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We lead multidisciplinary applied research and training to rethink the way health care is delivered in general practice and across the community.
Mobilising context as complex and dynamic in evaluations of complex health interventions
Background: The relationship between healthcare interventions and context is widely conceived as involving complex and dynamic interactions over time. However, evaluations of complex health interventions frequently fail to mobilise such complexity, reporting context and interventions as reified and demarcated categories. This raises questions about practices shaping knowledge about context, with implications for who and what we make visible in our research. Viewed through the lens of case study research, we draw on data collected for the Triple C study (focused on Case study, Context and Complex interventions), to critique these practices, and call for system-wide changes in how notions of context are operationalised in evaluations of complex health interventions. Methods: The Triple C study was funded by the Medical Research Council to develop case study guidance and reporting principles taking account of context and complexity. As part of this study, a one-day workshop with 58 participants and nine interviews were conducted with those involved in researching, evaluating, publishing, funding and developing policy and practice from case study research. Discussions focused on how to conceptualise and operationalise context within case study evaluations of complex health interventions. Analysis focused on different constructions and connections of context in relation to complex interventions and the wider social forces structuring participant’s accounts. Results: We found knowledge-making practices about context shaped by epistemic and political forces, manifesting as: tensions between articulating complexity and clarity of description; ontological (in)coherence between conceptualisations of context and methods used; and reified versions of context being privileged when communicating with funders, journals, policymakers and publics. Conclusion: We argue that evaluations of complex health interventions urgently requires wide-scale critical reflection on how context is mobilised - by funders, health services researchers, journal editors and policymakers. Connecting with how scholars approach complexity and context across disciplines provides opportunities for creatively expanding the field in which health evaluations are conducted, enabling a critical standpoint to long-established traditions and opening up possibilities for innovating the design of evaluations of complex health interventions.
Developing user personas to capture intersecting dimensions of disadvantage in older patients who are marginalised: a qualitative study
Background Remote and digital services must be equitable, but some patients have difficulty using these services. Designing measures to overcome digital disparities can be challenging for practices. Personas (fictional cases) are a potentially useful tool in this regard. Aim To develop and test a set of personas to reflect the lived experiences and challenges that older people who are disadvantaged face when navigating remote and digital primary care services. Design and setting Qualitative study of digital disparities in NHS community health services offering video appointments. Method Following familiarisation visits and interviews with service providers, 17 older people with multiple markers of disadvantage (limited English, health conditions, and poverty) were recruited and interviewed using narrative prompts. Data were analysed using an intersectionality lens, underpinned by sociological theory. Combining data across all participant interviews, we produced personas and refined these following focus groups involving health professionals, patients, and advocates (n = 12). Results Digital services create significant challenges for older patients with limited economic, social, and linguistic resources and low digital, health, or system literacy. Four contrasting personas were produced, capturing the variety and complexity of how dimensions of disadvantage intersected and influenced identity and actions. The personas illustrate important themes including experience of racism and discrimination, disorientation, discontinuity, limited presence, weak relationships, loss of agency, and mistrust of services and providers. Conclusion Personas can illuminate the multiple and intersecting dimensions of disadvantage in patient populations who are marginalised and may prove useful when designing or redesigning digital primary care services. Adopting an intersectional lens may help practices address digital disparities.
How to read a paper involving artificial intelligence (AI)
This paper guides readers through the critical appraisal of a paper that includes the use of artificial intelligence (AI) in clinical settings for healthcare delivery. A brief introduction to the different types of AI used in healthcare is given, along with some ethical principles to guide the introduction of AI systems into healthcare. Existing publication guidelines for AI studies are highlighted. Ten preliminary questions to ask about a paper describing an AI based decision support algorithm are suggested.
