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Objective The objective of this study is to determine demographic and diagnostic distributions of physical pain recorded in clinical notes of a mental health electronic health records database by using natural language processing and examine the overlap in recorded physical pain between primary and secondary care.Design, setting and participants The data were extracted from an anonymised version of the electronic health records of a large secondary mental healthcare provider serving a catchment of 1.3 million residents in south London. These included patients under active referral, aged 18+ at the index date of 1 July 2018 and having at least one clinical document (≥30 characters) between 1 July 2017 and 1 July 2019. This cohort was compared with linked primary care records from one of the four local government areas.Outcome The primary outcome of interest was the presence of recorded physical pain within the clinical notes of the patients, not including psychological or metaphorical pain.Results A total of 27 211 patients were retrieved. Of these, 52% (14,202) had narrative text containing relevant mentions of physical pain. Older patients (OR 1.17, 95% CI 1.15 to 1.19), females (OR 1.42, 95% CI 1.35 to 1.49), Asians (OR 1.30, 95% CI 1.16 to 1.45) or black (OR 1.49, 95% CI 1.40 to 1.59) ethnicities, living in deprived neighbourhoods (OR 1.64, 95% CI 1.55 to 1.73) showed higher odds of recorded pain. Patients with severe mental illnesses were found to be less likely to report pain (OR 0.43, 95% CI 0.41 to 0.46, p

Abstract Background Estimates of chronic pain prevalence using coded primary care data are likely to be substantially lower than estimates derived from community surveys. Most primary care studies have estimated chronic pain prevalence using data searches confined to analgesic medication prescriptions. Increasingly, following recent NICE guideline recommendations, patients and doctors opt for non-drug treatment of chronic pain thus excluding these patients from prevalence estimates based on medication codes. We aimed to develop and test an algorithm combining medication codes with selected diagnostic codes to estimate chronic pain prevalence using coded primary care data. Methods Following a scoping review 4 criteria were developed to identify cohorts of people with chronic pain. These were (1) people with one of 12 (‘tier 1’) conditions that almost always results in the individual having chronic pain (2) people with one of 20 (‘tier 2’) conditions included when there are also 3 or more prescription-only analgesics issued in the last 12 months (3) chronic neuropathic pain, or (4) 4 or more prescription-only analgesics issued in the last 12 months. These were translated into 8 logic rules which included 1,932 SNOMED CT codes. Results The algorithm was run on primary care data from 41 GP Practices in Lambeth. The total population consisted of 386,238 GP registered adults ≥ 18 years as of the 31st March 2021. 64,135 (16.6%) were identified as people with chronic pain. This definition demonstrated notably high rates in Black ethnicity females, and higher rates in the most deprived, and older population. Conclusions Estimates of chronic pain prevalence using structured healthcare data have previously shown lower prevalence estimates for chronic pain than reported in community surveys. This has limited the ability of researchers and clinicians to fully understand and address the complex multifactorial nature of chronic pain. Our study demonstrates that it may be possible to establish more representative prevalence estimates using structured data than previously possible. Use of logic rules offers the potential to move systematic identification and population-based management of chronic pain into mainstream clinical practice at scale and support improved management of symptom burden for people experiencing chronic pain.

Abstract 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

Abstract 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.

Objectives To develop and probe the first computerised decision-support tool to provide antidepressant treatment guidance to general practitioners (GPs) in UK primary care.Design A parallel group, cluster-randomised controlled feasibility trial, where individual participants were blind to treatment allocation.Setting South London NHS GP practices.Participants Ten practices and eighteen patients with treatment-resistant current major depressive disorder.Interventions Practices were randomised to two treatment arms: (a) treatment-as-usual, (b) computerised decision support tool.Results Ten GP practices participated in the trial, which was within our target range (8–20). However, practice and patient recruitment were slower than anticipated and only 18 of 86 intended patients were recruited. This was due to fewer than expected patients being eligible for the study, as well as disruption resulting from the COVID-19 pandemic. Only one patient was lost to follow-up. There were no serious or medically important adverse events during the trial. GPs in the decision tool arm indicated moderate support for the tool. A minority of patients fully engaged with the mobile app-based tracking of symptoms, medication adherence and side effects.Conclusions Overall, feasibility was not shown in the current study and the following modifications would be needed to attempt to overcome the limitations found: (a) inclusion of patients who have only tried one Selective Serotonin Reuptake Inhibitor, rather than two, to improve recruitment and pragmatic relevance of the study; (b) approaching community pharmacists to implement tool recommendations rather than GPs; (c) further funding to directly interface between the decision support tool and self-reported symptom app; (d) increasing the geographic reach by not requiring detailed diagnostic assessments and replacing this with supported remote self-report.Trial registration number NCT03628027.

