Transforming post pandemic cancer services.

This paper outlines the impact of the COVID-19 pandemic on cancer services in the UK including screening, symptomatic diagnosis, treatment pathways and projections on clinical outcomes as a result of these care disruptions. A restoration of cancer services to pre-pandemic levels is not likely to mitigate this adverse impact, particularly with an ageing population and increased cancer burden. New cancer cases are projected to rise to over 500,000 per year by 2035, with over 4 million people living with and beyond cancer. This paper calls for a strategic transformation to prioritise effort on the basis of available datasets and evidence-in particular, to prioritise cancers where an earlier diagnosis is feasible and clinically useful with a focus on mortality benefit by preventing emergency presentations by harnessing data and analytics. This could be delivered by a focus on underperforming groups/areas to try and reduce inequity, linking near real-time datasets with clinical decision support systems at the primary and secondary care levels, promoting the use of novel technologies to improve patient uptake of services, screening and diagnosis, and finally, upskilling and cross-skilling healthcare workers to expand supply of diagnostic and screening services.

Exploring the Experiences of Living With the Post-COVID Syndrome: A Qualitative Study.

INTRODUCTION: Many people experience persistent symptoms for more than 12 weeks following SARS-CoV-2 infection, which is known as post-COVID-19 condition (PCS) or Long COVID (LC). PCS can impair people's quality of life and daily functioning. However, there is a lack of in-depth research exploring the PCS patient journey, as well as gendered aspects of patients' experiences. METHODS: Nineteen semi-structured qualitative interviews were conducted with people living with PCS in the United Kingdom (13 women, 6 men). Interviews were transcribed verbatim and analysed inductively using reflexive thematic analysis. RESULTS: Five main themes were identified: 'Symptom dismissal', 'Lack of information and support', 'Life before and after Long COVID', 'Psychological impact' and 'Acceptance'. A shift overtime to self-management of symptoms was evident. These themes represent different stages of patients' PCS journey. Narratives indicated that women highlighted dismissal by healthcare professionals (HCPs), which was not as prominent in men's narratives. In addition, women went into more detail about the psychological impact of PCS compared to men. CONCLUSION: Women with PCS reported symptom dismissal by HCPs, which may have delayed their diagnosis and negatively affected their well-being. We were not able to explore the experiences of people from non-conforming gender groups. Raising awareness of these issues among HCPs, particularly general practitioners, could improve patient care in PCS. PATIENT OR PUBLIC CONTRIBUTION: Patient and public involvement consisted of people who took part in the interviews and commented on the themes' interpretation and study conclusions.

Ethnic inequalities in the impact of COVID-19 on primary care consultations: a time series analysis of 460,084 individuals with multimorbidity in South London.

BACKGROUND: The COVID-19 pandemic caused rapid changes in primary care delivery in the UK, with concerns that certain groups of the population may have faced increased barriers to access. This study assesses the impact of the response to the COVID-19 pandemic on primary care consultations for individuals with multimorbidity and identifies ethnic inequalities. METHODS: A longitudinal study based on monthly data from primary care health records of 460,084 patients aged ≥18 years from 41 GP practices in South London, from February 2018 to March 2021. Descriptive analysis and interrupted time series (ITS) models were used to analyse the effect of the pandemic on primary care consultations for people with multimorbidity and to identify if the effect varied by ethnic groups and consultation type. RESULTS: Individuals with multimorbidity experienced a smaller initial fall in trend at the start of the pandemic. Their primary care consultation rates remained stable (879 (95% CI 869-890) per 1000 patients in February to 882 (870-894) March 2020), compared with a 7% decline among people without multimorbidity (223 consultations (95% CI 221-226) to 208 (205-210)). The gap in consultations between the two groups reduced after July 2020. The effect among individuals with multimorbidity varied by ethnic group. Ethnic minority groups experienced a slightly larger fall at the start of the pandemic. Individuals of Black, Asian, and Other ethnic backgrounds also switched from face-to-face to telephone at a higher rate than other ethnic groups. The largest fall in face-to-face consultations was observed among people from Asian backgrounds (their consultation rates declined from 676 (659-693) in February to 348 (338-359) in April 2020), which may have disproportionately affected their quality of care. CONCLUSIONS: The COVID-19 pandemic significantly affected primary care utilisation in patients with multimorbidity. While there is evidence of a successful needs-based prioritisation of multimorbidity patients within primary care at the start of the pandemic, inequalities among ethnic minority groups were found. Strengthening disease management for these groups may be necessary to control widening inequalities in future health outcomes.

