The argument emerges from a growing mismatch between the architecture of medical evidence and the reality of modern patients. Clinical guidelines are overwhelmingly built for single diseases: one condition, one evidence base, one optimised pathway. But the patients walking into general practice and general internal medicine increasingly carry several long-term conditions at once, often bridging physical and mental health, cardiovascular risk, chronic pain, frailty, and social vulnerability. Large analyses of electronic health records show that multimorbidity clusters into recurring patterns that cut across these domains, and that the condition is associated with poorer function, worse quality of life, higher healthcare use, and earlier onset in deprived communities. For such a patient, the clinical problem is not only disease burden but healthcare burden: the appointments, tests, self-monitoring, medications, side effects, and contradictory advice that accumulate when each disease is managed by its own logic.

Consider a patient with type 2 diabetes, osteoarthritis, depression, hypertension, insomnia, and chronic kidney disease. The generalist seeing this person is not simply applying six evidence bases in sequence. The authors argue that the clinician is reconciling six partially incompatible logics of care, each with its own targets, monitoring schedules, and pharmacological demands. A diabetes guideline may push tight glycaemic control; the kidney disease may complicate the drugs used to achieve it; the depression may undermine the self-management every other condition depends on; the osteoarthritis may make exercise, the universal recommendation, painful. The question that actually matters in the consultation is not what each guideline advises, but what the next best thing to do for this person now happens to be.

That question becomes urgent when the mathematics of prevention is examined honestly. Modelling work cited in the Perspective shows that ignoring competing mortality can substantially overestimate the expected benefit of preventive interventions in older adults and people with multimorbidity. A statin, a blood pressure tablet, or a screening test may offer a genuine relative risk reduction, but if the competing risks of age, frailty, and other diseases intervene first, the absolute benefit shrinks, while the burden of taking the treatment remains fully present. The authors also highlight direct treatment disutility, the harm and inconvenience a treatment imposes in its own right, which can flip the balance between benefit and harm. Evidence, in other words, does not speak for itself; it must be adjudicated against life expectancy, burden, and the patient’s own goals.

And patients, it turns out, often adjudicate differently from their doctors. A systematic mixed-studies review found that patients with multimorbidity commonly prioritise symptom relief and the preservation of function and independence, whereas clinicians tend to prioritise longer-term risk reduction and surrogate markers. This divergence is not a failure of communication to be corrected but a structural feature of complex care that must be made visible. The Perspective is careful to distinguish prioritisation from its neighbouring concepts: it is not shared decision-making, though shared decision-making safeguards it; not deprescribing, though deprescribing is one of its tools; not treatment burden measurement, though burden is one of its inputs; and not Choosing Wisely, though it extends that movement’s logic. Its distinctive work is deciding what should come first now, what can wait, and what should stop.

Crucially, the authors insist that generalists already perform this work, but implicitly and without a language that grants it legitimacy. Qualitative studies of physicians caring for complex patients show that their decisions are shaped by disease interactions, patient resources, consultation constraints, organisational pressures, continuity of relationship, and the effort to steer care toward a workable goal. Physicians report that patient values matter, yet are not always elicited directly and are difficult to reconcile with protocols, multidisciplinary teams, and families. Even committed clinicians describe limited time and systems that reward the completion of checklists far more readily than the exercise of judgment. The result is a paradox the authors name directly: prioritisation is central to good generalist care, yet it remains under-described, under-taught, and under-valued.

The Perspective does not leave the concept abstract. It points to a growing body of implementation research that moves goal-oriented care from theory toward operational reality. Grudniewicz and colleagues have proposed strengthening the Chronic Care Model by subordinating disease management to what matters most to the person over time, rather than abandoning disease management altogether. Tinetti and colleagues tested a patient priorities-aligned care model for older adults with multiple conditions and reported potentially favourable differences in treatment burden and shared prescribing decisions compared with usual care, although the differences did not reach statistical significance. Schuttner and colleagues used multicriteria decision analysis to demonstrate something clinically profound: the right next step changes depending on whether the patient’s aim is mortality reduction, symptom relief, or preserved function. Prioritisation, in other words, is not a fixed ranking but a dynamic computation that depends on the goal.

