Value Assessment’s ‘Leaky Bucket’ Problem

In Health Affairs Forefront, NPC outlines the challenges in assessing the value of new treatments and proposes a framework and recommendations to ensure patient access to new therapies and continued biopharmaceutical innovation.

Scientific breakthroughs are leading to new medicines that fundamentally modify or even cure certain debilitating diseases. Gene therapies, for instance, have the potential to deliver one-time corrections for genetic conditions like hemophilia A and sickle cell disease. But how do we determine the value of such life-changing innovations? 

In Health Affairs Forefront, National Pharmaceutical Council (NPC) Vice President of Health Services Research Kimberly Westrich, MA, and Chief Science Officer Robert W. Dubois, MD, PhD, outline the challenges in assessing the value of these types of therapies and propose a framework and recommendations to ensure patient access and continued biopharmaceutical innovation. 

Challenges of Value Assessment for Curative Therapies 

One approach for estimating the economic value of treatments is cost-effectiveness analysis (CEA). When using traditional CEA methods that compare treatment costs to clinical benefits, curative therapies that are expected to provide significant health gains for conditions that currently have poor outcomes will result in very high “value-based” prices, potentially millions of dollars per therapy.  

In the next 15 years, some analysts estimate that more than a million patients will be treated with gene therapies. As such, determining how to thoughtfully measure and allocate the value of these innovative therapies is critical for the U.S. health care system.  

Some have proposed methods that ignore value-based results for curative therapies and explicitly cap prices. But these approaches may disincentivize the development of future transformative therapies and limit patient access to innovative medicines.  

Fundamental Questions About Value 

In the blog, Westrich and Dubois lay out a three-step framework of fundamental, inter-related value questions that have important implications for the assessment of health care treatments and therapies:  

  1. How do we define value? 

  1. How do we measure value? 

  1. How should we allocate value?  

Each question in the framework builds on the previous one, and any “leakage” of value from steps one and two will impact how value is allocated in step three. For example, if not all sources of value are identified or if value is not properly measured, value can be underestimated, leading to incorrect conclusions about value allocation, including what share of value is being realized by innovators.  

This “leaky bucket” problem in value assessment is likely to affect innovation incentives for individual diseases and therapies differently. If a treatment brings great value in an area that is often omitted from value assessments, such as productivity or caregiver burden, then that therapy may be more disadvantaged than others. 

Value assessments have real-life implications, so the quality of the analyses matter. Payers may rely on these assessments in making coverage decisions and limit access to an undervalued therapy. Innovators are then looking at these pricing and reimbursement decisions when considering incentives for investment in the next generation of therapies and whether their return on investment will be sufficient.  

Plugging Value Assessment’s ‘Leaky Bucket’ 

Westrich and Dubois emphasized the “need for comprehensive approaches to value assessment” to ensure important decisions by payers and other stakeholders are not being made based on incomplete assessments.  

The authors recommended that current gaps in value measurement should be addressed through adoption of a societal perspective on value, capturing and measuring a broader set of benefits and costs, rather than the typical narrower set of costs and benefits that reflect a payer perspective.  

They also stressed that the potential for and implications of “leakage” in value measurement should be called out explicitly in value assessments. “Just because some benefits may be hard to measure with today’s methods and data does not mean they are valueless,” they concluded.