Multimorbidity clusters among people with serious mental illness: a representative primary and secondary data linkage cohort study.

BACKGROUND: People with serious mental illness (SMI) experience higher mortality partially attributable to higher long-term condition (LTC) prevalence. However, little is known about multiple LTCs (MLTCs) clustering in this population. METHODS: People from South London with SMI and two or more existing LTCs aged 18+ at diagnosis were included using linked primary and mental healthcare records, 2012-2020. Latent class analysis (LCA) determined MLTC classes and multinominal logistic regression examined associations between demographic/clinical characteristics and latent class membership. RESULTS: The sample included 1924 patients (mean (s.d.) age 48.2 (17.3) years). Five latent classes were identified: 'substance related' (24.9%), 'atopic' (24.2%), 'pure affective' (30.4%), 'cardiovascular' (14.1%), and 'complex multimorbidity' (6.4%). Patients had on average 7-9 LTCs in each cluster. Males were at increased odds of MLTCs in all four clusters, compared to the 'pure affective'. Compared to the largest cluster ('pure affective'), the 'substance related' and the 'atopic' clusters were younger [odds ratios (OR) per year increase 0.99 (95% CI 0.98-1.00) and 0.96 (0.95-0.97) respectively], and the 'cardiovascular' and 'complex multimorbidity' clusters were older (ORs 1.09 (1.07-1.10) and 1.16 (1.14-1.18) respectively). The 'substance related' cluster was more likely to be White, the 'cardiovascular' cluster more likely to be Black (compared to White; OR 1.75, 95% CI 1.10-2.79), and both more likely to have schizophrenia, compared to other clusters. CONCLUSION: The current study identified five latent class MLTC clusters among patients with SMI. An integrated care model for treating MLTCs in this population is recommended to improve multimorbidity care.

Ethnic differences in physical and mental multimorbidity in working age adults with a history of depression and/or anxiety.

BACKGROUND: The current study used data from an ethnically diverse population from South London to examine ethnic differences in physical and mental multimorbidity among working age (18-64 years) adults in the context of depression and anxiety. METHOD: The study included 44 506 patients who had previously attended Improving Access to Psychological Therapies services in the London Borough of Lambeth. Multinomial logistic regression examined cross-sectional associations between ethnicity with physical and mental multimorbidity. Patterns of multimorbidity were identified using hierarchical cluster analysis. RESULTS: Within 44 056 working age adults with a history of depression or anxiety from South London there were notable ethnic differences in physical multimorbidity. Adults of Black Caribbean ethnicity were more likely to have physical multimorbidity [adjusted relative risk ratio (aRRR) = 1.25, 95% confidence interval (CI) 1.15-1.36] compared to adults of White ethnicity. Relative to adults of White ethnicity, adults of Asian ethnicity were more likely to have physical multimorbidity at higher thresholds only (e.g. 4 + conditions; aRRR = 1.53, 95% CI 1.17-2.00). Three physical (atopic, cardiometabolic, mixed) and three mental (alcohol/substance use, common/severe mental illnesses, personality disorder) multimorbidity clusters emerged. Ethnic minority groups with multimorbidity had a higher probability of belonging to the cardiometabolic cluster. CONCLUSION: In an ethnically diverse population with a history of common mental health disorders, we found substantial between- and within-ethnicity variation in rates of physical, but not mental, multimorbidity. The findings emphasised the value of more granular definitions of ethnicity when examining the burden of physical and mental multimorbidity.

Completeness, agreement, and representativeness of ethnicity recording in the United Kingdom's Clinical Practice Research Datalink (CPRD) and linked Hospital Episode Statistics (HES).

