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Moving Beyond Theory: The Need for Active Cultivation of the Value Flower


Moving beyond academic rhetoric is the bold step needed to make a wider field of value flowers take root and flourish.

Despite decades of investment in patient-centered health care, we are all too aware that decisions about access and value are typically made in the context of financial risk management, and often without the input of those who should benefit from care. In addition to a myriad of payment reform strategies, rising interest in cost-effectiveness evaluation (as part of “value assessment”) commands a central place in the debate about how to measure and pay for high-quality, efficient, and equitable health care.

In 2018, the ISPOR Special Task Force on US Value Assessment published recommendations on existing and novel elements to be considered in value assessment (VA). Using what has come to be commonly known as the “value flower” (see figure below), the Task Force’s report made a case for the need for consideration of components beyond the quality adjusted life years (QALYs) gained and the net cost of a drug, device, or intervention.

While those recommendations have been an important contribution for wider discussion and have served as a reference point for driving the field of health economics and outcomes research (HEOR), there is a growing consensus that in practice, they do not capture key components in the complex debate about the concept of value. For example, in a recent article by Neumann et al., while the authors cited academic work exploring new methods that account for these additional value elements, they also acknowledged that their use and application remain inconsistent.

The goal of wider adoption is to demonstrate the relevance of value elements to real-world patient experience, data, and decision-making. More initiatives are needed that seek to both define, and put into practical application, one or more of these novel elements. There is also a need for more transparency in these efforts – in the form of open-source model code, open access publication, and publicly-available data resources – thus enhancing the opportunity for collective learning and accelerated adoption of better methods.

The Innovation and Value Initiative (IVI) provides the technical knowledge, resources, and collaborative learning platform that facilitate exploration and application of these value elements – and more. We do this work in partnership with patients and patient communities, researchers, and industry and purchaser stakeholders, to build consensus on the scope and inputs that need to be incorporated into value assessment models. A major part of our work creates learning resources in the form of open-source models that allow researchers and decision-makers to explore, apply, and test new methods using their own data to determine what impacts they have on our considerations of value. Since its inception in 2017, IVI has published open-source models that incorporate the functional capability to perform analyses on value of insurance, real-option value, and value of hope.

One example from our current work on major depressive disorder (MDD) showcases the complexity of moving from theory to practice. A popular topic is how to address productivity – one of the value flower “petals” that most stakeholders agree should have a role in our consideration of value. However, unpacking the concept into data inputs that are relevant to decisions for employers that reflect the real experience of patients, families, and caregivers reveals the enormity of the challenge. For instance, are presenteeism and absenteesim sufficient metrics of productivity? How should short-term and long-term disability be included? Are lost career opportunities due to a patient’s chronic or poorly managed condition measurable and useful to understanding value? How are caregiver productivity impacts measured and how can they be included in the assessment of an intervention? Even if consensus can emerge – through significant investment in dialogue – will appropriate data inputs be available to consistently support such analyses?

Another priority that should command our immediate and prolonged attention and effort is equity. Rather than standing alone as a “petal,” equity must be the stem from which value assessment blooms. IVI recently initiated a multi-year equity-focused effort to build consensus on how to operationalize value assessments that support equity. We already know that solutions will touch on the quality and representativeness of both clinical trial and real-world data. Together with our stakeholder partners, IVI will push further and explore how to define the processes, data inputs, and analytic methods that value assessment must consistently employ to support equity in decision-making.

It has been accepted that traditional methods and tools do not facilitate responsive, equitable decision-making. This alone should spur all actors to invest in not only academic, theoretical explorations, but active, applied research to define priorities and to demonstrate when and how additional value elements must be incorporated. The stakes are high – conventional approaches are ill-suited to address challenging questions, including but not limited to addressing equity in decision-making when clinical trial data fails to represent patient diversity and experience in all its dimensions.

As Neuman et al. acknowledge, so-called novel value elements “will not solve all issues related to value measurement in health care, but they can help us think more clearly and comprehensively about the trade-offs that individuals and societies are willing to make in their choices.” IVI challenges those with an interest in this endeavor to actively engage in our transparent learning lab to test these approaches and others. Moving beyond academic rhetoric is the bold step needed to make a wider field of value flowers take root and flourish.


  1. Strategies to Include Underrepresented Patient Populations in Patient Preference Research to Inform Open-Source Value Models
  2. Enhancing Our Understanding of Long-Term Value: Insurance Value
  3. IVI-RA Value Model
  4. Exploring the Implications of the “Value of Hope”
  5. IVI-NSCLC Value Model
  6. Open-Source Value Project Model for Major Depressive Disorder Health Economic Module: Draft Protocol
  7. Should We Pay for Scientific Knowledge Spillovers? The Underappreciated Value of “Failed” R&D Efforts

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