• Conditional Reimbursement Policies: Moving Forward with Uncertain Evidence

    Conditional Reimbursement Policies: Moving Forward with Uncertain Evidence
    Conditional Reimbursement Policies: Moving Forward with Uncertain Evidence

    The discussion surrounding conditional reimbursement policies has grown more complicated in the current healthcare environment. Despite the uncertainty surrounding these policies’ efficacy and execution, we must investigate how we might proceed with them as we navigate this difficult terrain. [1]

    In other words, a new technology is initially sponsored temporarily under a conditional reimbursement paradigm. Afterward, a second decision is made based on further information, with the option to either terminate funding if the technology does not provide enough value (a perceived loss, as the technology was previously financed and subsequently withdrawn) or continue funding in order to maintain the status quo.  On the other hand, under a standard reimbursement paradigm, the choice is whether to support new technology, which might lead to either no gain at all or an improvement if funded.[1]

    Systems that promote efficiency and quality have replaced traditional fee-for-service models, which pay providers according to the amount of services they provide. The entire cost, cost-effectiveness, and therapeutic benefit of new medications are often uncertain. Reimbursement with conditions is one way to deal with this uncertainty. New pharmacotherapies who have already received the approvals are the main candidates for conditional reimbursement. Conditional reimbursement rules provide financial rewards to healthcare providers who achieve predetermined performance targets. Although these guidelines aim to save costs and improve patient outcomes, these regulations have proven to be more difficult to implement.[1,2]

    Critics claim that rules about conditional compensation may result in unforeseen outcomes, such as an excessive focus on quantity rather than quality, wherein clinicians give priority to fulfilling metrics rather than providing all-encompassing, patient-focused care. Furthermore, the added administrative work involved in monitoring and reporting results may cause funds to be diverted from providing direct patient care. The evidence is also ambiguous, and there is disagreement over what constitutes significant results, which causes differences in the formulation and application of policies. These policies also incite loss aversion, implying that greater incremental cost-effectiveness ratios (ICERs) are reasonable for current treatments than for novel treatments. This suggests that the decision-making procedure has a direct bearing on how a reimbursement decision turns out. The reassessment process appears to be a complicated and politically delicate procedure, according to the first experiences of countries implementing conditional reimbursement in practice.  Gathering new information in practice tends to be difficult, and officials appear to take a somewhat passive approach to withdraw payment, most likely due to popular opposition to these decisions.  Payers therefore require instruments to deal with these uncertainties in terms of both pricing and proof.[1,3]

    Conditional reimbursement policy advocates think they have the key to revolutionizing healthcare delivery, notwithstanding these obstacles. They contend that by providing incentives for innovation and advancement, these models eventually help patients by reducing costs and improving health outcomes. Conditional reimbursement enables the collection of stronger evidence about the efficacy and economic viability of novel technologies. The level of proof required from manufacturers is raised by a conditional funding mechanism, particularly one that requires continual data creation in real-world contexts and feeds back into the HTA process. This strategy may be able to address the post-HTA negotiation’s delays and lack of transparency, particularly for novel new drugs whose assessments have been accelerated by the HTA and regulatory aspects of the reimbursement process.[1,4]

    In order to effectively manage conditional reimbursement policies, a comprehensive plan including multiple crucial tactics is required. Policymakers should be aware of this possible problem when using conditional reimbursement as a tool for policy, as the decision-making process directly affects the outcome of a reimbursement decision. In order to jointly establish policies that support common objectives of enhancing patient outcomes and cutting costs, it is important to involve stakeholders from all corners of the healthcare spectrum, including payers, providers, lawmakers, and patients.  To guarantee that policies continue to be applicable and successful, mechanisms for ongoing review and modification should be put in place. This will allow for ongoing policy evolution based on empirical data. In addition, healthcare practitioners need sufficient assistance and training to comprehend conditional reimbursement rules and use them successfully. Any technological obstacles that could prevent compliance must also be addressed.[1]

    Navigating conditional reimbursement systems at the intersection of value-based and traditional healthcare calls for careful thought, dedication to cooperation, and adaptability. By taking a balanced approach that promotes patient outcomes, reduces administrative expenses, and fosters innovation, we can advance a plan that will benefit healthcare providers as well as the communities they serve. The road ahead is unknown, but by carefully drafting policies and emphasizing evidence-based decision-making, we may get closer to having a healthcare system that offers both value and quality.