Developing a Long COVID Phenotype for Postacute COVID-19 in a National Primary Care Sentinel Cohort: Observational Retrospective Database Analysis
BACKGROUND: Following COVID-19, up to 40% of people have ongoing health problems, referred to as postacute COVID-19 or long COVID (LC). LC varies from a single persisting symptom to a complex multisystem disease. Research has flagged that this condition is underrecorded in primary care records, and seeks to better define its clinical characteristics and management. Phenotypes provide a standard method for case definition and identification from routine data and are usually machine-processable. An LC phenotype can underpin research into this condition. OBJECTIVE: This study aims to develop a phenotype for LC to inform the epidemiology and future research into this condition. We compared clinical symptoms in people with LC before and after their index infection, recorded from March 1, 2020, to April 1, 2021. We also compared people recorded as having acute infection with those with LC who were hospitalized and those who were not. METHODS: We used data from the Primary Care Sentinel Cohort (PCSC) of the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) database. This network was recruited to be nationally representative of the English population. We developed an LC phenotype using our established 3-step ontological method: (1) ontological step (defining the reasoning process underpinning the phenotype, (2) coding step (exploring what clinical terms are available, and (3) logical extract model (testing performance). We created a version of this phenotype using Protégé in the ontology web language for BioPortal and using PhenoFlow. Next, we used the phenotype to compare people with LC (1) with regard to their symptoms in the year prior to acquiring COVID-19 and (2) with people with acute COVID-19. We also compared hospitalized people with LC with those not hospitalized. We compared sociodemographic details, comorbidities, and Office of National Statistics-defined LC symptoms between groups. We used descriptive statistics and logistic regression. RESULTS: The long-COVID phenotype differentiated people hospitalized with LC from people who were not and where no index infection was identified. The PCSC (N=7.4 million) includes 428,479 patients with acute COVID-19 diagnosis confirmed by a laboratory test and 10,772 patients with clinically diagnosed COVID-19. A total of 7471 (1.74%, 95% CI 1.70-1.78) people were coded as having LC, 1009 (13.5%, 95% CI 12.7-14.3) had a hospital admission related to acute COVID-19, and 6462 (86.5%, 95% CI 85.7-87.3) were not hospitalized, of whom 2728 (42.2%) had no COVID-19 index date recorded. In addition, 1009 (13.5%, 95% CI 12.73-14.28) people with LC were hospitalized compared to 17,993 (4.5%, 95% CI 4.48-4.61; P
Differences in Clinical Presentation With Long COVID After Community and Hospital Infection and Associations With All-Cause Mortality: English Sentinel Network Database Study
Background: Most studies of long COVID (symptoms of COVID-19 infection beyond 4 weeks) have focused on people hospitalized in their initial illness. Long COVID is thought to be underrecorded in UK primary care electronic records. Objective: We sought to determine which symptoms people present to primary care after COVID-19 infection and whether presentation differs in people who were not hospitalized, as well as post–long COVID mortality rates. Methods: We used routine data from the nationally representative primary care sentinel cohort of the Oxford–Royal College of General Practitioners Research and Surveillance Centre (N=7,396,702), applying a predefined long COVID phenotype and grouped by whether the index infection occurred in hospital or in the community. We included COVID-19 infection cases from March 1, 2020, to April 1, 2021. We conducted a before-and-after analysis of long COVID symptoms prespecified by the Office of National Statistics, comparing symptoms presented between 1 and 6 months after the index infection matched with the same months 1 year previously. We conducted logistic regression analysis, quoting odds ratios (ORs) with 95% CIs. Results: In total, 5.63% (416,505/7,396,702) and 1.83% (7623/416,505) of the patients had received a coded diagnosis of COVID-19 infection and diagnosis of, or referral for, long COVID, respectively. People with diagnosis or referral of long COVID had higher odds of presenting the prespecified symptoms after versus before COVID-19 infection (OR 2.66, 95% CI 2.46-2.88, for those with index community infection and OR 2.42, 95% CI 2.03-2.89, for those hospitalized). After an index community infection, patients were more likely to present with nonspecific symptoms (OR 3.44, 95% CI 3.00-3.95; P
