Written by Technical Team | Last updated 24.10.2025 | 13 minute read
Co-design, sometimes called participatory design or user-centred co-creation, is more than just asking clinicians and patients what they want from a new app, portal or clinical system. At its best, it is a structured, intentional way of designing digital health tools with the people who will actually use them, at every stage of development — from defining the problem, to shaping features, to testing real-world usability. In a landscape where digital health products are increasingly responsible for triage decisions, medication safety, waiting list management and remote monitoring, the stakes are simply too high to build systems in isolation and hope they “land”. Co-design makes sure they do more than land. It helps them work.
Digital health fails most often not due to lack of technical capability but due to misalignment with clinical reality and human context. A seemingly elegant virtual ward dashboard can quietly become unusable if it takes twelve clicks to record an escalation, or if it duplicates data that is already recorded elsewhere in the electronic patient record. A beautifully branded long-term condition self-management app can be abandoned within days if it does not reflect what it’s actually like to live with fluctuating symptoms and fatigue. These failures are not trivial; they lead to clinician frustration, poor data quality, low adoption and, ultimately, poorer patient outcomes. Co-design addresses this risk head-on by treating clinicians and patients as expert contributors, not end-users to be “trained later”.
Co-design is especially critical in digital health because healthcare is not a normal market. Most digital products are designed for a buyer who is also the user (for instance, productivity software used by the same team that chose it). But in health, procurement and use are often separated. A regional commissioning body might approve a remote monitoring platform for heart failure, but it is respiratory nurses in a community team who must onboard patients, interpret alerts and incorporate that data into a stretched clinic schedule. Meanwhile, the patient is expected to trust the system, adhere to it, and change their behaviour based on it. Co-design narrows that procurement–practice gap by ensuring that what is specified, purchased and rolled out is grounded in lived workflows and lived experience.
There is also a safety and governance dimension. Clinical safety standards ask that digital tools minimise the risk of harm. But risk is not only clinical in the traditional sense (e.g. medication errors); it is operational, emotional and equity-related. For example: does the interface make it too easy to accidentally discharge the wrong patient? Does the tone of automated messaging cause unnecessary anxiety? Does the service assume access to a smartphone, exclude non-English speakers, or quietly punish people with poor digital confidence? Co-design surfaces these risks early, when they can still be influenced by design decisions rather than patched later with policy workarounds and apologetic training slides.
Finally, co-design matters because it builds trust. Clinicians are rightly wary of digital change that feels imposed and unproven, particularly when it appears to add tasks with no obvious clinical benefit. Patients are rightly wary of being “digitally managed” rather than cared for. When people can see their feedback directly shaping the product — “we asked for this,” “we said this wording was confusing and it changed,” “we said follow-up calls after 6pm were stressful and now the service avoids them” — trust increases. Trust drives adoption. Adoption drives impact. In that sense, co-design is not a soft nice-to-have activity; it is one of the most reliable levers for delivering meaningful, scalable digital health transformation.
Bringing clinicians and patients directly into the design process delivers a series of practical, measurable benefits to digital health programmes. The first and most obvious is usability. When clinicians and patients actively shape the interface, language and workflow, the end product is naturally easier to use because it has been created around real patterns of behaviour rather than hypothetical “ideal users”. This directly reduces training overhead, onboarding friction and resistance at go-live. It also reduces “shadow work” — the unofficial spreadsheets, workarounds and note-taking rituals that staff develop when a system does not truly fit the job. Shadow work is expensive, brittle and unsafe. Co-designed tools tend to replace it rather than generate more of it.
Another powerful benefit is accelerated adoption at scale. Many digital products in health do well in pilot but stall when expanded to wider populations. One common reason is that the design never captured enough diversity in settings, conditions or demographics to be robust. If the pilot group was digitally confident, monolingual, and already engaged with their care, the product can look artificially successful. Co-design, done well, deliberately includes variation: rural as well as urban teams, high and low bandwidth environments, people with multiple long-term conditions, people with sensory impairments, people acting as unpaid carers. This creates resilience in the design. Instead of breaking when rolled out beyond the “friendly” pilot site, the service is already shaped to cope with difference, which makes commissioners more confident to invest and clinicians more confident to recommend.
The biggest mistake teams make is treating clinician input as a single workshop, typically held once requirements are “mostly finalised”. That is not co-design. That is consultation theatre. Clinician engagement must be continuous, structured and respectful of clinical time, or it will collapse under competing pressures such as rota gaps, waiting lists and winter pressures. A practical approach is to embed clinicians in the digital design process in lightweight but high-impact ways, rather than pulling them into long generic meetings that feel detached from their day job.
One effective model is to identify and support “clinical design partners”. These are practising clinicians — nurses, AHPs, consultants, GPs, healthcare assistants, pharmacists — who are given explicit protected time and recognition to contribute to product development. Crucially, they are not there just to give opinions; they are there to map the real workflow and real failure points. They narrate what actually happens on a hectic ward round, at 02:00 in an out-of-hours triage call, or in the five minutes before a patient walks into a consultation. Designers and engineers can rarely see these moments unfiltered. Clinical design partners can. Over time, this relationship creates design literacy in clinicians and clinical literacy in designers, which is an extraordinary asset for any organisation serious about digital service quality.
To translate clinician expertise into design decisions, teams need methods that go beyond “what do you think of this screen?”. Useful techniques include journey mapping (stepping through an end-to-end clinical pathway and noting where digital support genuinely helps versus where it intrudes), failure mode exploration (asking “where could this go wrong, and what would that cost?”), and paper or clickable prototyping that clinicians can react to in a low-risk environment. Done well, those activities are fast, visual and energising, rather than bureaucratic. They also expose hidden complexity, such as multiple parallel record-keeping systems, unwritten escalation protocols, or informal workarounds that keep the service safe but invisible to managers.