BACKGROUND: This descriptive study assessed the completeness, agreement, and representativeness of ethnicity recording in the United Kingdom (UK) Clinical Practice Research Datalink (CPRD) primary care databases alone and, for those patients registered with a GP in England, when linked to secondary care data from Hospital Episode Statistics (HES). METHODS: Ethnicity records were assessed for all patients in the May 2021 builds of the CPRD GOLD and CPRD Aurum databases for all UK patients. In analyses of the UK, English data was from combined CPRD-HES, whereas data from Northern Ireland, Scotland, and Wales drew from CPRD only. The agreement of ethnicity records per patient was assessed within each dataset (CPRD GOLD, CPRD Aurum, and HES datasets) and between datasets at the highest level ethnicity categorisation ('Asian', 'black', 'mixed', 'white', 'other'). Representativeness was assessed by comparing the ethnic distributions at the highest-level categorisation of CPRD-HES to those from the Census 2011 across the UK's devolved administrations. Additionally, CPRD-HES was compared to the experimental ethnic distributions for England and Wales from the Office for National Statistics in 2019 (ONS2019) and the English ethnic distribution from May 2021 from NHS Digital's General Practice Extraction Service Data for Pandemic Planning and Research with HES data linkage (GDPPR-HES). RESULTS: In CPRD-HES, 81.7% of currently registered patients in the UK had ethnicity recorded in primary care. For patients with multiple ethnicity records, mismatched ethnicity within individual primary and secondary care datasets was < 10%. Of English patients with ethnicity recorded in both CPRD and HES, 93.3% of records matched at the highest-level categorisation; however, the level of agreement was markedly lower in the 'mixed' and 'other' ethnic groups. CPRD-HES was less proportionately 'white' compared to the UK Census 2011 (80.3% vs. 87.2%) and experimental ONS2019 data (80.4% vs. 84.3%). CPRD-HES was aligned with the ethnic distribution from GDPPR-HES ('white' 80.4% vs. 80.7%); however, with a smaller proportion classified as 'other' (1.1% vs. 2.8%). CONCLUSIONS: CPRD-HES has suitable representation of all ethnic categories with some overrepresentation of minority ethnic groups and a smaller proportion classified as 'other' compared to the UK general population from other data sources. CPRD-HES data is useful for studying health risks and outcomes in typically underrepresented groups.

Ethnic inequities in the patterns of personalized care adjustments for 'informed dissent' and 'patient unsuitable': a retrospective study using Clinical Practice Research Datalink.

BACKGROUND: In England, general practitioners voluntarily take part in the Quality and Outcomes Framework, which is a program that seeks to improve care by rewarding good practice. They can make personalized care adjustments (PCAs), e.g. if patients choose not to have the treatment/intervention offered ('informed dissent') or because they are considered to be clinically 'unsuitable'. METHODS: Using data from the Clinical Practice Research Datalink (Aurum), this study examined patterns of PCA reporting for 'informed dissent' and 'patient unsuitable', how they vary across ethnic groups and whether ethnic inequities were explained by sociodemographic factors or co-morbidities. RESULTS: The odds of having a PCA record for 'informed dissent' were lower for 7 of the 10 minoritized ethnic groups studied. Indian patients were less likely than white patients to have a PCA record for 'patient unsuitable'. The higher likelihood of reporting for 'patient unsuitable' among people from Black Caribbean, Black Other, Pakistani and other ethnic groups was explained by co-morbidities and/or area-level deprivation. CONCLUSIONS: The findings counter narratives that suggest that people from minoritized ethnic groups often refuse medical intervention/treatment. The findings also illustrate ethnic inequities in PCA reporting for 'patient unsuitable', which are linked to clinical and social complexity and should be tackled to improve health outcomes for all.

The psychometric properties of PSYCHLOPS, an individualized patient-reported outcome measure of personal distress.

OBJECTIVE: Few studies report the psychometric properties of individualized patient-reported outcome measures (I-PROMs) combining traditional analysis and Item Response Theory (IRT). METHODS: Pre- and posttreatment PSYCHLOPS data derived from six clinical samples (n = 939) were analyzed for validity, reliability, and responsiveness; caseness cutoffs and reliable change index were calculated. Exploratory and confirmatory factor analyses were used to determine whether items represented a unidimensional construct; IRT examined item properties of this construct. RESULTS: Values for internal consistency, construct validity, convergent and discriminant validity, and structural validity were satisfactory. Responsiveness was high: Cohen's d, 1.48. Caseness cutoff and reliable clinical change scores were 6.41 and 4.63, respectively. IRT analysis confirmed that item scores possess strong properties in assessing the underlying trait measured by PSYCHLOPS. CONCLUSION: PSYCHLOPS met the criteria for norm-referenced measurement of patient psychological distress. PSYCHLOPS functioned as a measure of a single latent trait, which we describe as "personal distress."

