For years, researchers have urged medicine to listen more closely to patients—what matters to them, how they feel, and what everyday functioning looks like when a condition takes over. Most of that effort shows up in clinical trials as patient-reported outcome measures, or PROMs. They’re designed to turn lived experience into data you can analyze.
But there’s a catch. PROMs sit right at the intersection of two competing forces in healthcare: patient-centred care and standardization. The same thing that makes PROMs useful for regulators and comparisons across studies—consistency—can also flatten what’s going on inside a person. Misryoum editorial desk noted that without context, numerical results from PROMs can struggle to support the kind of individual care clinicians try to provide.
The argument, laid out in a recent discussion, is not that PROMs are wrong. It’s more like…PROMs alone can’t answer the questions patients often ask in real life: why are things changing, and what does “better” mean for someone living their day-to-day. Narrative data—written and spoken accounts of experience—can add that missing texture. It’s the difference between a rating and a story you can actually understand.
PROMs aren’t quick or casual to build. According to the discussion, developing a PROM is a “sophisticated process” that can include literature reviews, in-depth interviews, focus groups, cognitive interviews, and clinical observation. After that comes extensive psychometric testing to establish reliability and validity. Misryoum newsroom reported that trials often include at least one PROM to capture how people feel or function, and in some areas—irritable bowel syndrome is one example—PROMs can even be used as primary indicators of treatment benefit.
In the most common setup, everyone completes the same so-called “static” PROM, and then researchers look at change from baseline, like mean change within each treatment group or the proportion of participants who cross a threshold for symptom improvement or worsening. It’s efficient. It’s also built on a big assumption: that all patients have the same underlying experiences behind the concept the measure is trying to capture.
That’s where the “mixed-method approach” comes in. PROM data can help develop and approve treatments while also supporting consultations—helping healthcare teams answer “how will it make me feel?” and “will I be able to do x?” Yet, Misryoum analysis indicates that PROM data alone often can’t tackle the follow-up questions: “why does it do that?” or “how do people cope with it.” To get at those, the discussion calls for narrative evidence—typically collected through embedded interviews at study entry and/or exit, or gathered outside trials to understand general experiences, priorities, needs, satisfaction, reasons for non-adherence, and patient preferences that are often highly individual.
The point isn’t to collect stories for their own sake. The piece stresses that the core research question should drive the choice of methods, and that qualitative work should supplement quantitative findings—either by adding depth to what PROMs can’t capture or by exploring things PROMs never touch. There’s a clinical realism here too: imagine a follow-up appointment where the PROM score looks stable, but a patient quietly mentions that the worst part isn’t the pain, it’s the unpredictability. Maybe that’s the moment a number can’t carry on its own—like the slight smell of antiseptic in a clinic hallway, lingering while someone tries to explain what “functioning” really means.
Misryoum editorial team stated the takeaway is simple, even if the implementation isn’t: researchers should engage in mixed methods research that combines qualitative and quantitative tools to understand patient expectations, perspectives, and experiences—during trials and in clinical practice. The discussion encourages careful, hypothesis-led design, and then, basically, asks for the fuller picture: not just how patients score, but what those scores represent in the messy reality of living with illness.
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