Designing cost-effectiveness research that resonates in the United States

What’s the difference between an American and a European Health Economist? On the face of it, not much. We use many of the same methods, publish in the same journals, attend the same conferences, and work in the same global industry. Yet the health economics research that matters and is impactful in the United States can be very different from what makes sense elsewhere.

In single-payer systems, the central question is often: what is the most clinically effective and efficient option at a population level? A difficult question, but one that evidence syntheses and cost-effectiveness models are well able to address. In the US, decision-making is more often an individual matter between the patient and their physician (and heavily influenced by insurance), and much less about what works best on average. While the US has a more fragmented system, there can be fewer gatekeepers to specialist care. Clinical guidelines frequently recommend multiple options, leaving choices to patients and providers. In practice, decisions are often shaped by guideline/formulary recommendations, public and private insurance coverage, and the various other trade and channel issues (including patient support programmes) inherent in commercial plans.

So what are health economists to do? When it comes to cost-effectiveness research in particular, how do we make sure that our outputs really resonate with US stakeholders who have uncertainties to manage and decisions to make?

With experiences on both sides of the pond, I have some thoughts…

Step one: Begin with listening, and think big

A more effective approach begins not with diving into any research, but with reading, listening, learning, and understanding perspectives that are likely more nuanced and complex than indirect comparisons or economic modelling that an HTA may direct.

• Map the patient journey, clinical guidelines, and underlying evidence. Engage as closely as possible with patients, caregivers, and others affected to understand lived experiences. Where are the gaps in care, who experiences them, why do they exist, and what might help?

• Identify the key decisions and challenges faced by patients, providers, and payers, particularly those that are highly uncertain or unaddressed by existing studies.

• What are the endpoints and value measures that are important to stakeholders? Maybe they are traditional elements; perhaps they incorporate broader aspects (productivity, insurance, hope, etc.).

• Listen to stakeholders across medical, market access, clinical, and commercial functions. What challenges do they see, and where might stronger health economic evidence help?

Only then should health economics researchers ask where our analyses might answer or at least inform these issues. To be impactful in the US, health economics research must go beyond traditional population-level analyses of effectiveness and efficiency necessary for HTA submissions, and grapple with the questions that affect the diversity of individual outcomes and experiences with health care.

Step two: Avoid temptation

There are three tempting assumptions that should absolutely be avoided.

It can be tempting to assume that, because the US lacks a formal HTA framework and QALYs are rarely directly used by payers, cost-effectiveness research has limited relevance. This is short-sighted. US stakeholders still face complex decisions involving cost, outcomes, and trade-offs—and well-designed research can inform many of them.

Producing a publication that concludes “Drug X is cost-effective at $X per QALY” may be all that your Global Value or AMCP Dossier needs to get sign-off from compliance. But treating cost-effectiveness research as a box-checking exercise in this way risks you missing an opportunity to address meaningful scientific or policy questions relevant to your stakeholders.

Finally, a strategy of only publishing analyses with clearly and unambiguously positive results may feel safe, nothing controversial will reach the public domain with your name on it. But it can also guarantee that your stakeholders are missing the information and insights you could bring them to improve patient care, and of course does nothing to inspire trust. Independent perspectives — including those that challenge readers’ presumptions about industry-funded work — only strengthen the value and integrity of your work. It will also keep you on the right side of Good Publication Practice.

Step three: Identify a research question specific to the decision or uncertainty you are targeting

HTA-style PICOs (specification of Population, Intervention, Comparator, and Outcome) can be helpful here; but nothing beats a targeted and specific one-line research question or decision problem. In general, healthcare providers will want to recommend the course of action most likely to lead to the best outcomes for the individual patient, in terms that matter to that patient. Certainly, this should reflect the patient’s likely adherence and persistence, and increasingly, should also include financial outcomes (as far as these can be discerned).

Think about:

• What does “best outcome” mean exactly here for your stakeholder?

• Is the research question financial in any way? It doesn’t have to be. Providers will simply want to recommend the course of action most likely to lead to the best outcomes for the individual patient.

• Do you need to enable comparison of health outcomes in a standardised manner, or across therapy areas, as the QALY and related measures facilitate? Are there other patient-centric measures relevant instead? Given the tolerability challenges, “time on chemotherapy” might be more meaningful in oncology than “progression-free life years.”

• Who does your decision problem relate to? It’s not necessarily patients eligible for a particular treatment. Maybe the question relates to diagnosis in the at-risk population, screening a higher-risk population, patients before/after another intervention (surgery, stem-cell transplant), or patients eligible or ineligible for a comparator.

• What is the decision being modelled? What specifically are the interventions, comparators, and counterfactuals in this decision problem? Is a decision always necessary, or can it be avoided or deferred?

• What are the confounders and effect modifiers that might complicate your ability to answer the question? Do you have methods available to address them or understand their impact?

If you’ve followed so far, I contend that “What is the incremental cost per QALY versus the in-trial comparator over the patient lifetime?” is very likely NOT the research question you’ve arrived at!

Step four: give it an American accent

A British accent can be very popular in the US, especially when performing the role of “evil villain” or “mean reality show judge.” But when performing health economics research in the US, it is important to ensure instead a clear and distinct American accent. The US has plenty of real-world and administrative data sources. It has its own HTA, with its own methods/guidance, if an HTA perspective is important. It is important to make sure you are using data that reflect US clinical practice (screening, diagnosis, monitoring, prior treatments, comparators, subsequent treatments), US patient populations subject to your decision problem, and US costs (resource usage, unit costs).

Step five: Communicate with impact

You have chosen a research question to address a specific decision or uncertainty, and therefore a particular stakeholder group to whom the issue is important. It is now important for you to communicate your messages clearly, with the perspective of that stakeholder firmly in mind. This may also inform the level of detail that may be necessary in explaining your research, provided that any reporting guidelines that may be relevant are met.

There is a risk that the complex modelling or research you may have had to adopt for the US health care system may obscure rather than clarify your insights. After all, defocusing on the average and examining the distribution of economic and health effects across a population will introduce complexity.

Have your stakeholder audience firmly in mind, communicate the messages from your research that are important to them, back it up with data and reasoning from your research, and ensure the right level of technical detail, depending on the likely knowledge or interest of that audience.

Conclusion

Cost-effectiveness and other health economics research are powerful tools in the US, just as they are in single-payer markets with formal HTAs. But their value in the US depends on how they are used. By focusing on real-world decisions, challenges, and uncertainties faced by US stakeholders, health economists can produce insights that genuinely influence practice, policy, and patient outcomes.