Idiographic patient reported outcome measures (I-PROMs) for routine outcome monitoring in psychological therapies: Position paper.

Idiographic patient-reported outcome measures (I-PROMs) are a growing set of individualized tools for use in routine outcome monitoring (ROM) in psychological therapies. This paper presents a position statement on their conceptualization, use, and analysis, based on contemporary evidence and clinical practice. Four problem-based, and seven goal-based, I-PROMs, with some evidence of psychometric evaluation and use in psychotherapy, were identified. I-PROMs may be particularly valuable to the evaluation of psychological therapies because of their clinical utility and their alignment with a patient-centered approach. However, there are several challenges for I-PROMs: how to generate items in a robust manner, their measurement model, methods for establishing their reliability and validity, and the meaning of an aggregated I-PROM score. Based on the current state of the literature, we recommend that I-PROMs are used to complement nomothetic measures. Research recommendations are also made regarding the most appropriate methods for analyzing I-PROM data.

Multimorbidity and fit note receipt in working-age adults with long-term health conditions.

BACKGROUND: Research on sickness absence has typically focussed on single diagnoses, despite increasing recognition that long-term health conditions are highly multimorbid and clusters comprising coexisting mental and physical conditions are associated with poorer clinical and functional outcomes. The digitisation of sickness certification in the UK offers an opportunity to address sickness absence in a large primary care population. METHODS: Lambeth Datanet is a primary care database which collects individual-level data on general practitioner consultations, prescriptions, Quality and Outcomes Framework diagnostic data, sickness certification (fit note receipt) and demographic information (including age, gender, self-identified ethnicity, and truncated postcode). We analysed 326 415 people's records covering a 40-month period from January 2014 to April 2017. RESULTS: We found significant variation in multimorbidity by demographic variables, most notably by self-defined ethnicity. Multimorbid health conditions were associated with increased fit note receipt. Comorbid depression had the largest impact on first fit note receipt, more than any other comorbid diagnoses. Highest rates of first fit note receipt after adjustment for demographics were for comorbid epilepsy and rheumatoid arthritis (HR 4.69; 95% CI 1.73-12.68), followed by epilepsy and depression (HR 4.19; 95% CI 3.60-4.87), chronic pain and depression (HR 4.14; 95% CI 3.69-4.65), cardiac condition and depression (HR 4.08; 95% CI 3.36-4.95). CONCLUSIONS: Our results show striking variation in multimorbid conditions by gender, deprivation and ethnicity, and highlight the importance of multimorbidity, in particular comorbid depression, as a leading cause of disability among working-age adults.

Prospective associations between depression and risk of hospitalisation for infection: Findings from the UK Biobank.

BACKGROUND: Associations between depression and non-communicable disease have been well-described. However, the evidence for its role in the development of infectious disease is less understood. We aimed to examine prospective associations between depression and risk of hospitalisation for infection in middle-aged adults from the UK Biobank (linked with Hospital Episode Statistics) and assessed the role of several depression-related factors. METHODS: We assessed prospective associations between depression status at the baseline assessment (2006-2010) and hospitalisations for infection up to the end of March 2016 in 460,418 middle-aged adults enrolled in the UK Biobank (mean age = 56.23 ± 8.11 years, 53.5% female). Cox regression was used to assess associations between depression and subsequent hospitalisations for any infections, as well as infection subtypes, viral infections, and bacterial infections. Amongst those with depression, we also examined the role of depression duration, the age of onset, and the use of antidepressants in hospitalisation risk. RESULTS: Depression at baseline was prospectively associated with an increased risk of hospitalisation for infection (adjusted hazard ration (aHR) = 1.20, 95% confidence interval (CI) = 1.16 to 1.25). This association was found for all infection subtypes apart from infections of the central nervous system (p = 0.911) and the skin (p = 0.313). Receipt of a depression diagnosis in late adulthood and use of antidepressants (but only in those with none/mild depressive symptoms at baseline) increased the risk of hospitalisation for infection amongst those with depression. CONCLUSIONS: These findings suggest that depression might be a risk factor which could be used to identify those at risk of hospitalisation for infection. Future research is required to understand the underlying factors that might result in this increased risk, so that targeted interventions can be developed. FUNDING: AD and AR are funded by Guy's Charity grant number EIC180702 (MLTC Challenge Fund); AD and JAT are co-funded by MRC and NIHR through grant number MR/S028188/1. IB is supported by the NIHR Maudsley BRC and by the NIHR Collaboration for Leadership in Applied Health Research and Care South Londnoo at King's College Hospital NHS Foundation Trust, King's College London. The views expressed are those of the author[s] and not necessarily those of the ESRC, NIHR, the Department of Health and Social Care or King's College London.