Obesity is one of the major contributors to the excess mortality seen in people with severe mental illness (SMI) and in low- and middle-income countries people with SMI may be at an even greater risk. In this study, we aimed to determine the prevalence of obesity and overweight in people with SMI and investigate the association of obesity and overweight with sociodemographic variables, other physical comorbidities, and health-risk behaviours. This was a multi-country cross-sectional survey study where data were collected from 3989 adults with SMI from three specialist mental health institutions in Bangladesh, India, and Pakistan. The prevalence of overweight and obesity was estimated using Asian BMI thresholds. Multinomial regression models were then used to explore associations between overweight and obesity with various potential determinants. There was a high prevalence of overweight (17·3 %) and obesity (46·2 %). The relative risk of having obesity (compared to normal weight) was double in women (RRR = 2·04) compared with men. Participants who met the WHO recommendations for fruit and vegetable intake had 2·53 (95 % CI: 1·65–3·88) times greater risk of having obesity compared to those not meeting them. Also, the relative risk of having obesity in people with hypertension is 69 % higher than in people without hypertension (RRR = 1·69). In conclusion, obesity is highly prevalent in SMI and associated with chronic disease. The complex relationship between diet and risk of obesity was also highlighted. People with SMI and obesity could benefit from screening for non-communicable diseases, better nutritional education, and context-appropriate lifestyle interventions.

BackgroundLong-term exposure to air pollution concentrations is known to be adversely associated with a broad range of single non-communicable diseases, but its role in multimorbidity has not been investigated in the UK. We aimed to assess associations between long-term air pollution exposure and multimorbidity status, severity, and patterns using the UK Biobank cohort.MethodsMultimorbidity status was calculated based on 41 physical and mental conditions. We assessed cross-sectional associations between annual modeled particulate matter (PM)2.5, PMcoarse, PM10, and nitrogen dioxide (NO2) concentrations (μg/m3–modeled to residential address) and multimorbidity status at the baseline assessment (2006–2010) in 364,144 people (mean age: 52.2 ± 8.1 years, 52.6% female). Air pollutants were categorized into quartiles to assess dose-response associations. Among those with multimorbidity (≥2 conditions; n = 156,395) we assessed associations between air pollutant exposure levels and multimorbidity severity and multimorbidity patterns, which were identified using exploratory factor analysis. Associations were explored using generalized linear models adjusted for sociodemographic, behavioral, and environmental indicators.ResultsHigher exposures to PM2.5, and NO2 were associated with multimorbidity status in a dose-dependent manner. These associations were strongest when we compared the highest air pollution quartile (quartile 4: Q4) with the lowest quartile (Q1) [PM2.5: adjusted odds ratio (adjOR) = 1.21 (95% CI = 1.18, 1.24); NO2: adjOR = 1.19 (95 % CI = 1.16, 1.23)]. We also observed dose-response associations between air pollutant exposures and multimorbidity severity scores. We identified 11 multimorbidity patterns. Air pollution was associated with several multimorbidity patterns with strongest associations (Q4 vs. Q1) observed for neurological (stroke, epilepsy, alcohol/substance dependency) [PM2.5: adjOR = 1.31 (95% CI = 1.14, 1.51); NO2: adjOR = 1.33 (95% CI = 1.11, 1.60)] and respiratory patterns (COPD, asthma) [PM2.5: adjOR = 1.24 (95% CI = 1.16, 1.33); NO2: adjOR = 1.26 (95% CI = 1.15, 1.38)].ConclusionsThis cross-sectional study provides evidence that exposure to air pollution might be associated with having multimorbid, multi-organ conditions. Longitudinal studies are needed to further explore these associations.

