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2025年4月14日

Editor’s note: This is the second in a series of four articles on the crucial role health economic modeling plays in evaluating the clinical and economic impacts of healthcare interventions. The series will focus on common modeling approaches, including cost-effectiveness analysis, and highlight how these techniques have become indispensable tools for HTA submissions and global reimbursement decisions.

The evolving landscape of drug development and healthcare delivery requires integrated, evidence-driven approaches to ensure that new therapies bring maximum value to both patients and stakeholders. Cost-effectiveness analysis (CEA) has become an essential tool in this process—guiding decisions in clinical development, reimbursement, and even policy-making.

The second blog in our health economic modeling series dives into what a cost-effectiveness analysis truly is, why it’s indispensable in modern healthcare decision-making, and how various stakeholders benefit from its insights.

Read the first blog in our series ‘Building effective health economic models: key components for success’.

What is a cost-effectiveness analysis (CEA)?

A cost-effectiveness analysis is an economic evaluation technique used to compare the costs and health outcomes of different medical interventions. Unlike clinical trials that focus solely on efficacy and safety, a CEA incorporates economic aspects—for example, comparing costs (such as development and treatment expenses) against measurable health benefits (like extended life expectancy or improved quality of life).

The results are typically presented in terms of cost per quality-adjusted life year (QALY) gained, also known as the incremental cost effectiveness ratio (ICER), a metric that compares the relative cost and benefit on quality of life offered by a given intervention in relation to a competitor. A life-extending cancer drug might demonstrate cost-effectiveness if the ICER falls within acceptable “willingness to pay” thresholds set by healthcare authorities, and therefore be added to their list of approved medications. For example, a life-extending treatment for advanced renal cell carcinoma proved more effective than its comparators as measured in life-years (LYs) and QALYs, and despite costing more than existing standards of care, the ICER still met the UK National Institutes for Clinical Health (NICE) willingness-to-pay threshold. The drug was therefore positively recommended by NICE to be added to the list of medications approved for treatment of advanced renal cell carcinoma.

Why is cost-effectiveness analysis crucial?

Global healthcare systems face the difficult task of balancing finite budgets with a steady influx of innovative treatments. CEAs allow stakeholders to make informed decisions by addressing several vital health policy questions:

  • Is Drug A worth its high price in terms of patient benefits compared to Drug B?
  • Should healthcare systems prioritize treatment access for the rare disease impacting fewer patients or for the common condition with broader societal impact?
  • How does a new treatment’s economic and clinical value align with existing standards in key global markets like the U.S. or Europe?

Importantly, CEAs provide clarity on the projected clinical and economic impact of a treatment beyond the observational period of clinical trials. This can be achieved by extrapolating surrogate endpoints (e.g., biomarker changes or walking distance tests) to final clinically relevant endpoints such as overall survival. その結果A grounded prediction of whether a treatment will truly deliver sustainable value in real-world settings.

How and when are CEA results used?

Cost-effectiveness analyses play a critical role at multiple stages of a drug’s lifecycle. Here’s how:

Clinical Development Decisions
Early in development, pharmaceutical companies can use CEAs to inform their go/no-go decisions. Imagine this scenario: A team is assessing whether to invest in a promising therapy for a rare disease. By developing an early economic model, they can forecast the therapy’s potential long-term value and estimate real-world health outcomes. However, these early predictions typically involve significant uncertainty due to limited clinical data, necessitating cautious interpretation and sensitivity analyses to manage risks. This interface between clinical trial design and early Health Technology Assessment (HTA) advice creates strategic decision points around market access and pricing.

Reimbursement and Access
Once a drug is market-ready, the results of a CEA can be pivotal in persuading payers and HTA authorities to fund it, particularly in geographies with government-sponsored healthcare like the UK. Agencies such as NICE (National Institute for Health and Care Excellence) require evidence demonstrating that a therapy represents good value for money compared to current treatment options.

While the U.S. does not have a centralized policymaking body for healthcare coverage decisions, organizations such as the Institute for Clinical and Economic Review (ICER) have played a pivotal role in shaping payer decisions by evaluating the cost-effectiveness of newly launched therapies. In regions where cost-effectiveness analysis (CEA) is not a formal requirement for reimbursement, developing a model can still yield valuable insights particularly in understanding how key uncertainties and data gaps may impact projected QALY gains.

Which stakeholders rely on CEA insights?

