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Background There are known socioeconomic inequalities in annual seasonal influenza (flu) vaccine uptake. The Coronavirus Disease 2019 (COVID-19) pandemic was associated with multiple factors that may have affected flu vaccine uptake, including widespread disruption to healthcare services, changes to flu vaccination eligibility and delivery, and increased public awareness and debate about vaccination due to high-profile COVID-19 vaccination campaigns. However, to the best of our knowledge, no existing studies have investigated the consequences for inequalities in flu vaccine uptake, so we aimed to investigate whether socioeconomic inequalities in flu vaccine uptake have widened since the onset of the COVID-19 pandemic. Methods and findings We used deidentified data from electronic health records for a large city region (Greater Manchester, population 2.8 million), focusing on 3 age groups eligible for National Health Service (NHS) flu vaccination: preschool children (age 2 to 3 years), primary school children (age 4 to 9 years), and older adults (age 65 years plus). The sample population varied between 418,790 (2015/16) and 758,483 (2021/22) across each vaccination season. We estimated age-adjusted neighbourhood-level income deprivation-related inequalities in flu vaccine uptake using Cox proportional hazards models and the slope index of inequality (SII), comparing 7 flu vaccination seasons (2015/16 to 2021/22). Among older adults, the SII (i.e., the gap in uptake between the least and most income-deprived areas) doubled over the 7 seasons from 8.48 (95% CI [7.91,9.04]) percentage points to 16.91 (95% CI [16.46,17.36]) percentage points, with approximately 80% of this increase occurring during the pandemic. Before the pandemic, income-related uptake gaps were wider among children, ranging from 15.59 (95% CI [14.52,16.67]) percentage points to 20.07 (95% CI [18.94,21.20]) percentage points across age groups and vaccination seasons. Among preschool children, the uptake gap increased in 2020/21 to 25.25 (95% CI [24.04,26.45]) percentage points, before decreasing to 20.86 (95% CI [19.65,22.05]) percentage points in 2021/22. Among primary school children, inequalities increased in both pandemic years to reach 30.27 (95% CI [29.58,30.95]) percentage points in 2021/22. Although vaccine uptake increased during the pandemic, disproportionately larger increases in uptake in less deprived areas created wider inequalities in all age groups. The main limitation of our approach is the use of a local dataset, which may limit generalisability to other geographical settings. Conclusions The COVID-19 pandemic led to increased inequalities in flu vaccine uptake, likely due to changes in demand for vaccination, new delivery models, and disruptions to healthcare and schooling. It will be important to investigate the causes of these increased inequalities and to examine whether these increased inequalities also occurred in the uptake of other routine vaccinations. These new wider inequalities in flu vaccine uptake may exacerbate inequalities in flu-related morbidity and mortality., Author(s): Ruth Elizabeth Watkinson 1,*, Richard Williams 2, Stephanie Gillibrand 1, Luke Munford 1, Matt Sutton 1 Introduction Seasonal influenza (flu) infection is associated with high demand for primary care [...]

Background: There is little evidence and no agreement on what constitutes full-time working for GPs. This is essential for workforce planning, resource allocation, and accurately describing GP activity. Aim: To clarify the definition of full-time working for GPs, how this has changed over time, and whether these changes are explained by GP demographics. Design and setting: Data were obtained from repeated cross-sectional national surveys for GPs, which were conducted between 2010 and 2021. Method: A comparison was undertaken of three measures of working time commitments (hours and sessions per week and hours per session) plus a measure of workload intensity across survey years. Multiple regression was used to adjust the changes over time for age, sex, ethnicity, contract type, area deprivation, and rurality. Unadjusted hours and sessions per week were compared with definitions of full-time working. Results: Average hours and sessions per week reduced from 40.5 (95% confidence interval [CI] = 38.5 to 42.5) to 38.0 (95% CI = 36.3 to 39.6) and 7.3 (95% CI = 7.2 to 7.3) to 6.2 (95% CI = 6.2 to 6.3) between 2010 and 2021, respectively. In 2021, 54.6% of GPs worked at least 37.5 hours per week and 9.5% worked at least nine sessions. Hours per session increased from 5.7 (95% CI = 5.7 to 5.7) to 6.2 (95% CI = 6.2 to 6.3) between 2010 and 2021. Partners worked more hours, sessions, and hours per session. Adjustments expanded the increase in hours per session from 0.54 to 0.61. Conclusion: At the current average duration of sessions, six sessions per week aligns with the NHS definition of full-time hours. However, hours per week is a more consistent way to define full-time work for GPs. [ABSTRACT FROM AUTHOR]