Summary: Background: Uptake of health checks among women has not been examined in relation to patient and General Practitioner (GP) practice level factors. We investigated patient and practice level factors associated with differential uptake of health checks. Methods: Primary care records from 44 practices in Lambeth for women aged 40-74 years old (N = 62,967) from 2000-2018 were analysed using multi-level logistic regression models. An odds ratio (OR) >1 indicates increased occurrence of no health check. Findings: The mean age (IQR) of the included female sample (aged 40-74 years) was 52.9 years (45.0-59.0). Adjusted for patient-level factors (age, ethnicity, English as first language, overweight/obesity, smoking, attendance to GP practices, and co-morbidity), the odds of non-uptake of health checks were higher for Other White (OR 1.24, 95% confidence interval 1.17-1.33), and Other ethnicity (1.20, 1.07-1.35) vs. White British. It was also higher for 50-69 year olds (1.55, 1.47-1.62), 70-74 year olds (1.60, 1.49-1.72) vs. 40-49 year olds. These ORs did not change on adjustments for practice level factors (proportion of patients living in deprived areas, proportion of patients with ≥1 chronic condition, ≥3 emergency diabetes admissions annually, GP density/1000 patients, quality outcome framework score of ≥ 95%, and patient satisfaction scores of ≥80%). Non-uptake was lower for Black Caribbeans, Bangladeshis, overweight/obese patients, frequent practice attenders and comorbid patients. Interpretation: Differential uptake in health checks remained after adjustment for patient and practice level factors. Better measures of social determinants of health and of practice context are needed. Funding: NIHR Research for Patient Benefit Programme (NIHR202769).

Objectives Explore inequalities in risk factors, mental and physical health morbidity in non-pregnant women of reproductive age in contact with mental health services and how these vary per ethnicity.Design Retrospective cohort study.Setting Data from Lambeth DataNet, anonymised primary care records of this ethnically diverse London borough, linked to anonymised electronic mental health records (‘CRIS secondary care database’).Participants Women aged 15–40 years with an episode of secondary mental health care between January 2008 and December 2018 and no antenatal or postnatal Read codes (n=3817) and a 4:1 age-matched comparison cohort (n=14 532).Main outcome measures Preconception risk factors including low/high body mass index, smoking, alcohol, substance misuse, micronutrient deficiencies and physical diagnoses.Results Women in contact with mental health services (whether with or without severe mental illness (SMI)) had a higher prevalence of all risk factors and physical health diagnoses studied. Women from minority ethnic groups were less likely to be diagnosed with depression in primary care compared with white British women (adjusted OR 0.66 (0.55–0.79) p

Abstract 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

Abstract 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.

Abstract Background Patients continue to suffer from medically unexplained symptoms otherwise referred to as persistent physical symptoms (PPS). General practitioners (GPs) play a key role in the management of PPS and require further training. Patients are often frustrated with the care they receive. This study aims to assess the acceptability of an ‘integrated GP care’ approach which consists of offering self-help materials to patients with PPS and offering their GPs training on how to utilise cognitive behavioural skills within their consultations, as well as assessing the feasibility of conducting a future trial in primary care to evaluate its benefit. Methods A feasibility cluster randomised controlled trial was conducted in primary care, South London, UK. GP practices (clusters) were randomly allocated to ‘integrated GP care plus treatment as usual’ or ‘treatment as usual’. Patients with PPS were recruited from participating GP practices before randomisation. Feasibility parameters, process variables and potential outcome measures were collected at pre-randomisation and at 12- and 24-weeks post-randomisation at cluster and individual participant level. Results Two thousand nine hundred seventy-eight patients were identified from 18 GP practices. Out of the 424 patients who responded with interest in the study, 164 fully met the eligibility criteria. One hundred sixty-one patients provided baseline data before cluster randomisation and therefore were able to participate in the study. Most feasibility parameters indicated that the intervention was acceptable and a future trial feasible. 50 GPs from 8 GP practices (randomised to intervention) attended the offer of training and provided positive feedback. Scores in GP knowledge and confidence increased post-training. Follow-up rate of patients at 24 weeks was 87%. However estimated effect sizes on potential clinical outcomes were small. Conclusions It was feasible to identify and recruit patients with PPS. Retention rates of participants up to 24 weeks were high. A wide range of health services were used. The intervention was relatively low cost and low risk. This complex intervention should be further developed to improve patients’/GPs’ utilisation of audio/visual and training resources before proceeding to a full trial evaluation. Trial registration NCT02444520 (ClinicalTrials.gov).