Cost outcomes of potentially inappropriate prescribing in middle-aged adults: A Delphi consensus and cross-sectional study.

BACKGROUND: Potentially inappropriate prescribing (PIP) is common in older adults and is associated with increased medication costs and costs of associated adverse drug events. PIP also affects almost 1/5 of middle-aged adults (45-64 y), as defined by the PRescribing Optimally in Middle-aged People's Treatments (PROMPT) criteria. However, there has been little research on PIP medication costs within this age group. AIMS: Calculate the medication costs of PIP for middle-aged adults according to the 22 PROMPT criteria and compare with the cost of consensus-validated, evidence-based (adequate) alternative prescribing scenarios. METHODS: Adequate alternatives to the 22 PROMPT criteria were created via literature review. A Delphi consensus panel of experts was recruited (n = 16), supported by a patient and public involvement group, to achieve consensus on the alternatives. A retrospective repeated cross-sectional study from 2014 to 2019 was then conducted utilising pseudonymised primary care data from Lambeth DataNet in South London (41 general practices, n = 1 185 335, using Lambeth DataNet May 2020 extract) to calculate the cost of PIP. RESULTS: The cross-sectional study included 55 880 patients. The total PIP cost was £2.79 million, with adequate alternative prescribing costing £2.74 million (cost savings of £51 278). Duplicate drug classes was the most costly criterion for both PIP and alternative prescribing. CONCLUSION: This study calculated the medication costs of PIP and created alternative prescribing scenarios for the 22 PROMPT criteria. There is no substantial cost difference between adequate prescribing vs. PIP. Future studies should investigate the wider health economic costs of alternative prescribing, such as reducing hospital admissions.

Determinants of long-term opioid prescribing in an urban population: A cross-sectional study.

BACKGROUND: Opioid prescribing has more than doubled in the UK between 1998 and 2016. Potential adverse health implications include dependency, falls and increased health expenditure. AIM: To describe the predictors of long-term opioid prescribing (LTOP) (≥3 opioid prescriptions in a 90-day period). DESIGN AND SETTING: A retrospective cross-sectional study in 41 general practices in South London. METHOD: Multi-level multivariable logistic regression to investigate the determinants of LTOP. RESULTS: Out of 320 639 registered patients ≥18 years, 2679 (0.8%) were identified as having LTOP. Patients were most likely to have LTOP if they had ≥5 long-term conditions (LTCs) (adjusted odds ratio [AOR] 36.5, 95% confidence interval [CI] 30.4-43.8) or 2-4 LTCs (AOR 13.8, CI 11.9-16.1) in comparison to no LTCs, were ≥75 years compared to 18-24 years (AOR 12.31, CI 7.1-21.5), were smokers compared to nonsmokers (AOR 2.2, CI 2.0-2.5), were female rather than male (AOR 1.9, CI 1.7-2.0) and in the most deprived deprivation quintile (AOR 1.6, CI 1.4-1.8) compared to the least deprived. In a separate model examining individual LTCs, the strongest associations for LTOP were noted for sickle cell disease (SCD) (AOR 18.4, CI 12.8-26.4), osteoarthritis (AOR 3.0, CI 2.8-3.3), rheumatoid arthritis (AOR 2.8, CI 2.2-3.4), depression (AOR 2.6, CI 2.3-2.8) and multiple sclerosis (OR 2.5, CI 1.4-4.4). CONCLUSION: LTOP was significantly higher in those aged ≥75 years, with multimorbidity or specific LTCs: SCD, osteoarthritis, rheumatoid arthritis, depression and multiple sclerosis. These characteristics may enable the design of targeted interventions to reduce LTOP.

