Optimizing the value of observational studies
Chris Pashos and Krista Payne of United BioSource Corporation explore observational or "non-interventional" studies and how they can enhance the clinical development and commercialization process.
As healthcare delivery and financing continues to evolve globally, life sciences companies are faced with the increasing demand for data, including identification of unmet need and evidence of value being delivered, from various stakeholders. Regulators, physicians, hospitals and healthcare providers, payers, health technology assessment authorities, patients, and advocacy organizations are among the entities seeking data from observational studies. These studies can provide additional information about the burden of disease, variations in clinical practice patterns, and the resulting clinical, patient-centered, and economic outcomes. Organizations as diverse as the Food and Drug Administration (FDA), National Institutes of Health (NIH), American College of Cardiology (ACC), the United Kingdom's National Institute for Health and Care Excellence (NICE), and the French Haute Autorité de Santé (HAS), have recognized that such information must be considered in addition to the data developed in the controlled clinical trial environment.
Observational or "non-interventional" studies can enhance the clinical development and commercialization process supporting new diagnostics, medicines, biologics, and medical devices, and these studies can help make that process more efficient and effective. However, because observational studies can, in principle, accomplish many different things, they also can vary greatly with respect to research objectives, sources and types of data being collected, relevant audiences, and alternative communication strategies. Therefore, it is critical that they are designed with clear, feasible objectives and executed efficiently and effectively. It's also important that these studies have a comprehensive means to communicate meaningful findings. Because the findings of observational studies are not typically as readily apparent as the findings of randomized clinical trials, it is critical that the analysis and dissemination strategy be developed carefully and implemented effectively in a timely manner.
Range of Uses
Prospective observational studies done in parallel with Phase I, II or early III clinical trials can help establish the unmet burden of a disease and identify deficiencies in current clinical practice or areas that need to be improved or addressed. Having these data on hand can help inform the design of subsequent Phase II or III trials to evaluate whether and how the new product affects those areas of need. Once a new diagnostic, medicine, biologic or medical device has been approved, prospective observational studies also offer the opportunity to assess its use and performance in the real, non-controlled world of heterogeneous patients being managed in different clinical settings in various geographic locations. Prospective observational studies can include more patients than are commonly enrolled in Phase I through III programs, thereby providing the opportunity to better define the safety and effectiveness profile of the product and demonstrate its real value relative to comparators. The opportunity to have longitudinal data on patients in usual care practice also offers a counterpoint to, or context for, case studies, small case series, or other real world data that by definition are more limited in comparison.
Planning
Observational studies can focus narrowly or broadly on various aspects of the disease, medical practice and healthcare resource use, as well as outcomes related to safety and effectiveness, as perceived by the clinician and the patient. Given the potential for such broad coverage and diverse objectives, it is imperative to obtain consensus within the sponsor organization and among collaborating physicians on what research needs the study will address and how it will do so. In addition, those in the research partnership must ensure that appropriate levels of human and financial resources are devoted to the effort, and that the objectives can be met with those resources in a timely manner.
Analysis and Communication
Prospective observational studies allow the researcher and sponsor organization to meet the needs for evidence of many different external audiences. Whether the goal is to understand the unmet needs of current practice and outcomes, or to elucidate the comparative value of a new medicine, healthcare technology, or service, the data need to be appropriately analyzed and effectively communicated in ways that meaningfully reach the various audiences including regulators, payers, providers, patients, and technology assessors. To do so, relevant data need to be paired with appropriate communication venues in a timely and strategic manner. The type of audience will determine how findings are communicated. Designing and implementing an effective communication strategy is just as important as designing and executing the study. Less than optimal performance on any of those areas will reduce the value of the entire research effort.
It is critical to always maintain clear focus on the goals of the study, and use the analysis and communications to ensure that those goals are met. Such communications are an opportunity to interact and successfully collaborate with external stakeholders about their needs and how the study findings are meaningful in addressing those needs.
Key Lessons
To be done well, prospective observational studies require considerable effort, time and financial investment. When done well, they produce valuable information in a timely manner for the sponsor and its many key external audiences. To ensure that a prospective observational research program delivers value, researchers must:
• Plan carefully and strategically
• Have explicit consensus within the sponsor organization and among collaborators about study objectives
• Have clear priorities for data collection
• Match research goals with appropriate levels of human and financial resources to ensure study success
• Align the investment with the need and opportunity
• Ensure that analyses are conducted in a rigorous fashion
• Optimize communications so that relevant external audiences better understand unmet needs and product real world value
About the authors:
About Chris Pashos
Chris Pashos, PhD, has served as Vice President, Safety, Epidemiology, Registries, and Risk Management at UBC. Dr. Pashos leads and actively participates in international collaborations with clinicians and researchers to assess the burden of disease, and the use, outcomes, and value of medicines, medical devices, and other healthcare technologies and services. His work enables sponsors to understand the comprehensive value, including the benefits and risks, of products and services, and to communicate that value to multiple provider, payer, policy, and patient audiences, thereby promoting optimal access to appropriate care. Dr. Pashos has designed and implemented prospective observational studies, such as patient registries, involving hundreds of thousands of patients. His real-world research expertise also extends to retrospective database analyses, clinical-economic models to present outcomes of therapeutic alternatives; and surveys on the use of healthcare resources and the patient-reported outcomes of that care. He has worked in numerous therapeutic areas, notably hematology/oncology, cardio-metabolic diseases, urology, rare diseases, and women's health.
Dr. Pashos holds a Ph.D. and master's degree in public policy from Harvard University and a Bachelor of Science with Distinction from the United States Naval Academy.
About Krista Payne
Krista Payne is a Principal Scientific Consultant and Executive Director of Value Demonstration, at United BioSource Corporation (UBC). This department is responsible for the conceptualization and design of strategic evidence gathering programs, and real-world observational studies in support of market access and product reimbursement. Routinely, value demonstration studies have been designed to provide tailored datasets to populate health economic models or other quantitative and qualitative burden of illness evaluations.
She can be reached at Krista.Payne@ubc.com.
Closing thought: How can we optimize the value of observational studies?