BackgroundThe effect of antibiotics on the human microbiome is now well established, but their indirect effect on the related immune response is less clear. The possible association of Herpes zoster, which involves a reactivation of a previous varicella zoster virus infection, with prior antibiotic exposure might indicate a potential link with the immune response.MethodsA case-control study was carried out using a clinical database, the UK's Clinical Practice Research Datalink. A total of 163,754 patients with varicella zoster virus infection and 331,559 age/sex matched controls were identified and their antibiotic exposure over the previous 10 years, and longer when data permitted, was identified. Conditional logistic regression was used to identify the association between antibiotic exposure and subsequent infection in terms of volume and timing.ResultsThe study found an association of antibiotic prescription and subsequent risk of varicella zoster virus infection (adjusted odds ratio of 1.50; 95%CIs: 1.42-1.58). The strongest association was with a first antibiotic over 10 years ago (aOR: 1.92; 95%CIs: 1.88-1.96) which was particularly pronounced in the younger age group of 18 to 50 (aOR 2.77; 95%CIs: 1.95-3.92).ConclusionsBy finding an association between prior antibiotics and Herpes zoster this study has shown that antibiotics may be involved in the reactivation of the varicella zoster virus. That effect, moreover, may be relatively long term. This indirect effect of antibiotics on viruses, possibly mediated through their effect on the microbiome and immune system, merits further study.

Summary: Background: Social and material deprivation accelerate the development of multimorbidity, yet the mechanisms which drive multimorbidity pathways and trajectories remain unclear. We aimed to examine the association between health inequality, risk factors and accumulation or resolution of LTCs, taking disease sequences into consideration. Methods: We conducted a retrospective cohort of adults aged 18 years and over, registered between April 2005 and May 2020 in general practices in one inner London borough (n = 826,936). Thirty-two long term conditions (LTCs) were selected using a consensus process, based on a definition adapted to the demographic characteristics of the local population. sThe development and resolution of these LTCs were examined according to sociodemographic and clinical risk factors (hypertension; moderate obesity (BMI 30·0–39·9 kg/m2), high cholesterol (total cholesterol > 5 mmol/L), smoking, high alcohol consumption (>14 units per week), and psychoactive substance use), through the application of multistate Markov chain models. Findings: Participants were followed up for a median of 4.2 years (IQR = 1·8 - 8·4); 631,760 (76%) entered the study with no LTCs, 121,424 (15%) with 1 LTC, 41,720 (5%) with 2 LTCs, and 31,966 (4%) with three or more LTCs. At the end of follow-up, 194,777 (24%) gained one or more LTCs, while 45,017 (5%) had resolved LTCs and 27,021 (3%) died. In multistate models, deprivation (hazard ratio [HR] between 1·30 to 1·64), female sex (HR 1·13 to 1·20), and Black ethnicity (HR 1·20 to 1·30; vs White) were independently associated with increased risk of transition from one to two LTCs, and shorter time spent in a healthy state. Substance use was the strongest risk factor for multimorbidity with an 85% probability of gaining LTCs over the next year. First order Markov chains identified consistent disease sequences including: chronic pain or osteoarthritis followed by anxiety and depression; alcohol and substance dependency followed by HIV, viral hepatitis, and liver disease; and morbid obesity followed by diabetes, hypertension, and chronic pain. Interpretation: We examined the relations among 32 LTCs, taking the order of disease occurrence into consideration. Distinctive patterns for the development and accumulation of multimorbidity have emerged, with increased risk of transitioning from no conditions to multimorbidity and mortality related to ethnicity, deprivation and gender. Musculoskeletal disorders, morbid obesity and substance abuse represent common entry points to multimorbidity trajectories.

