An ageing population, multimorbidity, frailty and polypharmacy are all contributing to an increase in the complexity of patients managed by the NHS in the UK and by health systems in other countries. Moreover, the interaction of these factors can lead to a “complexity cycle” which further increases the risks to patients and the pressures on the NHS.
The convergence of these factors has shifted the NHS landscape from managing isolated illnesses to navigating patients with multiple complex health needs. This complexity arises because frail patients with multiple long-term conditions often require numerous medications, which significantly increases the risk of adverse drug interactions and hospitalisations.
Consequently, the NHS is aiming to move away from traditional, single-disease specialist models toward integrated, person-centred care that prioritises holistic assessment and strategic deprescribing to maintain patient independence and safety.
To support this transition, we also need to move away from single-disease trials toward studies that include complex, older populations with multimorbidity. Many clinical guidelines are based on younger, healthier cohorts; making it difficult to use them appropriately for people with frailty and polypharmacy.
Managing uncertainty is a core skill in primary care and other frontline clinical specialties such as emergency medicine where patients frequently present with early, evolving or non-specific symptoms that do not fit clear diagnostic categories. Rather than eliminating uncertainty, safe practice depends on recognising it, communicating transparently with patients and colleagues, and managing risk over time.
This is especially important for serious illnesses that may initially present with vague or common symptoms where premature or inappropriate reassurance can delay diagnosis. An example is ovarian cancer which can present with symptoms such as abdominal pain and bloating; and where there is overlap with other, less serious illnesses such as irritable bowel syndrome/
Safe management in patients with such presentations begins with a structured clinical assessment that considers red flags, comorbidities and the patient’s clinical and social contexts; alongside an explicit acknowledgement of diagnostic uncertainty. Shared decision-making is crucial: clinicians should explain what is known, what is uncertain, and why a “watchful waiting” approach may be appropriate. Clear safety netting then becomes a key risk-management tool.
Effective safety netting includes: specifying which symptoms should prompt concern; giving clear advice to patients on when and how to seek further help; setting an expected time course for symptom resolution; and arranging planned follow-up where appropriate. Documenting this advice and ensuring it is understood – particularly in patients with language barriers, health literacy challenges or high levels of anxiety – is essential. Used well, safety netting transforms uncertainty from a source of risk into an active, patient-centred strategy for safe care.
Safety netting is the primary risk-management tool that transforms passive waiting into an active, patient-centred strategy.
Stage
Action
Symptom Specificity
Define exactly which “red flag” symptoms (e.g., weight loss, night sweats) should prompt immediate concern
Clear Pathways
Provide explicit instructions on how and when to seek further help (e.g., “Call the urgent line, don’t wait for a routine appt”).
Timeboxing
Set a definitive time course for symptom resolution (e.g., “If this is a virus, you should feel better in 5 days”).
Planned Follow Up
Arrange a “fail-safe” review to ensure the patient does not get lost in the system.
Dr David Edward Webber passed away peacefully on Sunday 12 April 2026, surrounded by his loving family after a period of illness, having faced cancer with quiet strength. He was 74.
Dr Webber was a pioneering figure in global self-care and a founding member of the Self-Care Academic Research Unit (SCARU) at Imperial College London. His work fundamentally shaped how self-care is understood, conceptualised and advanced across health systems, policy and academia.
He was the founder and long-serving President of the International Self-Care Foundation (ISF), established in 2014 to champion a more holistic, person-centred approach to health. Through this work, he became one of the foremost global advocates for integrating self-care into public health strategy, prevention and everyday life.
Among his most influential contributions was the development of the widely adopted “Seven Pillars of Self-Care” framework, which provided the first comprehensive articulation of self-care as a multidimensional construct. This framework has been translated into multiple languages and used internationally by governments, academic institutions and global health organisations. The framework was also the foundation of the Self-Care Matrix, a unifying framework for self-care, which he co-authored
Dr Webber also founded International Self-Care Day 27/7 (24 July), now recognised worldwide as a focal point for promoting responsible self-care. His efforts helped elevate self-care within the agendas of organisations such as the World Health Organization and the United Nations, contributing to a broader shift toward prevention and individual empowerment in health.