Making prioritisation explicit, the authors argue, requires deliberate elicitation of what matters now. They describe a simple clinical sequence: identify what matters most to the patient at this moment, select the next action with the greatest likely benefit and lowest burden relative to that goal, and actively stop, simplify, or defer care that does not serve it. Supporting tools are emerging. Person-centred care approaches built around extended consultations, personalised goal setting, and planned follow-up have been developed in general practice, and one research group has even produced a prioritisation algorithm to identify which patients are most likely to benefit from a longer, goal-setting appointment in time-constrained settings. Communication and goal-setting tools such as structured wellbeing journals have shown promise in supporting more meaningful care-planning conversations with older adults. The lesson, the authors stress, is not that every consultation must become long or formalised, but that a good consultation may sometimes be one in which fewer targets are addressed and the patient leaves with a clearer plan, lower burden, and fewer contradictory demands.

The hardest test of prioritisation is whether it leads to de-intensification. Adding treatment is easy to justify, because each addition can be defended by a disease-specific rationale; stopping requires accepting responsibility for uncertainty. Yet the authors argue that prioritisation which never results in stopping is performative rather than real. The evidence here is genuinely mixed, and they are candid about it. Deprescribing interventions generally reduce medication counts, and a meta-analysis found benefits on potentially inappropriate prescribing and adverse drug reactions in older adults, but evidence for broader outcomes remains inconsistent, particularly in vulnerable multimorbid populations. Structured medication reviews, meanwhile, are hampered by time pressure, organisational complexity, unclear roles, and poor data integration, according to qualitative findings from the DynAIRx study. This is the landscape in which generalists operate: enough evidence to justify action, never enough to eliminate judgment.

The Perspective closes with a warning about how the SPPiRE analysis complicates even well-intentioned priority elicitation: when general practitioners prioritised pain, opioid intensification became more likely despite guideline concerns about chronic pain pharmacotherapy in older adults. Eliciting priorities, the authors conclude, is necessary but not sufficient; priorities must still be interpreted through a generalist lens weighing immediate suffering against long-term harm. The wider implications reach into education, where trainees should learn to justify not only what they do but what they decline to do; into quality measurement, which should reward goal-concordant sequencing and burden reduction rather than indiscriminate completion; and into system design, where altered specialist treatments should be documented and reconciled so that patients are not left as messengers between competing experts. In complexity, the authors write, the central clinical task is deciding what deserves attention first, what can wait, and what no longer serves the patient. Prioritisation, they argue, is the treatment decision.

Subject of Research: Prioritisation as a clinical intervention in generalist care for patients with multimorbidity

Article Title: Prioritisation Is Treatment: What Generalists Do When Guidelines Collide

Article References: Jerjes, W., & Majeed, A. (2026). Prioritisation Is Treatment: What Generalists Do When Guidelines Collide. Journal of General Internal Medicine. https://doi.org/10.1007/s11606-026-10861-1

Image Credits: AI Generated

DOI: 10.1007/s11606-026-10861-1

Keywords: generalism, multimorbidity, prioritisation, clinical guidelines, polypharmacy, deprescribing, treatment burden, shared decision-making, goal-oriented care, primary care, Choosing Wisely, patient priorities

The research, known as the HERON study, was led by the Nuffield Department of Primary Care Health Sciences at the University of Oxford together with the NIHR HealthTech Research Centre in Community Healthcare. Over five months, from June to November 2025, the team surveyed 314 people across all four nations of the United Kingdom, asking them to describe the biggest problems in respiratory care and the places where technology might help. The responses amounted to nearly 1,300 distinct challenges and ideas, which the researchers then sorted and refined into 73 separate areas where a device, app, test or data system could plausibly make a difference to care.

What happened next is what gives the study its force. Rather than simply publishing a wish list, the team checked each of the 73 areas against what already exists, ranging from early laboratory prototypes to products currently on sale. The results were stark. In 52 of the 73 areas, they found nothing adequate on the market or in development. A further 21 areas were only partly covered by existing technology. And not a single area met the demanding bar the study set itself: a suitable solution already in routine use at scale across the UK. The authors note that the picture may have shifted in the time since they completed their review, but the overall message is difficult to escape. The technology that patients and clinicians want most is, for the most part, not the technology being built.

This mismatch matters because the scale of respiratory disease in the UK is enormous. Around one in five people lives with a lung condition, making respiratory illness the third leading cause of death in the country and responsible for more than 700,000 hospital admissions each year. The burden falls disproportionately on poorer communities, where air quality, housing conditions and access to care combine to worsen outcomes, yet research funding has not kept pace with the scale of the problem. Meanwhile, the market for respiratory technology has grown quickly, but the products emerging from it have tended to follow what is technically possible rather than what users have asked for. Cutting-edge features, the study’s authors observe, do not always match what the people using those products actually want or need.