Abstract 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.

Abstract Background Persistent physical symptoms (PPS), also known as medically unexplained symptoms (MUS), affect approximately 50% of patients in secondary care and are often associated with disability, psychological distress and increased health care costs. Cognitive behavioural therapy (CBT) has demonstrated both short- and long-term efficacy with small to medium effect sizes for PPS, with larger treatment effects for specific PPS syndromes, including non-cardiac chest pain, irritable bowel syndrome (IBS) and chronic fatigue syndrome (CFS). Research indicates that PPS conditions share similar cognitive and behavioural responses to symptoms, such as avoidance and unhelpful beliefs. This suggests that a transdiagnostic approach may be beneficial for patients with PPS. Methods A randomised controlled trial (RCT) will be conducted to evaluate the efficacy and cost-effectiveness of a transdiagnostic CBT-based intervention for PPS. 322 participants with PPS will be recruited from secondary care clinics. Participants stratified by clinic and disability level will be randomised to CBT plus standard medical care (SMC) versus SMC alone. The intervention consists of 8 CBT sessions delivered by a qualified therapist over a period of 20 weeks. Outcomes will be assessed at 9, 20, 40- and 52-weeks post randomisation. Efficacy will be assessed by examining the difference between arms in the primary outcome Work and Social Adjustment Scale (WSAS) at 52 weeks after randomisation. Secondary outcomes will include mood, symptom severity and clinical global impression at 9, 20, 40 and 52 weeks. Cost-effectiveness will be evaluated by combining measures of health service use, informal care, loss of working hours and financial benefits at 52 weeks. Discussion This trial will provide a powered evaluation of the efficacy and cost-effectiveness of a transdiagnostic CBT approach versus SMC for patients with PPS. It will also provide valuable information about potential healthcare pathways for patients with PPS within the National Health Service (NHS). Trial registration ClinicalTrials.gov NCT02426788. Registered 27 April 2015. Overall trial status: Ongoing; Recruitment status: No longer recruiting.

Background The Patient Health Questionnaire-9 (PHQ-9) is a widely used measure of depression in primary care. It was, however, originally designed as a diagnostic screening tool, and not for measuring change in response to antidepressant treatment. Although the Quick Inventory of Depressive Symptomology (QIDS-SR-16) has been extensively validated for outcome measurement, it is poorly adopted in UK primary care, and, although free for clinicians, has licensing restrictions for healthcare organisation use. Aims We aimed to develop a modified version of the PHQ-9, the Maudsley Modified PHQ-9 (MM-PHQ-9), for tracking symptom changes in primary care. We tested the measure's validity, reliability and factor structure. Method A sample of 121 participants was recruited across three studies, and comprised 78 participants with major depressive disorder and 43 controls. MM-PHQ-9 scores were compared with the QIDS-SR-16 and Clinical Global Impressions improvement scale, for concurrent validity. Internal consistency of the scale was assessed, and principal component analysis was conducted to determine the items’ factor structure. Results The MM-PHQ-9 demonstrated good concurrent validity with the QIDS-SR-16, and excellent internal consistency. Sensitivity to change over a 14-week period was d = 0.41 compared with d = 0.61 on the QIDS-SR-16. Concurrent validity between the paper and mobile app versions of the MM-PHQ-9 was r = 0.67. Conclusions These results indicate that the MM-PHQ-9 is a valid and reliable measure of depressive symptoms in paper and mobile app format, although further validation is required. The measure was sensitive to change, demonstrating suitability for use in routine outcome assessment.

