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To explore whether a delay from referral to first contact with nurse-led community health services is associated with the likelihood of subsequent emergency department attendance.
We use individual linked administrative data on use of community health and hospital services. We identify a cohort of 343,721 individuals referred to community health services in England by their primary care provider in 2019. We then track their subsequent community healthcare contacts and emergency department attendances.
We exploit variation in the time to contact caused by weekend delays, which create longer times to first contact for people referred later in the working week. The main analysis compares patients referred on Thursday with those referred on Tuesday.
We show that 6.7% of patients referred on Thursday wait an extra two days for their first community contact relative to those referred on Tuesday. Despite this delay, we find no evidence that people referred on Thursday are more likely to have a subsequent emergency department attendance compared to those referred on Tuesday.
We do not find delayed community health services contact to be associated with an increased risk of emergency attendance amongst patients referred to community services by their primary care provider. This suggests that short delays in contact time are not detrimental for this group.
Shifting care from hospital to community settings is a key priority for health systems internationally. In England, community health services face significant staffing shortages, limiting the extent to which services can be responsive and support the desired strategic shift. Our findings suggest that these constrained community providers could use their limited capacity to prioritise responding quickly to other patients without harming those referred via primary care.
STROBE guidelines.
This study did not include patient or public involvement in its design, conduct, or reporting.
Qualitative research addresses ‘how’ and ‘why’ questions in healthcare. It captures the complexity of clinical practice by providing insights into experiences, behaviours and context often missed by quantitative methods. The objective of this review was to explore the volume, trends and adherence to reporting standards in qualitative research across hospital-based medical subspecialties.
Longitudinal bibliometric review.
Ovid Medline, Embase and Emcare were searched for qualitative research published between 2000 and 2024 in 12 medical subspecialties. For each subspecialty, the number and percentage of qualitative publications was identified. Adherence to reporting standards was assessed in a random sample of publications covering all subspecialties.
Between 2000 and 2024, 715 471 qualitative research studies were published across 12 medical subspecialties, representing 1.36% of all studies (52 620 042). Neurology and oncology had the highest number of qualitative studies (116 835 and 106 360). Although infectious diseases contributed a lower absolute number of qualitative studies (59 947), they had the highest proportion relative to all studies (4.07%). Conversely, nephrology and haematology exhibited the lowest number of qualitative studies (14 510 and 29 198) and smallest proportions (0.90% and 0.81%). Overall, the annual proportion of qualitative research increased from 0.64% (6052/945 008) in 2000 to 1.95% (56 909/2 919 825) in 2024. However, the relative positions remained largely stable over time.
Adherence to reporting standards was generally good, particularly in relation to methodological coherence. However, there was under-reporting of positionality (where researchers consider how their identity and standpoint may influence the research process) and reflexivity (where researchers critically reflect on how their assumptions and decisions shape the study).
Qualitative research is under-represented in medical subspecialties but has increased steadily over time, with notable variation in adoption between subspecialties. While overall adherence to reporting standards is good, greater attention to positionality and reflexivity is needed to enhance transparency and rigour.
To systematically examine how structural vulnerability has been defined and operationalised in United States-based health research, identify conceptual consistencies and methodological gaps, and propose core dimensions of structural vulnerability along with implications for future application in health research.
A systematic mixed-studies review using a parallel-results convergent synthesis design.
PubMed, Embase, Scopus and CINAHL were searched from first publication through 2024 using the terms ‘structural* vulnerab*’ AND health.
Peer-reviewed English-language empirical studies conducted in the United States that applied the concept of structural vulnerability were identified. The Mixed Methods Appraisal Tool was used to assess study quality. Study content was analysed to identify how structural vulnerability was defined and operationalised.
Thirty-seven predominantly high-quality studies published between 2011 and 2024 met inclusion criteria. Structural vulnerability was consistently defined through two interrelated dimensions: as a social positionality (characterised by constrained resilience, limited agency and imposed risks rooted in systemic discrimination and social hierarchies) and as a critical analytic framework for examining structural determinants of health. Quantitative studies predominantly used individual-level indicators (e.g., income, housing) and cross-sectional designs. Qualitative studies focused on experiences of structural vulnerability in relation to health outcomes and infrequently translated findings into structural interventions. The most frequently studied outcomes were infectious disease, substance use and mental health.
Structural vulnerability, as a conceptual and empirical lens, reveals how systems produce—and can potentially reduce—health risks. Findings underscore the need for geographically diverse and longitudinal studies, as well as multidimensional measures. Advancing health equity demands critiquing systemic causes of inequities and pursuing justice-oriented interventions.