To break that pattern, the Oxford team adapted a method with a strong track record in a different field. The James Lind Alliance has long brought patients and clinicians together to agree which research questions matter most, a process known as priority setting. HERON turned that same participatory logic onto technology itself, defining the term broadly to include anything from a home lung-function test to a smartphone app to the data infrastructure behind a virtual ward. As far as the authors are aware, no one had previously described a systematic method of this kind for setting HealthTech priorities in chronic respiratory disease, making the study a methodological first as well as a practical roadmap.

The researchers were also deliberate about who they reached. Online surveys, however convenient, systematically miss many of the people most affected by lung disease, including those without reliable internet access, those with low literacy and those whose lives are consumed by managing illness. So alongside the survey, the team went into the community, attending pulmonary rehabilitation classes, a singing group for people living with breathlessness and a respiratory service for people who are homeless. These sessions took place in Greater Manchester, Norwich, Bristol, Nottingham and Weston-super-Mare, and were kept deliberately informal to lower the barriers to participation. The researchers did not collect demographic details at these sessions, so they cannot measure precisely how far they succeeded in broadening the sample, an honest limitation they acknowledge openly.

In March 2026, the longlist was put to the test. Twenty-three patients, carers and clinicians spent a day together working through the 73 areas and narrowing them down to a final top 20. The priorities span the whole journey of living with lung disease, from screening people who are at risk before symptoms become serious, through day-to-day management, to helping people maintain their gains after a course of pulmonary rehabilitation ends, a point at which support often abruptly stops. Some of the most striking items are strikingly modest in conception: an inhaler that shows when it is running out, oxygen equipment that can leave the house, a tool that helps separate anxiety from the onset of an exacerbation. Each addresses a failure point that patients describe constantly and that current devices simply ignore.

One demand cut across all twenty priorities, and the authors present it as the study’s central design principle. Whatever gets built has to work for someone with poor eyesight, unsteady hands or no confidence with a smartphone, and it has to be affordable to run, both for the National Health Service and for the patient. Accessibility, usability and equity, they argue, cannot be retrofitted late in development or bolted on as an afterthought; they need to be built in from the very start. Dr Helen Ashdown, an academic general practitioner at the University of Oxford who led the study, said that there is enormous potential for technology to improve respiratory care, but that simply developing more technology is not enough. HERON, she explained, identifies not only where the eventual users of technology think innovation could make the greatest difference, but also what they need from those technologies if they are going to work in real life.

The roadmap is already being put to work. The National Institute for Health and Care Research has opened its latest Invention for Innovation, or i4i FAST, funding opportunity for chronic respiratory health technology, and it explicitly encourages applicants to address the HERON priorities in their applications. That means the list is not merely an academic exercise but a live filter through which public research money will flow. The Respiratory Transformation Partnership, a national collaboration between the NHS, government and industry established to improve asthma and COPD care, is also supporting the findings, which will inform its considerations and help connect promising technologies with the needs of patients and respiratory services. Dr Jonathan Fuld, National Clinical Director for Respiratory Disease at NHS England and Chair of the partnership, said that patients should be at the heart of how new respiratory technologies are developed, and that by aligning innovation support with these priorities there is an opportunity to help promising technologies progress from development and evaluation through to adoption in the NHS.

The study was funded by LifeArc, a medical research charity, and its ambitions extend beyond the chest clinic. The method itself, the authors point out, is not tied to lungs. The same structured process of gathering challenges from patients, carers and clinicians, mapping them against the existing technology landscape and distilling a ranked set of priorities could be applied wherever HealthTech priorities need setting, from diabetes to dementia. If it catches on, the HERON study may be remembered less for its list of twenty technologies than for the question it forces the industry to answer before writing a single line of code or moulding a single prototype: who asked for this, and what did they actually say they needed? For the one in five people in the UK living with lung disease, and the clinicians trying to keep them out of hospital, the answer has never been spelled out so clearly.

Subject of Research: Patient and clinician priorities for respiratory health technology development in the UK

Article Title: Respiratory patients and clinicians name the 20 technologies they want most – and could transform NHS lung care

Article References: Respiratory patients and clinicians name the 20 technologies they want most – and could transform NHS lung care. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: respiratory disease, health technology, HERON study, University of Oxford, Thorax, patient priorities, NHS, inhalers, COPD, asthma, medical devices, NIHR