Background: Early detection of intermediate hyperglycaemia, otherwise known as non-diabetic hyperglycaemia (NDH) is crucial to identify people at high risk of developing type 2 diabetes mellitus (T2DM) who could benefit from preventative interventions. Failure to identify NDH may also increase the risks of T2DM-related complications at the time of T2DM diagnosis. We investigate sociodemographic inequalities in identification of NDH in England. Methods: We used nationwide data from the English National Health Service (NHS) National Diabetes Audit, which includes all people who were newly identified with NDH (N = 469,910) or diagnosed with T2DM (N = 222,795) between 1st April 2019 and 31st March 2020. We used regression models to explore inequalities in the under identification of NDH by area-level deprivation and age group. Results: Of those with a new T2DM diagnosis, 67.3% had no previous record of NDH. The odds of no previous NDH being recorded were higher amongst people living in more deprived areas (Odds ratio (OR) 1.15 (95% confidence intervals (CI) [1.12, 1.19]) most deprived (Q1) compared to least deprived (Q5) quintile) and younger individuals (OR 4.02 (95% CI [3.79, 4.27] under 35s compared to age 75–84)). Deprivation-related inequalities persisted after stratification by age group, with the largest inequalities amongst middle and older age groups. People living in more deprived areas and younger people also had shorter recorded NDH duration before progression to T2DM, and higher T2DM severity at the time of diagnosis. Conclusions: There is under identification of NDH relative to diagnosis of T2DM amongst people living in more deprived areas and particularly amongst younger people, resulting in missed opportunities for targeted T2DM prevention efforts and potentially contributing to inequalities in T2DM prevalence and severity. More active NDH case-finding amongst these groups may be an important first step in helping to reduce inequalities in T2DM. [ABSTRACT FROM AUTHOR]

Objectives: The objective was to assess the effectiveness of a Water Fluoridation program on a contemporary population of children. Methods: The study used a longitudinal prospective cohort design. In Cumbria, England, two groups of children were recruited and observed over a period of 5–6 years. The Birth Cohort consisted of families recruited from two hospitals in Cumbria where children were conceived after water fluoridation was reintroduced. The systemic and topical effects of community water fluoridation were evaluated in the Birth Cohort. The Older Cohort were approximately 5 years old and recruited from primary schools in Cumbria, shortly after water fluoridation was reintroduced. The predominantly topical effects of fluoridated water were evaluated in the Older Cohort. The primary outcome was the proportion of children with clinical evidence of caries experience in their primary (Birth Cohort) or permanent teeth (Older Cohort). Unadjusted and adjusted regression models were used for analysis. Results: The final clinical examinations for the Birth Cohort involved 1444 participants (mean age 4.8 years), where 17.4% of children in the intervention group were found to have caries experience, compared to 21.4% in the control group. A beneficial effect of water fluoridation was observed adjusting for deprivation (a socioeconomic measure), sex, and age, (adjusted odds ratio 0.74 95% CI 0.55 to 0.98). The final Older Cohort clinical examinations involved 1192 participants (mean age 10.8 years) where 19.1% of children in the intervention group were found to have caries experience compared to 21.9% in the control group (adjusted odds ratio 0.80, 95% CI 0.58 to 1.09). For both the Birth Cohort and Older Cohort there was evidence of a beneficial effect on dmft/DMFT count (IRR 0.61, 95% CI 0.44, 0.86) and (IRR 0.69, 95% CI 0.52, 0.93) respectively. No conclusive proof was found to indicate that the effectiveness of water fluoridation differed across area deprivation quintiles. Conclusions: In the contemporary context of lower caries levels and widespread use of fluoride toothpaste, the impact of water fluoridation on the prevalence of caries was smaller than previous studies have reported. It is important to consider the clinical importance of the absolute reduction in caries prevalence against the use of other dental caries preventive measures. [ABSTRACT FROM AUTHOR]

Objectives: The addition of fluoride to community drinking water supplies has been a long‐standing public health intervention to improve dental health. However, the evidence of cost‐effectiveness in the UK currently lacks a contemporary focus, being limited to a period with higher incidence of caries. A water fluoridation scheme in West Cumbria, United Kingdom, provided a unique opportunity to study the contemporary impact of water fluoridation. This study evaluates the cost‐effectiveness of water fluoridation over a 5–6 years follow‐up period in two distinct cohorts: children exposed to water fluoridation in utero and those exposed from the age of 5. Methods: Cost‐effectiveness was summarized employing incremental cost‐effectiveness ratios (ICER, cost per quality adjusted life year (QALY) gained). Costs included those from the National Health Service (NHS) and local authority perspective, encompassing capital and running costs of water fluoridation, as well as NHS dental activity. The measure of health benefit was the QALY, with utility determined using the Child Health Utility 9‐Dimension questionnaire. To account for uncertainty, estimates of net cost and outcomes were bootstrapped (10 000 bootstraps) to generate cost‐effectiveness acceptability curves and sensitivity analysis performed with alternative specifications. Results: There were 306 participants in the birth cohort (189 and 117 in the non‐fluoridated and fluoridated groups, respectively) and 271 in the older school cohort (159 and 112, respectively). In both cohorts, there was evidence of small gains in QALYs for the fluoridated group compared to the non‐fluoridated group and reductions in NHS dental service cost that exceeded the cost of fluoridation. For both cohorts and across all sensitivity analyses, there were high probabilities (>62%) of water fluoridation being cost‐effective with a willingness to pay threshold of £20 000 per QALY. Conclusions: This analysis provides current economic evidence that water fluoridation is likely to be cost‐effective. The findings contribute valuable contemporary evidence in support of the economic viability of water fluoridation scheme. [ABSTRACT FROM AUTHOR]

