Pharma Needs To Better Understand Patients In Their Lived Environments
By Deborah Borfitz
April 8, 2021 | Social and behavioral science is critical to the generation of real-world evidence (RWE) that reflects the patient perspective, according to Emily Freeman, Ph.D., senior director of patient insights in global R&D at Lundbeck Pharmaceuticals, during a presentation at the recent Summit for Clinical Ops Executives (SCOPE). Information about the usage and potential risks and benefits of a medical product are derived from patient experience data (PED) and real-world data (RWD), and generating that evidence requires more multi-disciplinary expertise than is currently being brought to the table, she says.
Merging psychology, sociology, and anthropology, the social and behavioral science arena focuses on understanding why people behave the way they do, Freeman says. It is already being used by social media platforms, Amazon, Google, Procter & Gamble, and Johnson & Johnson to provide needed context for product development.
The context for PED and RWD collection in clinical development may well involve wearables and sensors rather than a human, she notes. Output from those devices combined with behavior changes, patient-reported outcomes (PROs), the patient experience, and digital biomarkers and therapeutics generate RWD.
Health outcomes are multi-factorial, says Freeman, although social circumstances may contribute between 15% and 40% toward an individual’s response to an intervention and personal behavior between 30% and 50%. Other primary drivers of overall health outcomes are medical care (10% to 20% impact) and, of course, genomics.
Generation of RWE should involve asking questions of the data collected to understand the behavioral component, Freeman says. The RWD collected needs to align with the right technology, database, and outcomes.
One of the “big secrets” of understanding the lived experiences of people, and what matters to them most, is to collect data in their everyday environment, continues Freeman. “Randomized controlled trials may not be truly representative of how people experience disease or the outcomes that matter in their lived environment.”
Qualitative data is needed to “capture the context” of real-world settings, she says, and the U.S. Food and Drug Administration issued guidance to this effect in October 2019. Patient interviews, focus groups, and case studies are among the potential methods for creating that framework.
The three most robust methods for analyzing that data, says Freeman, are ethnography (cultural understanding of disease and how healthcare is delivered and understood), grounded theory (thematically coding collected data to concepts of interest, such as PROs relevant in real-word settings), and discourse analysis (how individuals experience their symptoms/disease and subsequent behaviors).
The analysis exercise results in hypothesis generation from the patient’s perspective, she says. People are not educated to be patients, as she pointed out during a later panel session on understanding patient behavior. “They are told they have a disease and dropped into the system… we need to take a step back and look at the lived experience of patients and wrap services around that.”
Collecting RWD in the lived environment and overlaying that with the clinical care those individuals receive can identify additional endpoints as well as contextualize risk and benefits and better align clinical research and care, Freeman adds. Interactions between physicians and patients have changed with the advent of personalized therapies, wearables, in-home sensors pushing data to patient portals, and diagnostic and therapeutic decision-making aided by clinical decision support tools.
Physicians today can tailor therapies based on all those new data points, continues Freeman, and that has implications for medical product development, regulatory approvals, and payer reimbursement.