At Imperial College London, he played a central role in the establishment of SCARU, the first academic research unit dedicated to the scientific study of self-care. As an Honorary Research Fellow, he contributed to advancing self-care as a legitimate and necessary academic discipline, bridging policy, research and practice. Beyond his formal achievements, Dr Webber held several senior roles including previous Director General of the Global Self-Care Federation (previously the World Self-Medication Industry, WSMI). He was widely respected for his intellectual generosity, humility and ability to connect people and ideas across disciplines and sectors. He worked tirelessly to bring coherence to a fragmented field and to promote collaboration among diverse stakeholders.
His contributions were recognised at the highest level, including his appointment as an Officer of the Order of the British Empire (OBE), with the investiture conducted by HRH The Princess Royal in February 2024. Ever the student and the inquirer, he was subsequently in July 2024 awarded with distinction a Master of Art degree by research entitled ‘‘Emilie Isabel Barrington: Her place in the Holland Park Circle and the founding of Leighton House Museum, 1877-1926’’. This research has established the leading role played by Mrs Barrington in the foundation of the museum (the centenary of Leighton House Museum is in 2026).
To many, he was more than a colleague. He was a mentor, a guide and an enduring source of insight and encouragement. His influence extended beyond his global work through the individuals and communities he supported along the way.
Dr Webber leaves behind a lasting legacy in global health. His vision helped reposition self-care from a peripheral concept to a central pillar of sustainable healthcare systems.
He will be deeply missed by his family, colleagues and the international community he helped to build.
The Parliamentary Health and Social Care Committee states that the Government’s vaccination strategy is ‘a failure’ and should be replaced with a new plan. Vaccination rates in the UK have been falling since around 2012 when pressures on GP services began to increase.
A key part of the solution to improving childhood vaccination rates in not to create new services like “family hubs” but to invest in core general practice services to increase primary care capacity. This needs to be combined with greater incentives for childhood vaccination.
A successful vaccination strategy must strengthen and not side-line general practice. Without substantial reinvestment in general practice and improved incentives, any new structures will struggle to reverse the long-term decline in childhood vaccination coverage in the UK.
GPs provide continuity, trusted relationships, accurate records, recalls, and opportunistic vaccination; all of which are essential for high uptake. When GP capacity is stretched, these functions weaken and coverage falls as we have seen over the past decade.
The decline in our national vaccination rates is not therefore an inevitability; it is a direct consequence of a strained primary care system. We must stop looking for ‘quick fixes’ and new administrative layers and instead return to what has worked in the past: a well-funded and adequately-staffed General Practice system.
General practitioners and emergency medicine doctors in the UK are increasingly encountering patients who return from overseas with complications following medical procedures. These cases can often be challenging to manage. Frequently, there is limited or no access to operative notes, discharge summaries, or detailed information about the techniques and materials used, making clinical assessment and safe follow-up difficult.
The complications themselves are often complex, including serious infections, wound breakdown, thromboembolic events, and implant-related problems. Many require urgent specialist input. GPs are typically the first point of contact and must manage patient distress, clinical uncertainty, and risk, while navigating referral decisions in the absence of clear guidance or established care pathways.
For patients, the lower cost of surgical procedures overseas can be an appealing alternative to private care in the UK. However, this often comes at the expense of structured follow-up, continuity of care, and access to the original operating team. Once complications arise, patients may find themselves without support from the healthcare provider who delivered the procedure.
The impact of these cases extends beyond general practice and is increasingly felt in NHS emergency departments. Patients may present acutely with sepsis, bleeding, wound failure, or suspected thromboembolic disease, often without any reliable documentation of the original procedure. This creates significant diagnostic and risk-management challenges for clinicians working in emergency departments, leading extensive investigations, senior clinician input, and sometimes to precautionary admission to an NHS hospital. These presentations add to the pressures on already overstretched emergency services.
