Essential reading for advancing patient experience data research

Patient experience data (PED) captures patients’ experiences with a disease, condition or treatment, including symptoms, impacts on daily life, treatment experiences, needs, priorities and preferences. PED can help identify unmet needs, inform patient-focused clinical trial endpoints and generate evidence that supports regulatory, payer, healthcare professional and patient decision-making. Patient-centric endpoints play a central role in enabling innovative approaches to quantifying treatment benefit across a wide range of therapeutic areas.

Start by identifying the meaningful aspects of health that matter to patients and defining the concepts of interest to be measured. Fit-for-purpose clinical outcome assessments (COAs) or digital measures can then translate these concepts into endpoints. Endpoint development should also consider the type and timing of the endpoint, its position in the endpoint hierarchy and the estimand to ensure the treatment effect is meaningful and interpretable.

A COA is fit for purpose when it adequately measures the intended concept of interest, reflects a meaningful aspect of health and is supported by evidence appropriate to its intended context of use. This includes evidence supporting content validity, reliability, ability to detect change and interpretation of scores. A COA that is fit for one context of use should not automatically be assumed to be fit for another.

Digital measures, captured through wearables, sensors or mobile devices, add value when they fill a measurement gap: a meaningful aspect of health that is currently unmeasurable, or that existing methods cannot capture reliably or in real-world conditions. Like any COA, they must be grounded in clear COA principles. In addition, they should be verified, analytically valid (the algorithm does what it claims) and clinically valid. They also need strong evidence of usability in the intended setting, and interpretable scores or changes.

COA scores are interpreted using meaningful score thresholds, unique for each instrument and domain. Meaningful within-patient change (MWPC) defines the change in a score that matters to an individual patient. Meaningful score regions (MSRs) link score ranges to severity states, such as mild, moderate or severe. Both are estimated using anchor-based methods, supported by distribution-based methods and graphical analyses, and triangulated across evidence.

Meaningful within-person change (MWPC) reflects the amount of change in a COA score that is considered relevant to an individual patient’s experience. MWPC thresholds can be estimated using anchor-based approaches supported by distribution-based methods and graphical analyses, with multiple sources of evidence triangulated to support interpretation.

A PED strategy should consider regulatory and health technology assessment (HTA) evidence needs early in clinical development because decision-makers may value different outcomes and forms of evidence. Aligning PED measures, endpoints and analyses with anticipated regulatory and HTA requirements can increase the relevance of the evidence across clinical development, regulatory review and market access.

Multinational PED research requires more than translating assessments into additional languages. Sponsors should consider COA licensing, translation, cultural adaptation and linguistic validation, and electronic implementation. Planning these interdependent activities early can help preserve the validity and comparability of PED collected across countries.

PED strategy should begin early and evolve throughout the product development lifecycle. A PED roadmap can define the evidence needed at each stage, from understanding disease experience and selecting measures to validating endpoints, supporting regulatory and HTA submissions, and communicating patient value after launch. The PED roadmap should align with the broader integrated evidence generation plan.