Remote care in UK general practice: baseline data on 11 case studies
Background: Accessing and receiving care remotely (by telephone, video or online) became the default option during the coronavirus disease 2019 (COVID-19) pandemic, but in-person care has unique benefits in some circumstances. We are studying UK general practices as they try to balance remote and in-person care, with recurrent waves of COVID-19 and various post-pandemic backlogs. Methods: : Mixed-methods (mostly qualitative) case study across 11 general practices. Researchers-in-residence have built relationships with practices and become familiar with their contexts and activities; they are following their progress for two years via staff and patient interviews, documents and ethnography, and supporting improvement efforts through co-design. In this paper, we report baseline data. Results: : Reflecting our maximum-variety sampling strategy, the 11 practices vary in size, setting, ethos, staffing, population demographics and digital maturity, but share common contextual features—notably system-level stressors such as high workload and staff shortages, and UK’s technical and regulatory infrastructure. We have identified both commonalities and differences between practices in terms of how they: 1] manage the ‘digital front door’ (access and triage) and balance demand and capacity; 2] strive for high standards of quality and safety; 3] ensure digital inclusion and mitigate wider inequalities; 4] support and train their staff (clinical and non-clinical), students and trainees; 5] select, install, pilot and use technologies and the digital infrastructure which support them; and 6] involve patients in their improvement efforts. Conclusions: : General practices’ responses to pandemic-induced disruptive innovation appear unique and situated. We anticipate that by focusing on depth and detail, this longitudinal study will throw light on why a solution that works well in one practice does not work at all in another. As the study unfolds, we will explore how practices achieve timely diagnosis of urgent or serious illness and manage continuity of care, long-term conditions and complex needs.
Explaining the UK's high-risk' approach to type 2 diabetes prevention: Findings from a qualitative interview study with policy-makers in England
Objectives When seeking to prevent type 2 diabetes, a balance must be struck between individual approaches (focusing on people's behaviour choices') and population approaches (focusing on the environment in which those choices are made) to address the socioeconomic complexity of diabetes development. We sought to explore how this balance is negotiated in the accounts of policy-makers developing and enacting diabetes prevention policy. Methods Twelve semistructured interviews were undertaken with nine UK policy-makers between 2018-2021. We explored their perspectives on disease prevention strategies and what influenced policy decision-making. Interviews were transcribed and analysed thematically using NVIVO. We used Shiffman's political priority framework to theorise why some diabetes prevention policy approaches gather political support while others do not. Results The distribution of power and funding among relevant actors, and the way they exerted their power determined the dominant approach in diabetes prevention policy. As a result of this distribution, policy-makers framed their accounts of diabetes prevention policies in terms of individual behaviour change, monitoring personal quantitative markers but with limited ability to effect population-level approaches. Such an approach aligns with the current prevailing neoliberal political context, which focuses on individual lifestyle choices to prevent disease rather than on infrastructure measures to improve the environments and contexts within which those choices are made. Conclusion Within new local and national policy structures, there is an opportunity for collaborative working among the National Health Service, local governments and public health teams to balance the focus on disease prevention, addressing upstream drivers of ill health as well as targeting individuals with the highest risk of diabetes.