These presentations place a significant additional burden on general practice. Consultations are typically longer and more complex, requiring careful documentation, risk management, and coordination with secondary care. This work is undertaken within already stretched services and is often compounded by medico-legal uncertainty. More broadly, the NHS absorbs the cost and workload of managing complications from procedures that were neither planned nor delivered within the UK healthcare system.
Together, these challenges highlight the need for improved patient awareness of the risks associated with overseas medical treatment, clearer clinical pathways for managing post-procedure complications, and greater recognition of the pressure placed on NHS services; including general practice, emergency departments, and specialist teams. Addressing these issues will be increasingly important as international medical travel continues to grow.
As artificial intelligence (AI) become increasingly embedded in routine healthcare – supporting tasks such as triage, documentation, interpretation of investigation, diagnosis and patient communication – it introduces new patient safety risks through incorrect outputs (“hallucinations”) that should be treated as safety errors rather than technical glitches. In our article in the Journal of Patient Safety, we argue that primary care must extend its established safety culture to AI by systematically detecting, classifying, reporting, and learning from AI-related errors using principles already applied to human error, such as audit, governance, and incident reporting.
We highlight evidence that AI-generated clinical text can contain omissions, fabrications, or unsafe recommendations that may not be apparent to clinicians and patients and that risk becoming “silent errors” in electronic health records. These errors can then contribute to cognitive offloading if clinicians over-trust AI outputs. To mitigate these risks, we call for routine AI oversight in practice (including review, sampling, and escalation), explicit clinician accountability for AI-influenced outputs, patient engagement in spotting discrepancies, and closer collaboration with AI developers.
Ultimately, AI errors are inevitable, and that embedding AI safety as a core, proactive design feature – rather than an afterthought – is essential to ensure AI enhances rather than compromises patient safety in primary care.
I spoke to GP Registrars on the Imperial College GP Training Scheme about the evolution of medical records in primary care. This is a journey that mirrors the broader transformation of healthcare itself.
The story begins in 1911, with the introduction of the Lloyd George Envelope following the National Insurance Act. These brown paper envelopes (named after the then Chancellor and future Prime Minister, David Lloyd George), each containing a patient’s handwritten medical notes and printed correspondence, became the standard for decades. They were simple, portable, and remarkably durable but also limited by their physical nature. Searching for information meant literally leafing through these paper records, and continuity of care relied on legibility and the clinician’s diligence in recording.
The late 20th century brought a revolution: the computerisation of general practice. Early adopters in the 1980s and 1990s began using systems like EMIS and Vision, digitising the record and transforming how we document, code, and retrieve information on people’s healthcare. Over time, these systems became essential clinical tools by enabling prescribing safety checks, audit, population health management as well as research and quality improvement.
Today, almost every consultation, prescription, and referral is logged electronically. The electronic health record (EHR) has become the backbone of primary care. Yet, despite these advances, challenges remain: data fragmentation across systems, burdensome data entry, and limited interoperability between sectors.
Looking ahead, I believe we are on the verge of another major transformation. Artificial intelligence (AI) and machine learning have the potential to redefine how we record, understand, and act on health information. In the coming years, we can expect:
AI-assisted consultation notes, automatically generated from clinician–patient conversations.
Predictive analytics, helping us identify patients at risk of deterioration or with unmet health needs.
Natural language processing, allowing clinicians to query records using plain English.
Integrated patient data, linking information from hospitals, social care, and personal devices.
The shift from the Lloyd George envelope to intelligent digital systems represents more than just technological progress. It also reflects an ongoing effort to improve care, enhance safety, and make information work for both clinicians and patients.
As we look to the future, the challenge will be ensuring that these innovations support, rather than replace, the human connection that is at the heart of general practice. The tools may change rapidly, but our purpose remains the same: delivering compassionate, person-centred care grounded in good records and good professional relationships.
As the world continues to grapple with the aftermath of the COVID-19 pandemic, Long Covid has emerged as a significant public health challenge. Characterised by persistent symptoms like fatigue, brain fog, shortness of breath, and joint pain lasting weeks, months or even years after an infection, Long Covid affects millions globally. Yet, one major hurdle in understanding and addressing this condition is its under-recording in electronic medical records (EMRs).