Background The NHS Diabetes Prevention Programme (NDPP) is a behaviour change programme for adults who are at risk of developing type 2 diabetes mellitus (T2DM): people with raised blood glucose levels, but not in the diabetic range, diagnosed with nondiabetic hyperglycaemia (NDH). We examined the association between referral to the programme and reducing conversion of NDH to T2DM. Methods and findings Cohort study of patients attending primary care in England using clinical Practice Research Datalink data from 1 April 2016 (NDPP introduction) to 31 March 2020 was used. To minimise confounding, we matched patients referred to the programme in referring practices to patients in nonreferring practices. Patients were matched based on age ([greater than or equal to]3 years), sex, and [greater than or equal to]365 days of NDH diagnosis. Random-effects parametric survival models evaluated the intervention, controlling for numerous covariates. Our primary analysis was selected a priori: complete case analysis, 1-to-1 practice matching, up to 5 controls sampled with replacement. Various sensitivity analyses were conducted, including multiple imputation approaches. Analysis was adjusted for age (at index date), sex, time from NDH diagnosis to index date, BMI, HbA1c, total serum cholesterol, systolic blood pressure, diastolic blood pressure, prescription of metformin, smoking status, socioeconomic status, a diagnosis of depression, and comorbidities. A total of 18,470 patients referred to NDPP were matched to 51,331 patients not referred to NDPP in the main analysis. Mean follow-up from referral was 482.0 (SD = 317.3) and 472.4 (SD = 309.1) days, for referred to NDPP and not referred to NDPP, respectively. Baseline characteristics in the 2 groups were similar, except referred to NDPP were more likely to have higher BMI and be ever-smokers. The adjusted HR for referred to NDPP, compared to not referred to NDPP, was 0.80 (95% CI: 0.73 to 0.87) (p < 0.001). The probability of not converting to T2DM at 36 months since referral was 87.3% (95% CI: 86.5% to 88.2%) for referred to NDPP and 84.6% (95% CI: 83.9% to 85.4%) for not referred to NDPP. Associations were broadly consistent in the sensitivity analyses, but often smaller in magnitude. As this is an observational study, we cannot conclusively address causality. Other limitations include the inclusion of controls from the other 3 UK countries, data not allowing the evaluation of the association between attendance (rather than referral) and conversion. Conclusions The NDPP was associated with reduced conversion rates from NDH to T2DM. Although we observed smaller associations with risk reduction, compared to what has been observed in RCTs, this is unsurprising since we examined the impact of referral, rather than attendance or completion of the intervention., Author(s): Rathi Ravindrarajah 1, Matt Sutton 1,2, David Reeves 1,2, Sarah Cotterill 1, Emma Mcmanus 1,2, Rachel Meacock 1,2, William Whittaker 1, Claudia Soiland-Reyes 3, Simon Heller 4, Peter Bower [...]

Introduction. Shifting care from hospitals into community‐based settings is a major policy goal internationally. Community health services in England currently face the greatest workforce shortages of all sectors, threatening the feasibility of this policy. Moreover, little is known about the extent of variation in community workforce provision regionally and how this relates to determinants of need. Aim. To analyse regional variation in the community services workforce in England between 2010 and 2021. Methods. We obtained NHS workforce statistics data on the number of nurses and nursing support staff providing community services at each NHS organisation in England, from March 2010 to November 2021. We aggregated the organisation‐level data to both regional and national levels, which enabled us to maintain consistent units of analysis across the decade. To examine longitudinal trends and regional variation in workforce provision, we calculated the number of staff per 100,000 population aged 65+ in each region and each period. We then graphed and summarised the variation and examined the correlations with levels of deprivation and rurality. Results. There was a twofold variation in community services workforce provision between English regions. In November 2021, the number of staff per 100,000 people aged over 64 ranged from 300 in the South West to 697 in the North West. Most regions experienced a reduction in provision between 2010 and 2021, with a 21.2% reduction nationally. East of England experienced the largest reduction of 39.3%, whilst London experienced a 2.1% increase. In November 2021, regions with more deprived populations had higher workforce provision and regions with a larger proportion of residents living in rural areas had lower workforce provision. Conclusions. The size of the community services workforce has fallen relative to population needs, contradictory to the policy priority to enhance care in the community. There was substantial regional variation in the size of the workforce, which has persisted throughout the decade. Workforce provision was higher in more deprived areas but lower in rural areas, potentially impacting equitable access in rural areas. [ABSTRACT FROM AUTHOR]

