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Negotiations: Using a population-based budget impact model (BIM) or a prescription-based BIM?


Budget Impact Model (BIM)


Your budget impact model is your most important negotiation tool for bringing a new drug or health technology to market. This is because the budget impact model sets up the scenarios which will be used for the trade-offs. Though many people in market access may not see it this way when they build the models given they are not doing the negotiation, this is how the process plays out. The sensitivity analysis and scenarios should be built with this objective in mind. For this reason the budget impact model should be built accurately as a negotiation tool with the submission with impeccable accuracy. What you choose as a model must line up with the market and the forecasts for that market. These elements will then be put in a legal agreement which the company and the payer will be held accountable to.


A Budget Impact Model (BIM) is a financial tool used to estimate the economic implications of adopting a new medical intervention, such as a drug or treatment, within a specific healthcare system. That healthcare system is usually governed by a payer type which may be a public or a private payer who is responsible for the funds. The budget impact model assesses how the introduction of a new treatment will affect overall healthcare spending over a defined period, typically one to five years. BIMs are particularly relevant for decision-makers in public health programs, such as Medicaid in the United States or CADTH (Canadian Agency for Drugs and Technologies in Health) in Canada, as they help inform resource allocation and funding decisions.


Use in Medical Spending Decisions


In the context of Medicaid funding in the U.S. or CADTH in Canada, BIMs are used to:


  • Evaluate the financial impact of new drugs on the healthcare budget.

  • Compare the costs of new treatments to existing therapies.

  • Inform policymakers about the affordability and sustainability of new interventions.

  • Support negotiations with pharmaceutical companies regarding pricing and reimbursement.


Types of Budget Impact Models


There are two primary types of BIMs: population-based and prescription-based models.


Population-Based Budget Impact Model


A population-based BIM estimates the budget impact of a new intervention across a defined population, taking into account the overall prevalence of the condition and the expected uptake of the new treatment. This model is particularly useful for:


  • Assessing the impact of treatments for orphan or rare diseases, where the patient population is small but may require significant resources.

  • Understanding the broader implications for public health systems, as it considers the entire population rather than individual prescribing patterns.


Prescription-Based Budget Impact Model


A prescription-based BIM focuses on the costs associated with individual prescriptions and is typically used for chronic diseases. This model is more suited for:


  • Estimating the long-term costs associated with ongoing treatments that patients will require over time.

  • Analyzing the impact of new therapies on existing treatment regimens, particularly in conditions where patients are on multiple medications.

  • Estimating accurately market shares is key in this model. Inaccuracies will delay negotiations.


Comparison and Suitability


The choice between a population-based and a prescription-based BIM depends on the nature of the disease and the treatment:


  • Orphan or Rare Diseases: A population-based model is better suited because it captures the full budget impact on a small, specific population, considering the high costs of treatment and the potential for significant budgetary implications.


  • Chronic Diseases: A prescription-based model is more appropriate as it allows for detailed tracking of costs associated with long-term therapy and the cumulative financial impact on healthcare systems.


  • New Class of Medicines: For new categories or classes of medicines, a population-based model may be preferred initially to assess the broader implications, while a prescription-based model can provide insights into ongoing costs and resource utilization as the treatment is integrated into standard care.


Conclusion


In summary, Budget Impact Models play a crucial role in guiding healthcare spending decisions, particularly for Medicaid, public payer expenditures, managed care and CADTH overrall health expenditures on entire system. Understanding the differences between population-based and prescription-based models is essential for accurately assessing the financial implications of new treatments, especially in the context of rare diseases and chronic conditions.


References & Sources


References & sources I use to build economic & budget impact models for negotiating new drugs or health technologies in global markets:










9). Bodenheimer, T., Grumbach, K. (2012). Understanding Health Policy: A Clinical Approach. McGraw Hill Lange Medical.


10). Brazier, J., Ratcliffe, J., Salomon, J.A., Tsuchiya, A. (2007). Measuring and valuing health benefits for economic evaluation. Oxford University Press.


11). Brunsson, Nils. (2007). The Consequences of Decision-making. Oxford University Press.


12). Crowley, P.H., Zentall, T.R. (2013). Comparative Decision Making. Oxford University Press.


13). Glied, S., Smith, P.C. (2011). The Oxford Handbook of Health Economics. Oxford University Press.


14). Hall, M.A. (1997). Making Medical Spending Decisions. The law, ethics & economics of rationing mechanisms. Oxford University Press, New York, Oxford.


15). Henderson, J.W. (2002). Health Economics & Policy. South Western, a division of Thomson Learning.


16). Hunink, M., Glasziou, Siegel, J., weeks, J., Pliskin, J., Elstein, A., Weinstein, M. (2001). Decision making in health and medicine: Integrating evidence and values. Cambridge University Press.


17). Lammers, S.E., Verhey, A., (1998). On Moral Medicine: Theological Perspectives in Medical Ethics, Second Edition. William B. Eerdmans Publishing Company, Grand Rapids, Michigan/Cambridge, U.K.


18). Neuman, P.J., Cohen, J.T., Ollendorf, D.A. (2021). The right price: A value-based prescription for drug costs. Oxford University Press.


19). Pharmafocus 2025. IQVIA.


20). Varvey, B. (2020). Principles of Clinical Ethics and their application to practice. Med. Princ Pract. 2020 Jun 4;30 (1): 17-28 doi: 10.1159/000509119.


21). Rhodes, R., Battin, M.P., Silvers, A. (2012). Medicine and Social Justice: Essays on the Distribution of Healthcare, Second Edition. Oxford University Press.


22). Rang, H.P., Dale, M.M., Ritter, J.M., Gardner, P. (1995). Pharmacology. Churchill Livingstone.










 
 
 

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