Episode #6: In quest of good ‘value for money’

Decoding The Drug Pricing Models

This weekly series of posts intends to help define, decode and even demystify the multiple drug pricing models used by sellers and payers to agree on the provision of drugs to patients around the world. The spectrum of models is broad: simple vs. complex, financial vs. value-based, population-based vs. patient-based. I will uncover the full spectrum of models in 6 episodes, using Lyfegen’s taxonomy of 19 pricing models.

Previous episodes

Episode #1: Agreeing on a simple rebate (Models 1 to 4)

Episode #2: Capping the drug cost (Models 5 to 8)

Episode #3: Adjusting Indication-Based Pricing (Models 9 to 10)

Episode #4: Easing the access to new drugs (Models 11 to 13)

Episode #5: Pricing based on health outcomes (Models 14 to 16)

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Episode #6: In quest of good ‘value for money’ (Models 17 to 19)

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Different routes may lead to an agreement on the ‘value of the drug’, whether by generating evidence over time or taking a more holistic approach on the total cost of care or supplementing the drug with value-added services for payers or patients. These 3 value-based models become increasingly popular and ‘trendy’ as long as strong data tracking processes can be put in place. ??

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Model 17: Coverage with Evidence Development

Coverage with Evidence Development (CED) is a unique drug pricing model that aims to address uncertainties around drug efficacy and effectiveness before making any definitive reimbursement decisions.

Under this model, a health technology assessment (HTA) body approves new treatment for coverage and reimbursement, provided that further data is gathered about its efficacy and effectiveness within the target population in the country. This ensures that payers and patients have access to a new treatment earlier while maximizing the potential for real-world evidence collection to make future, more informed pricing decisions.

The critical difference between CED and other pricing models is that the reimbursement is conditional on collecting additional data. This can be pursued through:

• Continuing ongoing clinical studies if they have not yielded conclusive evidence yet.
• Starting additional new data collection initiatives for outcome measures that are not covered in existing clinical studies.
• Establishing a registry to collect further data from patients that get the treatment.

By implementing these approaches, it becomes possible to re-evaluate the health benefits and long-term efficacy of a treatment in real-world settings, ultimately allowing for price adjustments based on the evidence provided.

CED can be especially useful in the following situations:

• When there is insufficient data from clinical trials, especially for rare diseases or for patients with specific characteristics (e.g. age, ethnicity) who have not been well-represented in clinical studies.
• When there is a high demand for expedited access to a promising treatment, such as in the case of life-threatening or severely debilitating conditions, where the time-consuming traditional assessment process could lead to delay in access for patients in need.

The CED model is intended to address several payer concerns, including:

• Reducing the risk of exposure to ineffective or unsafe treatments.
• Ensuring that the final decision on coverage and reimbursement is grounded in robust real-world evidence.
• Allowing for more effective allocation of limited healthcare resources.

An interesting example is with NICE In England, where novel cancer drugs are commonly reimbursed through the Cancer Drugs Fund (CDF). This cancer-specific funding source enables access to drugs for which there is plausible potential that they would satisfy the criteria for routine commissioning, but where there is significant clinical uncertainty. NICE guidance often finds that while a product could not be recommended for routine use due to high uncertainty and limitations in clinical data, approved patient access through the CDF can be had on the condition that more evidence on real-world effectiveness is gathered.

In France, both Novartis' Kymriah and Gilead's Yescarta CAR-T cell therapies were approved on the condition of evidence collection. The French transparency committee (TC) requested that further long-term data should be collected to address the uncertainties regarding the long-term efficacy, safety, and complexity of the treatment process. Consequently, the TC recommended that Kymriah and Yescarta be reimbursed on the condition that a CAR-T-specific registry be established to collect further data from French patients to enable a reassessment of the health benefit observed in the real world.

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Model 18: Total Cost of Care

The total cost of care model (TCC) is an approach to drug pricing that takes into account the total cost of the treatment, including not only the cost of the drug itself but also the costs of any related medical services and procedures that are necessary for the patient to receive the full benefits of the treatment. This model aims to shift the focus from the cost of the drug alone to the total cost of care for the patient, which can often be a more accurate reflection of the true value of the treatment.

In a total cost of care model, drug pricing agreements are typically structured in a way that incentivizes drug makers to produce treatments that are effective, safe, and affordable for patients. For example, the manufacturer may agree to lower the price of the drug in exchange for a share of the savings that are generated by reducing the overall cost of care for patients.

The cost of care can be either pre-paid or post-paid, depending on the specific agreement between the stakeholders involved.