Managing stroke risk in patients with atrial fibrillation: a cross-sectional analysis of socio-demographic inequalities in a London borough.

BACKGROUND: Stroke prevention is essential for patients with atrial fibrillation (AF), but some receive sub-optimal management. We reviewed those with a recorded AF diagnosis assessed with CHA2DS2-VASc stroke risk score (SRS) and socio-demographic determinants of anticoagulation prescribing. The objective was to compare with national guidance recommendations, which recommend anticoagulant therapy for SRS ≥ 2, to determine if there were inequalities in management. METHODS: A cross-sectional design was used to analyze records from all (n = 41) general practices in one London borough. Patients were excluded if they were <18 years, had AF resolved or diagnosed < 3 months. Logistic regression identified socio-demographic factors associated with high SRS and anticoagulant prescribing. RESULTS: Of 2913 patients, 2885 (99.0%) had an SRS, and 2411 (83.6%) a score ≥ 2 and 82.9% (1999 of 2411) were prescribed anticoagulation. Women (compared with men), Black and Mixed/Multiple ethnic groups (compared with White), and those living in most deprived areas (compared with least) were more likely to have a score ≥ 2. Patients with a high SRS from Black and Mixed/Multiple ethnic groups and aged 18-74 years were less likely to be prescribed anticoagulation. CONCLUSION: We found evidence of age and ethnic inequity in anticoagulation prescribing for stroke prevention in patients with AF.

What gets recorded, counts: dementia recording in primary care compared with a specialist database.

BACKGROUND: databases of electronic health records are powerful tools for dementia research, but data can be influenced by incomplete recording. We examined whether people with dementia recorded in a specialist database (from a mental health and dementia care service) differ from those recorded in primary care. METHODS: a retrospective cohort study of the population covered by Lambeth DataNet (primary care electronic records) between 2007 and 2019. Documentation of dementia diagnosis in primary care coded data and linked records in a specialist database (Clinical Records Interactive Search) were compared. RESULTS: 3,859 people had dementia documented in primary care codes and 4,266 in the specialist database, with 2,886/5,239 (55%) documented in both sources. Overall, 55% were labelled as having Alzheimer's dementia and 29% were prescribed dementia medication, but these proportions were significantly higher in those documented in both sources. The cohort identified from the specialist database were less likely to live in a care home (prevalence ratio 0.73, 95% confidence interval 0.63-0.85), have multimorbidity (0.87, 0.77-0.98) or consult frequently (0.91, 0.88-0.95) than those identified through primary care codes, although mortality did not differ (0.98, 0.91-1.06). DISCUSSION: there is under-recording of dementia diagnoses in both primary care and specialist databases. This has implications for clinical care and for generalizability of research. Our results suggest that using a mental health database may under-represent those patients who have more frailty, reflecting differential referral to mental health services, and demonstrating how the patient pathways are an important consideration when undertaking database studies.

Spatio-temporal associations of air pollutant concentrations, GP respiratory consultations and respiratory inhaler prescriptions: a 5-year study of primary care in the borough of Lambeth, South London.

BACKGROUND: Although the associations of outdoor air pollution exposure with mortality and hospital admissions are well established, few previous studies have reported on primary care clinical and prescribing data. We assessed the associations of short and long-term pollutant exposures with General Practitioner respiratory consultations and inhaler prescriptions. METHODS: Daily primary care data, for 2009-2013, were obtained from Lambeth DataNet (LDN), an anonymised dataset containing coded data from all patients (1.2 million) registered at general practices in Lambeth, an inner-city south London borough. Counts of respiratory consultations and inhaler prescriptions by day and Lower Super Output Area (LSOA) of residence were constructed. We developed models for predicting daily PM2.5, PM10, NO2 and O3 per LSOA. We used spatio-temporal mixed effects zero inflated negative binomial models to investigate the simultaneous short- and long-term effects of exposure to pollutants on the number of events. RESULTS: The mean concentrations of NO2, PM10, PM2.5 and O3 over the study period were 50.7, 21.2, 15.6, and 49.9 µg/m3 respectively, with all pollutants except NO2 having much larger temporal rather than spatial variability. Following short-term exposure increases to PM10, NO2 and PM2.5 the number of consultations and inhaler prescriptions were found to increase, especially for PM10 exposure in children which was associated with increases in daily respiratory consultations of 3.4% and inhaler prescriptions of 0.8%, per PM10 interquartile range (IQR) increase. Associations further increased after adjustment for weekly average exposures, rising to 6.1 and 1.2%, respectively, for weekly average PM10 exposure. In contrast, a short-term increase in O3 exposure was associated with decreased number of respiratory consultations. No association was found between long-term exposures to PM10, PM2.5 and NO2 and number of respiratory consultations. Long-term exposure to NO2 was associated with an increase (8%) in preventer inhaler prescriptions only. CONCLUSIONS: We found increases in the daily number of GP respiratory consultations and inhaler prescriptions following short-term increases in exposure to NO2, PM10 and PM2.5. These associations are more pronounced in children and persist for at least a week. The association with long term exposure to NO2 and preventer inhaler prescriptions indicates likely increased chronic respiratory morbidity.