The role of masks and respirators in preventing respiratory infections in healthcare and community settings
The covid-19 pandemic saw frequent changes and conflicts in mask policies and politicization of masks. On reviewing the evidence, including studies published after the pandemic, the data suggest respirators are more effective than masks in healthcare, but must be continuously worn to be protective. Healthcare and aged care settings amplify outbreaks, so protection of patients and staff is paramount. Most guidelines assume risk is only present during close contact or aerosol generating procedures, but studies show intermittent use of respirators is not protective. New research in aerosol science confirms the risk of infection is widespread in health facilities. In community settings, any mask use is protective during epidemics, especially if used early, when combined with hand hygiene, and if wearers are compliant. Community use of N95 respirators is more protective than surgical masks, which are more protective than cloth masks, but even cloth masks provide some protection. Mask guidelines should be adaptable to the specific context and should account for rising epidemic activity, and whether a pathogen has asymptomatic transmission. The main rationale for universal masking during pandemics is asymptomatic transmission, which means risk of transmission cannot be self-identified. The precautionary principle should be applied during serious emerging infections or pandemics when transmission mode is not fully understood, or vaccines and drugs are not available. If respirators are not available, medical or cloth masks could be used as a last resort. Data exist to support extended use and reuse of masks and respirators during short supply. In summary, extensive evidence generated during the covid-19 pandemic confirms the superiority of respirators and supports the use of masks and respirators in the community during periods of high epidemic activity. Some gaps in research remain, including economic analyses, research in special population groups for whom masking is challenging, and research on countering disinformation.
Chinese herbal medicine (“3 medicines and 3 formulations”) for COVID-19: rapid systematic review and meta-analysis
Background: To evaluate the evidence behind claims that Chinese Herbal Medicine, specifically “three medicines and three formulations” (3M3F, comprising Jinhua Qinggan, Lianhua Qingwen, Xuebijing, Qingfei Paidu, Huashi Baidu, and Xuanfei Baidu), is an effective treatment for COVID-19. Methods: We searched PubMed, MEDLINE and CNKI databases, preprint servers, clinical trial registries and supplementary sources for Chinese- or English-language randomized trials or non-randomized studies with comparator groups, which tested the constituents of 3M3F in the treatment of COVID-19 up to September 2020. Primary outcome was change in disease severity. Secondary outcomes included various symptoms. Meta-analysis (using generic inverse variance random effects model) was performed when there were two or more studies reporting on the same symptom. Results: Of 607 articles identified, 13 primary studies (6 RCTs and 7 retrospective non-randomized comparative studies) with 1467 participants met our final inclusion criteria. Studies were small and had significant methodological limitations, most notably potential bias in assessment of outcomes. No study convincingly demonstrated a statistically significant impact on change in disease severity. Eight studies reported sufficiently similar secondary outcomes to be included in a meta-analysis. Some statistically significant impacts on symptoms, chest CT manifestations, laboratory variables and length of stay were demonstrated, but such findings were sparse and many remain unreplicated. Conclusions: These findings neither support nor refute the claim that 3M3F alters the severity of COVID-19 or alleviates symptoms. More rigorous studies are required to properly ascertain the potential role of Chinese Herbal Medicine in COVID-19.
Examining Intersectionality and Barriers to the Uptake of Video Consultations Among Older Adults From Disadvantaged Backgrounds With Limited English Proficiency: Qualitative Narrative Interview Study
Background: The rapid shift to video consultation services during the COVID-19 pandemic has raised concerns about exacerbating existing health inequities, particularly for disadvantaged populations. Intersectionality theory provides a valuable framework for understanding how multiple dimensions of disadvantage interact to shape health experiences and outcomes. Objective: This study aims to explore how multiple dimensions of disadvantage—specifically older age, limited English proficiency, and low socioeconomic status—intersect to shape experiences with digital health services, focusing on video consultations. Methods: Following familiarization visits and interviews with service providers, 17 older people with multiple markers of disadvantage (older age, low socioeconomic status, and limited English proficiency) were recruited in the Redbridge borough of London. Data collection included narrative interviews and ethnographic observations during home visits. Field notes captured participants’ living conditions, family dynamics, and technological arrangements. Guided by intersectionality theory and digital capital concepts, interviews explored participants’ experiences accessing health care remotely. Intersectional narrative analysis was used to identify key themes and examine how different forms of disadvantage interact. We developed theoretically informed narrative portraits and user personas to synthesize findings. Results: Analysis revealed that the digitalization of health care can exacerbate existing inequities, erode trust, compound oppression, and reduce patient agency for multiply disadvantaged patient populations. Examining intersectionality illuminated how age, language proficiency, and socioeconomic status interact to create unique barriers and experiences. Key themes included the following: weakened presence in digital interactions, erosion of therapeutic relationships, shift from relational to distributed continuity, increased complexity leading to disorientation, engagement shaped by previous experiences of discrimination, and reduced patient agency. Conclusions: This study provides critical insights into how the digitalization of health care can deepen disparities for older patients with low income and limited English proficiency. By applying intersectionality theory to digital health disparities, our findings underscore the need for multifaceted approaches to digital health equity that address the complex interplay of disadvantage. Recommendations include co-designing inclusive digital services, strengthening relational continuity, and developing targeted support to preserve agency and trust for marginalized groups in an increasingly digital health care landscape.