The ripple effects of cost-effectiveness modeling go far beyond pharmaceutical companies. Here’s how different stakeholders are impacted:

Pharmaceutical Companies

  • Impact: Cost-effectiveness analyses (CEAs) play a key role in evaluating the feasibility of bringing a drug to market not just by assessing clinical endpoints, surrogate outcomes, and real-world evidence through economic modeling, but also by informing clinical trial designs to generate evidence aligned with future health technology assessment (HTA) requirements.

It is important to note that HTA evidence requirements often differ substantially from those required for regulatory approval. While regulatory bodies primarily focus on safety and efficacy, HTA agencies consider broader elements such as comparative effectiveness, long-term outcomes, and cost-effectiveness. As highlighted in a recent Certara publication ‘Integrating Payer Reimbursement Strategies into Modeling and Simulation-based Methods to Redefine Drug Development’ presented at ISPOR Europe, aligning early evidence generation with HTA expectations can significantly enhance a product’s market access potential particularly in markets where economic evaluations are central to reimbursement decisions.

  • Motivation: Efficiently allocate resources throughout clinical development while ensuring a strong value proposition for payers during reimbursement discussions.

Healthcare Providers

  • Impact: Providers, such as hospitals and medical centers, may use CEAs in resource allocation and treatment planning. These models calculate costs related to wages, equipment depreciation, and fixed facility expenses.
  • Motivation: Optimize operational efficiency and provide cost-effective care while ensuring resource deployment aligns with patient outcomes.

Private Insurers

  • Impact: CEAs often influence whether an insurer includes a medical technology in its coverage basket. Input on costs, health effects, and patient adherence are vital in determining the reimbursement strategy.
  • Motivation: Balance the books by ensuring that covered therapies provide measurable health benefits, reduce long-term healthcare costs, and align with organizational goals.

Patients and Advocacy Groups

  • Impact: Patients are ultimate beneficiaries of accessible therapies derived from informed reimbursement decisions. Including patient-centric inputs such as out-of-pocket costs or transportation expenses increases the relevance of CEAs.
  • Motivation: Advocate for affordable, equitable access to high-value therapies while understanding exactly how these solutions impact both medical and non-medical expenses.

Society

  • Impact: The societal perspective encompasses costs and benefits comprehensively, regardless of who incurs them (patients, healthcare systems, employers, caregivers, etc.), and allows decision-makers to see the true overall impact of an intervention on society.
  • Motivation: The societal perspective aligns with the goal of maximizing societal welfare, not just healthcare budgets, because it identifies interventions that provide the greatest net benefit to society. Many health economics guidelines (e.g., ISPOR value flower framework) recommend using the societal perspective, and it is a required component of some HTA-compliant models.

What’s next?

By fully integrating cost-effectiveness modeling into drug development processes, we can move toward a healthcare ecosystem that enhances population health without overburdening resources. Whether you lead an HEOR team or collaborate with health authorities in shaping policy, incorporating CEAs is no longer optional—it’s the key to sustainable, equitable healthcare progress.

It should be emphasized that even medical interventions with excellent clinical efficacy and safety may not be widely used and reimbursed due to the anticipated high costs of treating the target population or uncertainties associated with costs estimates and/or insufficient improvement in patient health for the cost. Of course, there’s a solution to this problem called Budget Impact (BI) Modeling that’s the focus of the third article in our series.

Health Economics and Advanced Modeling capabilities

For more information on Certara’s cost-effectiveness modeling services, navigate to the Health Economics and Outcomes Research (HEOR) page.

View HEOR Consulting ServicesContact us
Noemi Hummel

Associate Director

スイス連邦工科大学チューリッヒ校で経済学の博士号を取得し、ハイデルベルク大学で応用数学の修士号を取得しています。シニア生物統計学者として従事し、プロジェクトの方向性をモデリングしてきた、10年以上の経験を有しています。サターラでは、神経科学、腫瘍学、希少疾患を始めとする多様な疾患領域において、統計および経済モデリングに関するプロジェクトと、ベイジアンネットワークメタ解析、モデルに基づくメタ解析など、エビデンス合成方法の応用に携わってきました。

Mohsen Yaghoubi

Associate Principal Scientist

Mohsen is a health economist with 10+ experience in academia and industry. He specializes in economic evaluation alongside clinical trials, cost-effectiveness modeling, quantitative methods in health care, and burden of disease studies. He has built several economic evaluation models from scratch for different diseases (Diabetes, Cancer, Ophthalmology, Asthma, and COPD). Mohsen has also produced a wide range of evidence-based products in various clinical areas. He contributed to several Health Technology Assessment (HTA) research projects related to responding to decision-makers around the world.

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