Why does generating high-quality evidence matter?
Evidence helps researchers and other stakeholders draw meaningful conclusions about which interventions are the most effective treatment options for specific conditions and patients. Faulty and insufficient evidence could mean that stakeholders may make important treatment decisions based on incorrect data.
The quality of a decision is only as good as the quality of the evidence used to make that decision. High-quality evidence leads to sound and informed health care decisions.
For example, biopharmaceutical companies conduct clinical trials to determine whether a treatment works as expected and monitor medicines that are currently on the market. Evidence also aids in the development of clinical practice guidelines, which are intended to guide provider and patient decisions about appropriate health care for specific clinical circumstances. And payers rely on evidence in determining what treatments will be covered by their health plans.
Where does high-quality evidence come from?
Randomized controlled trials (RCTs) have long been considered the gold standard for evidence, but they cannot address all the answers that stakeholders are seeking about how a treatment works, particularly under real-world conditions or for small patient populations. There is a growing demand for better evidence to demonstrate how treatments work in the real world, and well-designed studies can produce high-quality, real-world evidence and complement RCTs. With greater improvements in technology, the data required for developing real-world evidence is becoming easier to collect and track from sources such as:
- Real-world studies
- Observational studies
- Electronic health records
- Medical claims
- Patient-reported data
- Patient registries
- Mobile technologies
- Social media
How does comparative effectiveness research fit into this picture?
Health care stakeholders need to think beyond traditional studies. Early discussions about comparative effectiveness research (CER) in the United States focused on defining “comparative” and determining the implications for research. Health care stakeholders were talking about the broad array of what should be compared, such as drugs, surgery, devices, physical therapy, primary care doctors versus specialists, how care is delivered, and the relevant comparisons among the varied technologies and services.
To meet this need, the Patient-Centered Outcomes Research Institute (PCORI) was created under the Affordable Care Act to conduct comparative effectiveness research (CER). CER is the conduct and synthesis of research comparing the benefits and harms of different interventions and strategies to prevent, diagnose, treat and monitor health conditions. The goal of CER is to improve health outcomes by developing and disseminating evidence-based information to patients, clinicians, and other decision-makers, responding to their expressed needs, about which interventions are most effective for which patients under specific circumstances. CER is evidence that uses a wide range of research methods, including randomized controlled trials, observational studies, and systematic reviews, a structured assessment of evidence available from multiple primary studies.
Today, the conversation has shifted from looking simply at what should be compared to how comparative studies should be designed to answer the practical questions about “effectiveness” in real-world settings.
Challenges with Evidence
Not all evidence can address every question for every stakeholder. It’s important to understand when evidence is fit for purpose, and it’s why the National Pharmaceutical Council and AcademyHealth developed and tested a conceptual framework that could help close the gaps between the questions explored by researchers and the issues that health care coverage decision-makers must address.
This gap stems from payers traditionally favoring randomized controlled trials over other methods, such as observational studies and indirect treatment comparisons. In particular, though growing demand has emerged for better evidence to demonstrate how treatments work in the real world, studies have shown that few payers use real-world evidence, including data from electronic health records or observational studies, in coverage or formulary decisions.
The framework is intended to help harmonize the evidence payers desire for coverage and formulary decisions with the evidence received from researchers, and help guide researchers as to what types of evidence needs to be developed in the future.