 of the 10 most expensive drugs by list price were FDA approved between 2020 and 2023, range in price between $1 million and $3 million.4 Six of these products were gene therapies, in theory administered once in a patient’s lifetime and in all likelihood, resulting in a cure. More than 60 gene therapies are expected to be approved by 2030, all very likely to cost (much) more than $1 million.5 Regardless of the benefits that these treatments bring to patients, payers in the United States are starting to take action to mitigate their exposure.

Under the standard reimbursement model that underlies most BIMs, the insurer that covers the patient at the time they receive the gene therapy pays the entire cost all at once. The huge upfront cost will be offset by downstream savings from reduced morbidity. Because the cost of therapy is far greater than the annual cost of managing the illness, meaningful offsets require that the patient stay with the plan for a very long time, often a decade or more. This time horizon is far beyond the typical BIM time horizon of 3-5 years. Contrast this with typical therapies where both the (ongoing) treatment costs and benefits are amortized over time (not always equally, of course). Economists and insurers have rightly asked whether this model is (a) fair and (b) creates perverse incentives. Alternative payment models are coming fast, particularly in Europe. In a nice paper published in Health Affairs, Caroline Horrow and Aaron Kesselheim created a taxonomy of new payment methods that insurers are creating to pay for these drugs.6 Some amortize payments over time, others tie payments to the drug’s initial performance in the patient, or tie payment to evidence of continued clinical benefit, others tie payments to prescribing volume in their enrollees—the list goes on.

“What’s important here is that these arrangements could have vastly different impacts on short- and longer-term payer budgets versus the “prescribe and bill” models that underlie most other drugs, and which dominate the current BIM-world way of thinking.”

How has the community that makes BIM’s responded to these issues? Judging by what I am seeing, they haven’t: Insurers are still getting the same BIMs that they did a decade ago. It’s worth asking why we haven’t seen much BIM innovation to date.b One plausible reason is that drugmakers aren’t asking for them. Risk-averse manufacturers probably don’t want to invite a discussion on novel payment models with payers if they can avoid it. Of course, insurers have to start this conversation, and by some accounts there is much talk but little action on this front in the United States. Some have noted that alternative payment models are hard to implement in the highly fragmented and regulated United States insurance market. Perhaps, but I can’t help but think that this is just another example of the well-known problem of institutional inertia. A notable exception is CMS: well before the gene therapies for sickle cell therapies were approved by FDA (priced at $2.2 and $3.1 million, respectively), they began work on what they now call the Cell and Gene Therapy (CGT) Access Model, an alternative payment model that is available and supported for state Medicaid plans.7 At some point, however, the pain is going to be severe enough that the commercial insurance world is going to be compelled to act (probably with policy support).

Building a Better BIM

I don’t see any reason why BIMs shouldn’t be able to accommodate new payment models. While BIMs are not rocket science, they can get complicated, and there is room for some innovative thinking as we think about modernizing them. What types of therapies will be most likely to be appropriate for alternative payment models? Is the typical outcome of these models—change in per member per month costs to insurers—the best outcome? Might there be “spillover effects” if providers shift prescribing to other drugs in response to outcomes agreements for a particular drug? Should we account for disenrollment and costs that are shared across plans? Frankly, we are past due for these types of discussions. Of course, we still want to make sure that the lack of standardization problem that plagued early BIMs doesn’t come back alongside modernized BIMs. With these issues in mind, here are a few suggestions for the BIM community:

  1. For those of us working with manufacturers of very high-cost therapies, consider implementing standard and alternative BIM structures to reflect novel payment mechanisms.

  2. Implement multiple payment models as scenario analyses, alongside standard sensitivity analyses.

  3. Develop standards for creating and presenting BIMs under the most common outcomes-based agreements.

  4. For very high upfront cost products, consider a more dynamic and open communication process between payers and manufacturers during the BIM development process, iterating the model as payment negotiations progress.

  5. Consider BIM’s that account for payer policies aimed at avoiding moral hazard (patients leaving an insurer after getting a very high cost treatment).

  6. Ask payers what would be most useful to them in a BIM.

In Conclusion…

BIM’s continue to serve a useful purpose as part of the dialogue between manufacturers and payers. These tools aren’t going away, but they will become less relevant for the highest cost (and highest profile) products—particularly those like gene therapies that load all treatment costs into a single, huge up-front payment—unless the BIM community sees fit to accommodate and incorporate the changing payment landscape for these therapies. One could even see a world where BIMs are an accelerator for alternative payment models if they serve to remove some of the uncertainty that surrounds them and provide a transparent tool for negotiations. Modern BIMs for modern drugs—it almost sounds like a catchy song title.

a Apologies to Brad DeLong and his excellently titled book on economic history, Slouching Towards Utopia. I couldn’t resist.

b I couldn’t find any papers providing guidance on how BIMs might need to be modified to account for outcomes-based agreements.

EXPLORE MORE

We developed a simplified BIM of a hypothetical gene therapy considering various alternative payment approaches. Download the Supplementary Materials and request a demonstration of the Excel model at Info@CurtaHealth.com.

Acknowledgements

Cynthia L. Gong, PharmD, PhD for significant contribution to this commentary. Lisa Bloudek, PharmD, MS and Brian Bloudek, MS for development of the hypothetical gene therapy BIM.

 

Scott Ramsey, MD, PhD

Senior Partner and Chief Medical Officer, Curta

 

REFERENCES

  1. Basu A, Winn AN, Johnson KM, et al. Gene Therapy Versus Common Care for Eligible Individuals With Sickle Cell Disease in the United States : A Cost-Effectiveness Analysis. Ann Intern Med. Published online ahead of print January 23, 2024.

  2. Sullivan SD, Mauskopf JA, Augustovski F, et al. Budget Impact Analysis-Principles of Good Practice: Report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force. Value Health. 2014;17(1):5-14.

  3. Academy of Managed Care Pharmacy (AMCP) Guidance on Submission of Pre-Approval and Post-Approval Clinical and Economic Information and Evidence, Version 4.1. https://www.amcp.org/Resource-Center/format-formulary-submissions/AMCP-Format-for-Formulary-Submissions-4.1.

  4. 10 of the Most Expensive Drugs in the U.S. January 15, 2024.https://www.drugs.com/article/top-10-most-expensive-drugs.html.

  5. Young CM, Quinn C, Trusheim MR. Durable Cell and Gene Therapy Potential Patient and Financial Impact: US Projections of Product Approvals, Patients Treated, and Product Revenues. Drug Discov Today. 2022;27(1):17–30.

  6. Horrow C, Kesselheim AS. Confronting High Costs And Clinical Uncertainty: Innovative Payment Models For Gene Therapies. Health Aff (Millwood). 2023; 42(11):1532-1540.

  7. Centers for Medicare & Medicaid Services. Cell and Gene Therapy (CGT) Access Model. https://www.cms.gov/priorities/innovation/innovation-models/cgt.

Lisa Bloudek
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