Acute hepatitis of unknown aetiology in children: evidence for and against causal relationships with SARS-CoV-2, HAdv and AAV2
Background The cause of acute paediatric hepatitis of unknown aetiology (2022) has not been established despite extensive investigation. Objective To summarise the evidence for and against a causal role for human adenovirus (HAdv), adeno-associated virus 2 (AAV-2) and SARS-CoV-2 in outbreaks of paediatric hepatitis in 2022. Methods We appraised and summarised relevant evidence for each of the Bradford Hill criteria for causality using quantitative (statistical modelling) and qualitative (narrative coherence) approaches. Each team member scored the evidence base for each criterion separately for HAdv, AAV-2 and SARS-CoV-2; differences were resolved by discussion. We additionally examined criteria of strength and temporality by examining the lagged association between SARS-CoV-2 positivity, respiratory HAdv positivity, positive faecal HAdv specimens and excess A&E attendances in 1-4 years for liver conditions in England. Results Assessing criteria using the published literature and our modelling: for HAdv three Bradford Hill criteria (strength, consistency and temporality) were partially met; and five criteria (consistency, coherence, experimental manipulation, analogy and temporality) were minimally met. For AAV-2, the strength of association criterion was fully met, five criteria (consistency, temporality, specificity, biological gradient and plausibility) were partially met and three (coherence, analogy and experimental manipulation) were minimally met. For SARS-CoV-2, five criteria (strength of association, plausibility, temporality, coherence and analogy) were fully met; one (consistency) was partially met and three (specificity, biological gradient and experimental manipulation) were minimally met. Conclusion Based on the Bradford Hill criteria and modelling, HAdv alone is unlikely to be the cause of the recent increase in hepatitis in children. The causal link between SARS-CoV-2, and to a lesser degree AAV-2, appears substantially stronger but remains unproven. Hepatitis is a known complication of multisystem inflammatory syndrome in children following COVID-19, and SARS-CoV-2 has been linked to increased susceptibility to infection post-COVID-19, which may suggest complex causal pathways including a possible interaction with AAV-2 infection/reactivation in hosts that are genetically susceptible or sensitised to infection.
The science-policy relationship in times of crisis: An urgent call for a pragmatist turn
In this conceptual paper, we argue that at times of crisis, what is sometimes called “evidence-based” or “science-driven” policymaking—establishing scientific truths and then implementing them—must be tempered by a more agile, deliberative and inclusive approach which acknowledges and embraces uncertainty. We offer pragmatism as one potential option, using examples from the UK to illustrate how such an approach might have changed particular crisis decisions and led to better outcomes. We propose that to better prepare for the next public health crisis, five pragmatism-informed shifts are needed in the science-policy relationship: from scientism to science-informed narrative rationality that emerges from practice; from knowledge-then-action to acting judiciously under uncertainty; from hierarchies of evidence to pluralist inquiry; from polarized camps to frame-reflective dialogue; and from an “inside-track” science-policy dialogue to greater participatory democracy. We suggest an agenda for a pragmatist-informed program of applied research on crisis public health policymaking.