Adapting the definition of multimorbidity - development of a locality-based consensus for selecting included Long Term Conditions.

BACKGROUND: Defining multimorbidity has proved elusive in spite of attempts to standardise definitions. For national studies, a broad definition is required to capture national diversity. For locally based studies, the definition may need to reflect demographic and morbidity patterns. We aimed to define multimorbidity for an inner city, multi-ethnic, deprived, young age community typical of many large cities. METHODS: We used a scoping literature review to identify the international literature, standards and guidelines on Long Term Condition (LTC) definitions for inclusion in our multimorbidity definition. Consensus was categorised into high, medium or low consensus, depending on the number of literature sources citing each LTC. Findings were presented to a workshop consisting of local health service stakeholders who were asked to select LTCs for inclusion in a second stage review. In the second stage, each LTC was tested against seven evaluation domains: prevalence, impact, preventability, treatment burden, progression to multiple LTCs, impact on younger people, data quality. These domains were used to create 12 target criteria. LTC rankings according to consensus group and target criteria scores were presented to a second workshop for a final decision about LTC inclusion. RESULTS: The literature review identified 18 literature sources citing 86 LTCs: 11 were excluded because they were LTC clusters. The remainder were allocated into consensus groupings: 13 LTCs were 'high consensus' (cited by ≥ 11 sources); 15 were 'medium consensus' (cited by 5-10 sources); 47 were 'low consensus' (cited by < 5 sources). The first workshop excluded 31 LTCs. The remaining 44 LTCs consisted of: 13 high consensus LTCs, all with high target score (score 6-12); 15 medium consensus LTCs, 11 with high target scores; 16 low consensus LTCs, 6 with high target scores. The final workshop selected the 12 high consensus conditions, 12 medium consensus LTCs (10 with high target scores) and 8 low consensus LTCs (3 with high target scores), producing a final selection of 32 LTCs. CONCLUSIONS: Redefining multimorbidity for an urban context ensures local relevance but may diminish national generalisability. We describe a detailed LTC selection process which should be generalisable to other contexts, both local and national.

Probability of sepsis after infection consultations in primary care in the United Kingdom in 2002-2017: Population-based cohort study and decision analytic model.

BACKGROUND: Efforts to reduce unnecessary antibiotic prescribing have coincided with increasing awareness of sepsis. We aimed to estimate the probability of sepsis following infection consultations in primary care when antibiotics were or were not prescribed. METHODS AND FINDINGS: We conducted a cohort study including all registered patients at 706 general practices in the United Kingdom Clinical Practice Research Datalink, with 66.2 million person-years of follow-up from 2002 to 2017. There were 35,244 first episodes of sepsis (17,886, 51%, female; median age 71 years, interquartile range 57-82 years). Consultations for respiratory tract infection (RTI), skin or urinary tract infection (UTI), and antibiotic prescriptions were exposures. A Bayesian decision tree was used to estimate the probability (95% uncertainty intervals [UIs]) of sepsis following an infection consultation. Age, gender, and frailty were evaluated as association modifiers. The probability of sepsis was lower if an antibiotic was prescribed, but the number of antibiotic prescriptions required to prevent one episode of sepsis (number needed to treat [NNT]) decreased with age. At 0-4 years old, the NNT was 29,773 (95% UI 18,458-71,091) in boys and 27,014 (16,739-65,709) in girls; over 85 years old, NNT was 262 (236-293) in men and 385 (352-421) in women. Frailty was associated with greater risk of sepsis and lower NNT. For severely frail patients aged 55-64 years, the NNT was 247 (156-459) in men and 343 (234-556) in women. At all ages, the probability of sepsis was greatest for UTI, followed by skin infection, followed by RTI. At 65-74 years, the NNT following RTI was 1,257 (1,112-1,434) in men and 2,278 (1,966-2,686) in women; the NNT following skin infection was 503 (398-646) in men and 784 (602-1,051) in women; following UTI, the NNT was 121 (102-145) in men and 284 (241-342) in women. NNT values were generally smaller for the period from 2014 to 2017, when sepsis was diagnosed more frequently. Lack of random allocation to antibiotic therapy might have biased estimates; patients may sometimes experience sepsis or receive antibiotic prescriptions without these being recorded in primary care; recording of sepsis has increased over the study period. CONCLUSIONS: These stratified estimates of risk help to identify groups in which antibiotic prescribing may be more safely reduced. Risks of sepsis and benefits of antibiotics are more substantial among older adults, persons with more advanced frailty, or following UTIs.