It is also vital to recognise that “clinicians” are not a single audience. Junior doctors interact with systems differently to consultants, because they are often the ones entering the bulk of data. Ward nurses experience digital tools differently to outpatient nurses, because acuity, staffing ratio and physical movement patterns are different. Community physiotherapists have different environmental constraints to pharmacists running medication reviews in care homes. Treating clinicians as a homogeneous advisory panel leads to blunt designs that work for nobody particularly well. Segmenting perspectives and deliberately sampling across roles avoids that trap.
There are several practical enablers that help clinicians feel that co-design is worthwhile and not just extra work:
When these enablers are in place, clinicians stop seeing digital as “IT’s project” and start seeing it as “our service”. That shift is cultural gold. It means clinicians will champion adoption, defend the design intent when it is misunderstood, and help refine the product in live use rather than quietly disengaging. It also means the digital team gains rapid access to real-world feedback without having to fight for attention every time something needs validating.
If clinician engagement keeps a service clinically safe and operationally realistic, patient engagement keeps it humane, comprehensible and empowering. Yet involving patients in digital co-design is often treated as risky or tokenistic. Teams worry about data confidentiality, about saying the wrong thing, about being accused of bias, or about being overwhelmed by individual stories that are hard to generalise. These are understandable concerns, but excluding patients creates a far greater risk: you end up designing a service about people rather than for them. That almost always leads to low uptake, mistrust and widening health inequality.
The first ethical principle is respect for lived expertise. Patients, unpaid carers and families are experts in things clinicians often only glimpse: the pattern of side effects across a whole day rather than a clinic snapshot; the anxiety of waiting for unstructured test results; the exhaustion of having to repeat the same basic information to every new professional; the dread of digital forms that time out or assume perfect recall of medication doses. When digital services ignore these realities, we accidentally design cruelty. When we listen to them, we design care.
Involving patients well means going beyond “user interviews with polite middle-class volunteers who are confident on Zoom”. It means deliberately seeking out and compensating a range of voices. People with limited English proficiency. People with low digital literacy. People who are disabled, neurodivergent or cognitively impaired. People who are in unstable housing or rural isolation. People who are full-time carers for partners, parents or children and therefore experience “healthcare” as a constant logistical negotiation rather than a sequence of appointments. Their needs are not edge cases; they are part of the real service population. If a digital product only works for the easiest segment, it is not fit for purpose in a public health system.
In practical terms, good patient co-design tends to include:
Transparency is also central. Patients need to understand not just “what do you think of this?” but “what will happen with what you tell us?”. Will their comments be anonymised? Will they affect their care? Will they be shared with commissioners, vendors, research teams? Clear, plain-language consent builds honesty, and honesty is what surfaces the uncomfortable truths that design teams most need to hear. For instance: “The tone of this automated message makes me feel like I’m being told off,” or “I wouldn’t report my smoking here because I’m scared it will affect how I get seen,” or “If you send this alert to my daughter rather than me, I’ll feel like I’m losing independence.” Those statements are design gold. They are early warnings about acceptance, dignity and safeguarding that no analytics dashboard will show you until it is far too late.
Finally, inclusivity is not just about who is in the room. It is about what power they hold in that room. If the only acceptable type of feedback is “minor tweaks to wording”, you are not doing co-design; you are doing copy-edit approval. True co-design means allowing patients and carers to question the premise. Do we even need this feature? Does this step add anxiety for no clinical gain? Why is the burden of data entry being pushed onto me rather than shared with the clinical team? Those questions can feel uncomfortable, especially to product owners with roadmaps and delivery milestones. But this discomfort is productive. It prevents digital health services from quietly shifting administrative and emotional labour onto patients and families under the banner of “empowerment”, and instead keeps the focus on genuine partnership.
One of the myths surrounding co-design in digital health is that it is a discovery phase activity, something you “tick off” before build and then move on from. In reality, co-design is an ongoing discipline. Clinical pathways evolve, policy evolves, public expectations evolve, and technology certainly evolves. A product that felt empowering and intuitive in year one can feel outdated, paternalistic or burdensome by year three if it is not continuously re-shaped with its users. The goal is not just to launch a tool but to steward a service.
Measuring success, therefore, has to include more than traditional implementation metrics such as log-ins, number of referrals, or time saved per task. Those quantitative indicators matter, but they are not the whole story. You also need to understand qualitative impact: Do clinicians feel safer delivering care with this tool than without it? Do they trust the data it produces enough to act on it? Do patients feel more in control, better informed, more respected? Do carers feel supported rather than surveilled? Are people from previously under-served groups actually using the service, and if not, why not? These are not “soft” questions. They go straight to whether the digital service is improving outcomes or quietly deepening inequality.
The most sustainable digital health organisations build co-design into their normal operating rhythm. They create lightweight mechanisms for continuous feedback: regular structured check-ins with clinical design partners; patient advisory panels that are compensated and briefed in plain language; quick-turn usability testing every time a meaningful feature changes; clear release notes that explain not only what has changed but why it changed, referencing the voices that shaped it. This culture sends a powerful message: the product is not finished, because care is not static. When clinicians and patients can see that message lived rather than just stated, they are far more willing to stay engaged, to surface emerging risks early, and to advocate for the service within their networks.
In the end, co-design matters in digital health design because it aligns the system around what actually helps. It prevents digital tools becoming yet another layer of friction in already stretched services. It protects safety by surfacing risks early. It protects dignity by treating lived experience as expertise, not anecdote. And it turns “users” into partners, which is the only honest route to digital health services that are safe, adoptable, caring and scalable.
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