Background NHS Practitioner Health is the England wide programme providing mental health and addiction healthcare to doctors and dentists. Outcomes are assessed using five measures. Aims To contribute to a service evaluation of NHS Practitioner Health. To determine responsiveness to change and compare outcome measures. Method Measures were completed at baseline and 6 months: Generalized Anxiety Disorder Assessment (GAD-7), Perceived Stress Scale (PSS), Patient Health Questionaire-9 (PHQ-9), Warwick-Edinburgh Mental Wellbeing scale (WEMWBS), Psychological Outcome Profiles (PSYCHLOPS). Responsiveness to change was determined using effect size with improvement threshold ≥0.80. Instruments were compared using Bland–Altman plots. Results Our sample, n = 402; with 14 (3.5%) excluded for missing data; final sample, n = 388. All measures showed strong mean effect sizes: PSYCHLOPS 1.86 (95%CI 1.73–1.99), 75.8% ≥0.80; PSS 1.48 (1.34–1.62), 64.4% ≥0.80; WEMWBS 1.24 (1.13–1.35), 58.2% ≥0.80; GAD-7 1.07 (0.96–1.18), 52.8% ≥0.80; PHQ-9 0.86 (0.76–0.96), 52.8% ≥0.80. Findings were largely unchanged after stratification by diagnosis, presenting problem or therapy type. Fifty (12.9%) participants did not reach the threshold for improvement on any instrument. Bland–Altman plots indicated generally strong agreement between measures; combining PSYCHLOPS with WEMWBS maximised capture of improvement with only 3.6% of patients lying outside limits of agreement; GAD-7 was most likely to duplicate recovery scores of other measures. Conclusions Patients attending the NHS Practitioner Health service demonstrated high levels of improvement in mental health scores. The patient-generated instrument produced higher change scores than standardised instruments. Combining PSYCHLOPS and WEMWBS captured 96% of patients with above threshold improvement; GAD-7 added little to overall recovery measurement.

Introduction This short article summarises findings about reduced physical activity of adults with progressive muscle disease as a result of COVID-19 lockdown.Methods As part of an ongoing longitudinal cohort study, we prospectively and objectively measured physical activity using accelerometry at baseline in 2019 and follow-up in 2020. A subset of 85 participants incidentally had follow-up data collected during the first UK COVID-19 lockdown from 23 March to 4 July 2020. Thus, for this cohort we had activity data from before and during the COVID-19 pandemic and we were able to prospectively and accurately quantify the changes in their physical activity.Results Our data highlighted reduced overall activity intensity and reduced light activity time in particular.Conclusions From our findings, we can infer specific evidence-based recommendations about how to redress inactivity secondary to COVID-19 restrictions for adults with progressive muscle diseases. These recommendations are likely to be generalisable to other groups who are vulnerable to functional decline secondary to prolonged inactivity.

Background: The threat of antimicrobial resistance has led to intensified efforts to reduce antibiotic utilisation, but serious bacterial infections are increasing in frequency. Objectives: To estimate the risks of serious bacterial infections in association with lower antibiotic prescribing and understand stakeholder views with respect to safe antibiotic reduction. Design: Mixed-methods research was undertaken, including a qualitative interview study of patient and prescriber views that informed a cohort study and a decision-analytic model, using primary care electronic health records. These three work packages were used to design an application (app) for primary care prescribers. Data sources: The Clinical Practice Research Datalink. Setting: This took place in UK general practices. Participants: A total of 706 general practices with 66.2 million person-years of follow-up from 2002 to 2017 and antibiotic utilisation evaluated for 671,830 registered patients. The qualitative study included 31 patients and 30 health-care professionals from primary care. Main outcome measures: Sepsis and localised bacterial infections. Results: Patients were concerned about antimicrobial resistance and the side effects, as well as the benefits, of antibiotic treatment. Prescribers viewed the onset of sepsis as the most concerning potential outcome of reduced antibiotic prescribing. More than 40% of antibiotic prescriptions in primary care had no coded indication recorded across both Vision® and EMIS® practice systems. Antibiotic prescribing rates varied widely between general practices, but there was no evidence that serious bacterial infections were less frequent at higher prescribing practices (adjusted rate ratio for 20% increase in prescribing 1.03, 95% confidence interval 1.00 to 1.06; p = 0.074). The probability of sepsis was lower if an antibiotic was prescribed at an infection consultation, and the number of antibiotic prescriptions required to prevent one episode of sepsis (i.e. the number needed to treat) decreased with age. For those aged 0–4 years, the number needed to treat was 29,773 (95% uncertainty interval 18,458 to 71,091) in boys and 27,014 (95% uncertainty interval 16,739 to 65,709) in girls. For those aged > 85 years, the number needed to treat was 262 (95% uncertainty interval 236 to 293) in men and 385 (95% uncertainty interval 352 to 421) in women. Frailty was associated with a greater risk of sepsis and a smaller number needed to treat. For severely frail patients aged 55–64 years, the number needed to treat was 247 (95% uncertainty interval 156 to 459) for men and 343 (95% uncertainty interval 234 to 556) for women. At all ages, the probability of sepsis was greatest for urinary tract infection, followed by skin infection and respiratory tract infection. The numbers needed to treat were generally smaller for the period 2014–17, when sepsis was diagnosed more frequently. The results are available using an app that we developed to provide primary care prescribers with stratified risk estimates during infection consultations. Limitations: Analyses were based on non-randomised comparisons. Infection episodes and antibiotic prescribing are poorly documented in primary care. Conclusions: Antibiotic treatment is generally associated with lower risks, but the most serious bacterial infections remain infrequent even without antibiotic treatment. This research identifies risk strata in which antibiotic prescribing can be more safely reduced. Future work: The software developed from this research may be further developed and investigated for antimicrobial stewardship effect. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 9, No. 9. See the NIHR Journals Library website for further project information.