Accurate coding of Long Covid in EMRs is essential for studying its epidemiology, improving patient care, and managing its impact on healthcare systems and on societies. Electronic medical records are at the core of modern health systems and have largely replaced the more traditional paper-based records used by healthcare providers for many decades. Electronic medical records are used to track patient diagnoses, treatments, and clinical outcomes. When Long Covid is not properly coded, it becomes difficult to use this data to carry out these tasks. Accurate coding using standardised systems such as SNOMED enables researchers and healthcare providers to:
Track Prevalence and Trends: Consistent coding allows us to estimate how many people are affected by Long Covid, identify demographic patterns, and monitor changes over time.
Study Risk Factors and Outcomes: Properly coded data helps researchers pinpoint who is most at risk and how Long Covid impacts long-term health.
Optimise Healthcare Resources: Understanding the true burden of Long Covid helps health systems allocate resources, plan specialised clinics, and train clinicians.
Support Policy and Funding: Reliable data informs public health policies and justifies funding for Long Covid research and treatment programs.
Without accurate coding, Long Covid remains under-represented in the data that shapes healthcare decisions.
The Challenges of Coding Long Covid
Despite its importance, coding Long Covid in EMRs faces many challenges:
Lack of Standardised Coding: The ICD-10 and SNOMED codes exist but their use is inconsistent. Many clinicians may not apply it, either due to unfamiliarity or because symptoms don’t neatly fit into a code’s description.
Symptom Overlap and Complexity: Long Covid presents with a wide range of symptoms that overlap with other conditions like chronic fatigue syndrome or fibromyalgia. Clinicians may code individual symptoms (e.g., fatigue) rather than linking them to Long Covid, fragmenting the data.
Confusion with other medical problems. Where patients have other long-term medical problems – such as chronic lung disease or cognitive impairment – new symptoms may be be assumed to be of these conditions rather than from Long Covid.
Limited Clinician Awareness: In busy clinical settings, Long Covid may not be recognised or prioritised, especially if patients present with vague or multisystem symptoms. Lack of training on Long Covid’s diagnostic criteria exacerbates this issue.
Under-reporting by Patients: Some patients may not seek care for persistent symptoms, or their concerns may be dismissed, leading to no record of Long Covid in EMRs.
These barriers lead to underestimation of Long Covid’s impact, which in turn limits research and resources needed to improve diagnosis and treatment.
The Consequences of Under-Coding
When Long Covid is not properly documented, the consequences ripple across patients, providers, and systems:
For Patients: Misdiagnosis or lack of a formal Long Covid diagnosis can delay treatment, leaving patients struggling without validation or access to specialised care.
For Research: Incomplete data hinders epidemiological studies, making it harder to understand Long Covid’s long-term effects or develop evidence-based treatments.
For Healthcare Systems: Without clear data, hospitals and clinics can’t plan for the growing demand for Long Covid care, leading to strained resources and inequities in access.
For Public Health: Policymakers rely on EMR data to justify funding and programs. Under-coding obscures the scale of the problem, potentially stalling progress.
Solutions to Improve Coding
Addressing the under-coding of Long Covid requires a multi-pronged approach:
Standardised Coding Protocols: Healthcare systems should promote the consistent use of ICD-10 and SNOMED codes. Clear guidelines are also needed for when and how to apply these codes. Future iterations of coding systems could include more specific Long Covid codes to capture its diverse presentations.
Clinician Training: Educating healthcare providers about Long Covid’s symptoms, diagnostic criteria, and coding practices is essential. Continuing medical education (CME) programs can bridge knowledge gaps and encourage proactive documentation.
Technology and AI: Natural language processing (NLP) tools can analyse unstructured EMR data, such as clinician notes, to flag potential Long Covid cases that might otherwise go uncoded. Integrating these tools into EMR systems could improve case identification.
Patient Awareness: Public health campaigns can encourage patients to report persistent symptoms and advocate for themselves, ensuring their conditions are documented.
Research and Collaboration: Partnerships between health systems, researchers, and policymakers can drive the development of better diagnostic and coding frameworks, informed by real-world data.