• In a pre-paid model, the payer, such as an insurance company or government health program, may agree to pay a set amount for the total cost of care for a specific period of time, such as a year, before the treatment is initiated. The drug manufacturer and the healthcare provider would then be responsible for delivering the treatment and related services within that pre-agreed amount.
• In a post-paid model, the drug manufacturer and the healthcare provider would deliver the treatment and related services, and then invoice the payer for the total cost of care. The payer would then pay the invoice based on the actual cost of care incurred. This model is often used when the total cost of care is difficult to predict in advance and allows for more flexibility in case the actual cost of care is different from what was initially estimated.

The choice between a pre-paid and a post-paid model depends on the specific needs of the stakeholders involved and the nature of the treatment being provided.

Compared to other drug pricing models, the total cost of care model is relatively complex to implement because it involves close collaboration between multiple stakeholders, including the drug manufacturer, the healthcare provider, and the payer. It requires a significant amount of data and analysis to determine the total cost of care for a specific patient population and to agree on the terms of the financial settlement between the stakeholders involved.

The specific clinical or outcome measures used in a total cost of care model can vary depending on the disease being treated and the treatment goals for the patient. Some common measures include:

• Quality of life measures such as pain, mobility, and ability to perform daily activities.
• Clinical endpoint measures such as disease progression, time to disease progression, or other specific markers of disease severity.
• Healthcare utilization measures such as hospitalization rates, frequency of doctor visits, and other measures of healthcare utilization.
• Resource utilization measures such as the number of diagnostic tests performed, the number of procedures performed, and the length of hospital stays.
• Economic measures such as direct medical costs, indirect costs such as lost productivity, and the cost-effectiveness of the treatment.
• By taking into account a range of factors, the total cost of care model provides a more comprehensive view of the true value of the treatment, allowing healthcare stakeholders to make more informed decisions about the use of treatments in clinical practice.

Despite the complexity of implementation, the total cost of care model can offer many benefits, including improved patient outcomes and quality of life, better alignment of financial incentives between stakeholders, and a more sustainable and equitable system of healthcare.

For these reasons, the total cost of care model is becoming increasingly popular.

There are several examples of the total cost of care model being used in different types of treatments.

• Oncology: The total cost of care model has been widely adopted in the oncology field. For example, the pharmaceutical company Novartis has a program in which it provides its cancer drug at a reduced cost to hospitals in exchange for a share of the savings generated by reducing the cost of care for patients.
• Orthopedic Treatments: The total cost of care model is being used in orthopedic treatments as well, such as joint replacements. For example, Johnson & Johnson has a program in which it provides its joint replacement devices at a reduced cost to hospitals in exchange for a share of the savings generated by reducing the cost of care for patients.
• Autoimmune diseases: In the U.S., Prime Therapeutics and EMD Serono reached a total cost of care agreement for the multiple sclerosis drug Rebif. The contract, which began on January 1, 2012, specifies that EMD Serono will pay rebates to Prime on the utilization of Rebif if patients who are on the drug have a higher overall total cost to their plans than patients taking a different MS drug, or if the medication adherence rate remains above a “specified level.” The clinical measures used to adjudicate the agreement are the number of relapses per year, the number of new or newly enlarged T2-hyperintense lesions on brain MRI, the number of new T1-hypointense lesions on brain MRI, and the change in disability as measured by the Expanded Disability Status Scale.

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Model 19: Added Value

Under the added value model, the manufacturer of a drug provides a range of additional services or support to payers or patients in exchange for a higher price for the drug. These services can include disease management programs, patient adherence support, reimbursement assistance, educational materials, and other services that can help to improve patient outcomes and reduce costs for pay.

The goal of an added value model is to align the interests of the manufacturer with those of the payer and the patient by ensuring that the payer is receiving a good value for the money it spends on the drug.

For example, a manufacturer may agree to an added value model in which it provides free access to a patient support program or a discounted price for a related drug in exchange for a higher price for the original drug.

Adjudicating an added value agreement involves monitoring the delivery and effectiveness of the additional services provided, as well as potentially negotiating thresholds or milestones tied to service quality, patient adherence rates, or healthcare cost savings. Patient-reported outcomes (PROMs) would typically be included to measure the entire care pathway. Milestones such as adherence to treatment protocol can be set, for example, over a period of 6, 12, or 18 months. Administrations or prescriptions are used to track adherence. The best approach is to include a combination of measures that directly evaluate the effectiveness of the added services in improving patient outcomes, enhancing patient experience, and reducing overall healthcare costs.

The advantages of the Added Value model include improved value for the payer, better drug pricing transparency, and incentivizing manufacturers to concentrate on delivering patient-centered care. However, challenges include the complexity of implementing and managing the agreements, which may necessitate sophisticated data tracking and analysis systems, as well as determining the precise value of the added services and how much they contribute to patient outcomes and cost savings.

As health data analytics and cost management practices improve in hospitals, it is a trend to aggregate value-added services to differentiate from competition.

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