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    References:

    1. Van de Wetering EJ, van Exel J, Brouwer WB. The challenge of conditional reimbursement: stopping reimbursement can be more difficult than not starting in the first place! Value Health. 2017;20(1):118-125. doi:10.1016/j.jval.2016.09.001.
    2. Pharmaceutical Pricing Board. Conditional reimbursement: guide for applicants. Available from: https://www.hila.fi/content/uploads/2023/01/Ehdollinen-korvattavuus_ohje-hakijoille_29.3.2023_EN.pdf.
    3. Mortimer D, Li JJ, Watts J, Harris A. Breaking up is hard to do: the economic impact of provisional funding contingent upon evidence development. Health Econ Policy Law. 2011;6:509-27.
    4. Glennie J, Villalba E, Wheatley-Price P. Closing the gaps to timely patient access: perspectives on conditional funding models. Curr Oncol. 2022;29(2):981–988. doi:10.3390/curroncol29020083.
  • Importance of Tapping Payer’s Data to Document the Effect of a New Therapy

    Importance of Tapping Payer’s Data to Document the Effect of a New Therapy

    Traditionally, the pharmaceutical industry has always been dependent upon the ‘push’ strategy for successful market access for products. The drug approval process, involving submission of data on efficacy, safety, and tolerability to the regulatory agencies, used to be simple; which ended with the drug being marketed to the targeted physicians and dispensed by pharmacies post approval. Thus, this whole process involved a limited set of stakeholders, viz. physicians, regulatory agencies, and pharmacies. Conversely, over the years, the market access landscape has evolved primarily due to two factors: (1)

    1. Rising healthcare costs owing to an increasing prevalence of chronic diseases, growing geriatric population, and higher prices of new therapies
    2. Competitive pricing and reimbursement environment

    This has further led to the emergence of a new and diverse set of stakeholders over the years, i.e. the ‘Payer’(s), increasing the complexity of drug access to the market in general, and to patients in particular. Payer exercises the greatest degree of control over pricing and reimbursement for any new drug, and will continue to dominate the market access scenario to ensure successful market access. (2,3)

    Pharmaceutical advancements are increasingly conflicting as countries attempt to accommodate healthcare costs via different tools. New criteria for recognizing unique drugs and differences among those within the same therapeutic area or concerning the same molecule are being introduced, even though ‘price’ remains the main driver. (4) There is a surge of criticism towards the increasing prices of drugs that adds growing pressure on pharma companies and manufactures to limit future price increases, and eventually on payers to be more cost-effective in their approach to setting budgets and managing costs. (5) Global pharma operations need to keep up with the pace of these changes to approach pharma tendering as a strategy that spans pricing and commercialization.

    In order to document the effect of a new therapy in the real world, pharma companies are trying to justify prices by tapping payer’s data. Payers encourage pharma to collect post-launch evidence of product performance in the real world, thus turning it in pharma’s favor. This can help verify a price agreement or even clarify uncertainties about the clinical and/or safety outcomes outlined at registration. (6)

    The successful market access will involve collaborative team work between sales and marketing departments. The strategy itself should be well equipped to respond to market evolution and also, to accommodate all known interactions. There is no ‘one-size-fits-all’ solution. The challenges in the market will constantly vary as per the product, therapy area and the setting in which the treatment will be used.i,vi

    Payers are increasingly focusing on “real-world” outcomes to form their decisions, encouraging new policies to be formed, in order to assimilate evidence from different sources. These policies prioritize the evidence that goes beyond information collected during clinical development in randomized controlled trials (RCTs), required by regulatory authorities for marketing approval. ‘Administrative data’- that normally use retrospective or real-time patient data – are an example of the real world data sources, as they are collected primarily for reimbursement, but contain some clinical diagnosis and procedure use with detailed information on charges. Retrospective analyses (longitudinal and cross-sectional) of clinical and economic outcomes at patient, group, or population levels can be performed with the help of claims databases. Such analyses can be performed in short time and at low costs. (7)

    In conclusion, payer data from real-world such as claims data can most certainly impact the sound coverage, payment, and reimbursement decisions. It is critical that payers recognize – a) the benefits, limitations, and methodological challenges in using these data, and b) the need to carefully consider the costs and benefits of different forms of data collection in different situations.

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    References

    1. Kumar A, et al. Pharmaceutical market access in emerging markets: concepts, components, and future. Journal of Market Access & Health Policy 2014; 2:10.3402/jmahp.v2.25302.
    2. McClearn C, et al. Big pharma’s market access mission. Deloitte University Press; 2013.
    3. Arx RV, et al. Leveraging success factors for market access in the life sciences industry. Capgemini Consulting and Cegedim dendrite; 2009.
    4. Skinner JS. The costly paradox of healthcare technology. September, 2013. 
    5. Pharmaceutical pricing and market access 2017.
    6. Wechsier J. Measuring the value of prescription drugs. Pharmaceutical Executive 2017; 37(5).
    7. Garrison LP Jr. Using real-world data for coverage and payment decisions: The ISPOR Real-World Data Task Force Report. Value Health 2007; 10(5):326-225.
  • Generating Scientific Evidence (Efficacy/Safety/Cost Data) from India