The association between colorectal cancer and prior antibiotic prescriptions: case control study.

BACKGROUND: Antibiotic use over several decades is believed to be associated with colorectal adenomas. There is little evidence, however, for the effect of more recent antibiotic use on frequency of colorectal cancers. METHODS: A case control study used the RCGP's Research and Surveillance Centre cohort of patients drawn from NHS England. In all, 35,214 patients with a new diagnosis of colorectal cancer between 1 January 2008 and 31 December 2018 were identified in the database and were matched with 60,348 controls. Conditional logistic regression was used to examine the association between antibiotic prescriptions and colorectal cancer. RESULTS: A dose-response association between colorectal cancers and prior antibiotic prescriptions was observed. The risk was related to the number and recency of prescriptions with a high number of antibiotic prescriptions over a long period carrying the highest risk. For example, patients prescribed antibiotics in up to 15 years preceding diagnosis were associated with a higher risk of colorectal cancer (odds ratio (OR) = 1.90, 95% confidence intervals (CI), 1.61-2.19, p < 0.001). CONCLUSIONS: Antibiotic use over previous years is associated with subsequent colorectal cancer. While the study design cannot determine causality, the findings suggest another reason for caution in prescribing antibiotics, especially in high volumes and over many years.

Is health research undertaken where the burden of disease is greatest? Observational study of geographical inequalities in recruitment to research in England 2013-2018.

BACKGROUND: Research is fundamental to high-quality care, but concerns have been raised about whether health research is conducted in the populations most affected by high disease prevalence. Geographical distribution of research activity is important for many reasons. Recruitment is a major barrier to research delivery, and undertaking recruitment in areas of high prevalence could be more efficient. Regional variability exists in risk factors and outcomes, so research done in healthier populations may not generalise. Much applied health research evaluates interventions, and their impact may vary by context (including geography). Finally, fairness dictates that publically funded research should be accessible to all, so that benefits of participating can be fairly distributed. We explored whether recruitment of patients to health research is aligned with disease prevalence in England. METHODS: We measured disease prevalence using the Quality and Outcomes Framework in England (total long-term conditions, mental health and diabetes). We measured research activity using data from the NIHR Clinical Research Network. We presented descriptive data on geographical variation in recruitment rates. We explored associations between the recruitment rate and disease prevalence rate. We calculated the share of patient recruitment that would need to be redistributed to align recruitment with prevalence. We assessed whether associations between recruitment rate and disease prevalence varied between conditions, and over time. RESULTS: There was significant geographical variation in recruitment rates. When areas were ranked by disease prevalence, recruitment was not aligned with prevalence, with disproportionately low recruitment in areas with higher prevalence of total long-term and mental health conditions. At the level of 15 local networks, analyses suggested that around 12% of current recruitment activity would need to be redistributed to align with disease prevalence. Overall, alignment showed little change over time, but there was variation in the trends over time in individual conditions. CONCLUSIONS: Geographical variations in recruitment do not reflect the suitability of the population for research. Indicators should be developed to assess the fit between research and need, and to allow assessment of interventions among funders, researchers and patients to encourage closer alignment between research activity and burden.