Nursing, positioned at the intersection of public health, social sciences and policy, is uniquely equipped to engage structural vulnerability as a critical analytic tool to address health inequities, design interventions and advocate for policy reform.
What problem did the study address? This study addressed a lack of clarity in the definition and operationalization of structural vulnerability in health research.
What were the main findings? The definition of structural vulnerability is consistent across quantitative and qualitative studies, but there are marked variations in its operationalization. Quantitative studies predominantly rely on individual-level indicators, while qualitative studies use it as a theoretical framework to guide analysis, interpret findings and examine structural determinants of health.
Where and on whom will the research have an impact? This review offers a clear framing for integrating structural vulnerability in health research in efforts to advance health equity.
PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guideline.
This study did not include patient or public involvement in its design, conduct or reporting.
Women with gestational diabetes mellitus (GDM) are at seven-fold to ten-fold increased risk of type 2 diabetes mellitus (T2DM) when compared with those who experience a normoglycaemic pregnancy, and the cumulative incidence increases with the time of follow-up post birth. This protocol outlines the development and validation of a risk prediction model assessing the 5-year and 10-year risk of T2DM in women with a prior GDM diagnosis.
Data from all birth mothers and registered births in Victoria and South Australia, retrospectively linked to national diabetes data and pathology laboratory data from 2008 to 2021, will be used for model development and validation of GDM to T2DM conversion. Candidate predictors will be selected considering existing literature, clinical significance and statistical association, including age, body mass index, parity, ethnicity, history of recurrent GDM, family history of T2DM and antenatal and postnatal glucose levels. Traditional statistical methods and machine learning algorithms will explore the best-performing and easily applicable prediction models. We will consider bootstrapping or K-fold cross-validation for internal model validation. If computationally difficult due to the expected large sample size, we will consider developing the model using 80% of available data and evaluating using a 20% random subset. We will consider external or temporal validation of the prediction model based on the availability of data. The prediction model’s performance will be assessed by using discrimination (area under the receiver operating characteristic curve, calibration (calibration slope, calibration intercept, calibration-in-the-large and observed-to-expected ratio), model overall fit (Brier score and Cox-Snell R2) and net benefit (decision curve analysis). To examine algorithm equity, the model’s predictive performance across ethnic groups and parity will be analysed. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis-Artificial Intelligence (TRIPOD+AI) statements will be followed.
Ethics approvals have been received from Deakin University Human Research Ethics Committee (2021–179); Monash Health Human Research Ethics Committee (RES-22-0000-048A); the Australian Institute of Health and Welfare (EO2022/5/1369); the Aboriginal Health Research Ethics Committee of South Australia (SA) (04-23-1056); in addition to a Site-Specific Assessment to cover the involvement of the Preventative Health SA (formerly Wellbeing SA) (2023/SSA00065). Project findings will be disseminated in peer-reviewed journals and at scientific conferences and provided to relevant stakeholders to enable the translation of research findings into population health programmes and health policy.
Around 75 000 people suffer from hip fractures yearly in the United Kingdom (UK) leading to significant mortality and morbidity. Although mortality has dropped from 8% to 5% between 2013 and 2023 after hip fractures, those undergoing surgery for hip fractures have a 30-day readmission rate which has remained stagnant at around 11% over the same decade in the UK.
This study protocol describes a mixed-methods investigation (The ARTHUR Study—avoiding readmission after hip fracture) which aims to understand and offer solutions to prevent avoidable 30-day readmission after hip fracture surgery. The study will focus on two hospitals in acute and community settings in a large urban and ethnically diverse city in the UK.
We describe two work packages.
Work Package One (WP1) involves analysis of 5 year’s worth of routinely collected health data provided by PIONEER, a Health Data Research UK data hub in Acute Care for our local population. Work Package Two (WP2) will involve semistructured interviews with patients, carers or family members as well as non-participant observations of hospital processes to understand systems-based issues related to readmissions after hip fracture surgery. Although recruitment may be an issue, our timeline for recruitment reflects this. We also aim to recruit a diverse population, which has often been under-represented in studies into hip fractures and aim to explore relevant interventions which can be widely generalisable.
This protocol was submitted via IRAS: 330074 and obtained UK NHS REC approval via the West Midlands Coventry and Warwickshire Research Ethics Committee (REC 23/WM/0242) on 25 January 2024. The results of this study will be published in relevant scientific journals and presented at orthopaedic, fragility fracture and geriatric specialty conferences and scientific meetings. A lay summary of the findings will be publicly available on the HRA website.
FreshRSS 