Conclusions
The under-recording of Long Covid in electronic medical records is more than a technical issue. It is a barrier to understanding and addressing a condition that affects millions of people globally. Accurate coding is the foundation for robust research, effective patient care, and informed public health strategies. By prioritising standardised coding, clinician education, and innovative technologies, we can shine a light on Long Covid’s true impact and pave the way for better outcomes.
For healthcare providers and clinicians, the message is clear: document Long Covid deliberately and consistently. For patients, it is about advocating for your health and ensuring your symptoms are recorded. And for health systems, it’s about investing in the tools and training needed to make electronic medical records an effective tool in managing Long Covid at patient, healthcare provider and national levels.
Polypharmacy, commonly defined as the concurrent use of five or more medications, is a growing challenge in modern healthcare, especially among older adults with multiple long-term conditions. While advances in medicine have improved disease management, they have also led to an unintended consequence: a rising medication burden that can harm patient well-being.
Our recent study published in Clinical Practice explores how reframing polypharmacy as a chronic condition can empower future doctors to manage it more effectively. For example, polypharmacy substantially increases the risk of adverse drug reactions (ADRs). This underscores the urgent need for a shift in how we approach medication management.
Traditional medical education focuses on treating individual diseases, often leading to prescribing cascades where one drug’s side effect triggers another prescription. This cycle complicates care and worsens outcomes. We designed a three-phase educational intervention for final-year medical students. The program included interactive workshops that introduced polypharmacy risks, diagnostic tools, and case-based learning using electronic health records (EHRs) and clinical decision-support systems (CDSS). Simulated patient consultations and medication reviews with pharmacists to identify drug interactions and propose deprescribing strategies. Finally, debriefing sessions and reflective diaries help to integrate insights into future practice.
The intervention yielded significant improvements. Students’ confidence in recognizing polypharmacy as a primary diagnostic issue jumped from 32% to 86% and their knowledge of diagnostic tools increased from 3.1 to 4.7 out of 5. Standardized patient satisfaction scores also rose from 3.5 to 4.8, reflecting better communication and patient-centred care. Reflective diaries revealed a shift toward holistic thinking, with students better equipped to identify drug-induced symptoms and collaborate with multidisciplinary teams.
By teaching polypharmacy as a chronic condition, this model equips medical students with the skills to break prescribing cascades, enhance patient safety, improve quality of life for patients and reduce healthcare costs. The study’s small sample size limits generalisability but it offers a promising blueprint for updating medical curricula. Future research should explore the long-term impact of such new educational models on patient outcomes and clinical decision-making. Integrating patient feedback and real-world testimonials could further enrich this approach.
As healthcare evolves, empowering clinicians to manage medication burden proactively is essential for improving quality of life. This innovative training is a step toward a more holistic, patient-centred approach in medicine.
Citation: Conte, A.; Sedghi, A.; Majeed, A.; Jerjes, W. Reframing Polypharmacy: Empowering Medical Students to Manage Medication Burden as a Chronic Condition. Clin. Pract. 2025, 15, 142. https://doi.org/10.3390/clinpract15080142
What Makes a Good Doctor? This is the question that Waseem Jerjes and I explore in the Journal of the Royal Society of Medicine. It is a key question that underpins the architecture of medical education, clinical practice, regulation, and professional identity.
It cannot be answered by regulators, educators, or employers in isolation. It must be answered together – by doctors and patients – revisited throughout a career, and adapted as society and the profession change. Without that shared reflection, the danger is not simply disillusionment, but the erosion of the moral foundations of clinical work.
As we enter an era when diagnosis will increasingly involve artificial intelligence and when performance metrics reward volume over value, reclaiming this question as a professional one is imperative. The integrity of our institutions – and of the practitioners within them – depends on reimagining excellence in inclusive, relational terms.
A good doctor is not a flawless technician or a fixed archetype. They are someone who questions assumptions, listens deeply, and adapts with humility to the needs of patients and society. Until our systems are designed to allow such physicians to thrive, we risk losing not only their presence, but their purpose.