    Generating Scientific Evidence (Efficacy/Safety/Cost Data) from India

    Every country exercises strict control on medicines’ market access. Typically, this requires successful completion and adequate presentation of results from phase I through phase III clinical trials, bringing forward the findings of medicine’s safety and efficacy. The USFDA approves approximately 40 new medicines for the US market each year through this process. (1) In India, this number is more than 100 new medicines annually; however, there is not enough published evidence on submitted applications or summaries of approved medicines. Therefore, concerns are being raised about the safety and efficacy around medicine approvals in India in the absence of appropriate clinical trials. (2,3)

    For instance, a recent study, which evaluated the clinical evidence on the safety and efficacy of the most common metformin fixed dose combinations (FDCs) for T2DM in India, has highlighted the growing national and international concerns about the Indian drug regulatory system. Findings from this study further show high numbers of unapproved medicines and their irrational combinations floating in the market. This study has assessed the basis of efficacy and safety of top-selling metformin FDCs in India against four WHO criteria from clinical trial guidelines for the approval of FDCs. In India, only five FDCs have been approved by the Central Drugs Standard Control Organization (CDSCO); while, in reality, the Indian FDC-diabetes market contributes to the two-third of all diabetes medicine sales. (4) Furthermore, evaluation of published and unpublished clinical trials of these approved FDCs seemed to show underpowered and poor quality evidence of safety and efficacy for the treatment of T2DM. (5)

    The overall lack of available India-specific evidence heightens the need for its generation by publishing the unpublished trial results with Indian patients. India has in place the only required registration with Clinical Trials Registry – India, the national clinical trials database, since 2009. Moreover, the unpublished trials listed in this registry merely provide basic trial information with no results or outcomes reported. The lack of trials on Indian patients, in particular, is of concern, considering CDSCO’s guidelines for drug approvals acknowledge the importance of conducting trials on the Indian population to determine safety and efficacy.4

    Additionally, the Government, with an aim to achieve Universal Health Coverage (UHC) in order to reduce huge out-of-pocket (OOP) health expenditure and ensure affordable access to essential health care for the entire population, has identified a key priority of ensuring value for money in the health budget. This requires a systematic process for generating policy-relevant evidence that can inform policy decisions regarding health resource allocation, i.e. clinical effectiveness studies, cost-effectiveness studies, budget impact studies, along with ethical, social and political feasibility studies. (6) Needless to say that the healthcare payers, regulatory authorities, and health technology assessment (HTA) agencies also make decisions on relative efficacy of the new products based on evidence generated from clinical trials. (7)

    In most western countries along with the United States, the consumer rarely pays for the product—the payer is generally a third-party private or governmental insurer. Before approving a new medical entity (medicines/medical technologies) for reimbursement, private and governmental payers analyze clinical and economic data to determine the clinical value and cost-effectiveness of the new product as compared with currently available treatments. (8) Indian health system, on the other hand, is characterized by a vast but under-utilized public health infrastructure and a largely unregulated private market catering to greater need for curative action; where high OOP health expenditures hinder access to healthcare. (9)

    We believe it is high time even insurance companies start asking for robust evidence in order to provide reimbursement of better healthcare technologies and easier access to care. India needs to bring about a major reform in its health insurance policies, wherein a keen eye for detail is given to the published trial data on safety and efficacy of a drug or relevant evidence about a medical technology.

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    References:

    1. U.S. Food and Drug Administation. New Drugs at FDA: CDER’s New Molecular Entities and New Therapeutic Biological Products.
    2. Ministry of Health and Family Welfare, Department of Health and Family Welfare. Gazette of India, 10 March 2016. New Delhi, 2016.
    3. McGettigan P, et al. Regulatory upheaval and irrational medicines in India: a study of fixed-dose combination drugs. PLoS Med 2015; 12:e1001826.
    4. Evans V, et al. Adequacy of clinical trial evidence of metformin fixed-dose combinations for the treatment of type 2 diabetes mellitus in India. BMJ Glob Health 2018; 3:e000263.
    5. Shimpi RD, et al. Comparison of effect of metformin in combination with glimepiride and glibenclamide on glycaemic control in patient with Type 2 diabetes mellitus. Int J PharmTech Res 2009; 1:50–61
    6. Prinja S, et al. Health Technology Assessment for Policy Making in India: Current Scenario and Way Forward. Pharmacoecon Open 2018; 2(1):1-3. 
    7. Dang A, et al. Real world evidence: An Indian perspective. Perspect Clin Res 2016; 7:156:160.
    8. Gold M. Getting reimbursement for your product in the United States. June, 2003. 
    9. Prinja S, et al. Universal Health Insurance in India: Ensuring Equity, Efficiency, and Quality. Indian Journal of Community Medicine : Official Publication of Indian Association of Preventive & Social Medicine. 2012; 37(3):142-149.