Introduction: Reducing waiting times is a major policy objective in publicly-funded healthcare systems. However, reductions in waiting times can produce a demand response, which may offset increases in capacity. Early detection and diagnosis of cancer is a policy focus in many OECD countries, but prolonged waiting periods for specialist confirmation of diagnosis could impede this goal. We examine whether urgent GP referrals for suspected cancer patients are responsive to local hospital waiting times. Method: We used annual counts of referrals from all 6,667 general practices to all 185 hospital Trusts in England between April 2012 and March 2018. Using a practice-level measure of local hospital waiting times based on breaches of the two-week maximum waiting time target, we examined the relationship between waiting times and urgent GP referrals for suspected cancer. To identify whether the relationship is driven by differences between practices or changes over time, we estimated three regression models: pooled linear regression, a between-practice estimator, and a within-practice estimator. Results: Ten percent higher rates of patients breaching the two-week wait target in local hospitals were associated with higher volumes of referrals in the pooled linear model (4.4%; CI 2.4% to 6.4%) and the between-practice estimator (12.0%; CI 5.5% to 18.5%). The relationship was not statistically significant using the within-practice estimator (1.0%; CI -0.4% to 2.5%). Conclusion: The positive association between local hospital waiting times and GP demand for specialist diagnosis was caused by practices with higher levels of referrals facing longer local waiting times. Temporal changes in waiting times faced by individual practices were not related to changes in their referral volumes. GP referrals for diagnostic cancer services were not found to respond to waiting times in the short-term. In this setting, it may therefore be possible to reduce waiting times by increasing supply without consequently increasing demand. [ABSTRACT FROM AUTHOR]

Payments for some diagnostic scans undertaken in outpatient settings were unbundled from Diagnosis Related Group based payments in England in April 2013 to address under‐provision. Unbundled scans attracted additional payments of between £45 and £748 directly following the reform. We examined the effect on utilization of these scans for patients with suspected cancer. We also explored whether any detected effects represented real increases in use of scans or better coding of activity. We applied difference‐in‐differences regression to patient‐level data from Hospital Episodes Statistics for 180 NHS hospital Trusts in England, between April 2010 and March 2018. We also explored heterogeneity in recorded use of scans before and after the unbundling at hospital Trust‐level. Use of scans increased by 0.137 scans per patient following unbundling, a 134% relative increase. This increased annual national provider payments by £79.2 million. Over 15% of scans recorded after the unbundling were at providers that previously recorded no scans, suggesting some of the observed increase in activity reflected previous under‐coding. Hospitals recorded substantial increases in diagnostic imaging for suspected cancer in response to payment unbundling. Results suggest that the reform also encouraged improvements in recording, so the real increase in testing is likely lower than detected. [ABSTRACT FROM AUTHOR]

Background: Significant health inequalities exist in England. Primary care networks (PCNs), comprised of GP practices, were introduced in England in 2019 with funding linked to membership. PCNs have been tasked with tackling health inequalities. Aim: To consider how the design and introduction of PCNs might influence their ability to tackle health inequalities. Design and setting: A sequential mixed-methods study of PCNs in England. Method: Linear regression of annual PCN-allocated funding per workload-weighted patient on income deprivation score from 2019–2023 was used. Qualitative interviews and observations of PCNs and PCN staff were undertaken across seven PCN sites in England (July 2020–March 2022). Results: Across 1243 networks in 2019–2020, a 10% higher level of income deprivation resulted in £0.31 (95% confidence interval [CI] = £0.25 to £0.37), 4.50%, less funding per weighted patient. In 2022–2023, the same difference in deprivation resulted in £0.16 (95% CI = £0.11 to £0.21), 0.60%, more funding. Qualitative interviews highlighted that, although there were requirements for PCNs to tackle health inequalities, the policy design, and PCN internal relationships and maturity, shaped and sometimes restricted how PCNs approached this task locally. Conclusion: Allocated PCN funding has become more pro-poor over time, suggesting that the need to account for deprivation within funding models is understood by policymakers. The following additional approaches have been highlighted that could support PCNs to tackle inequalities: better management support; encouragement and support to redistribute funding internally to support practices serving more deprived populations; and greater specificity in service requirements. [ABSTRACT FROM AUTHOR]