Background: Globally, there is increasing research on clusters of multimorbidity, but few studies have investigated multimorbidity in urban contexts characterised by a young, multi-ethnic, deprived populations. This study identified clusters of associative multimorbidity in an urban setting. Methods: This is a population-based retrospective cross-sectional study using electronic health records of all adults aged 18 years and over, registered between April 2005 to May 2020 in general practices in one inner London borough. Multiple correspondence analysis and cluster analysis was used to identify groups of multimorbidity from 32 long-term conditions (LTCs). Results: The population included 41 general practices with 826,936 patients registered between 2005 and 2020, with mean age 40 (SD15·6) years. The prevalence of multimorbidity was 21% (n = 174,881), with the median number of conditions being three and increasing with age. Analysis identified five consistent LTC clusters: 1) anxiety and depression (Ratio of within- to between- sum of squares (WSS/BSS

Abstract Background Medications targeting stroke risk factors have shown good efficacy, yet adherence is suboptimal. A lack of underlying theory may contribute to the ineffectiveness of eliciting or sustaining behaviour change in many existing interventions targeting medication adherence in stroke. Intervention effectiveness and implementation could be enhanced by consideration of evidence base and theory to drive development. The purpose of this study is to identify appropriate components for a theory-driven and evidence-based medication adherence intervention for stroke survivors. Methods The Behaviour Change Wheel (BCW), a guide to intervention development, informed our systematic process of intervention development. Our earlier systematic review had identified important determinants of medication adherence that were mapped into the Theoretical Domains Framework (TDF), with Knowledge, Beliefs about consequences and Emotions found to be more influential. Utilising the BCW facilitated selection of intervention options and behaviour change techniques (BCTs); the active ingredients within an intervention. To further refine BCT selection, APEASE criteria were employed, allowing evaluation of potential BCTs within context: The National Health Service (NHS), United Kingdom (UK). Results Five intervention functions (Education, Persuasion, Training, Environmental Restructuring and Enablement) and five policy categories (Communication/marketing, Guidelines, Regulation, Environmental/social planning and Service provision) were identified as potential intervention options, underpinned by our systematic review findings. Application of APEASE criteria led to an initial pool of 21 BCTs being reduced to 11 (e.g. Habit Formation, Information about Health Consequences and Action Planning) identified as potential intervention components that would both be feasible and directly target the underlying determinants of stroke survivors’ medication adherence. Conclusions Careful consideration of underlying evidence and theory to drive intervention design, facilitated by the BCW, enabled identification of appropriate intervention components. BCTs including Habit Formation, Information about Health Consequences and Self-monitoring of Behaviour were considered potentially effective and appropriate to deliver within the NHS. Having reduced the pool of potential intervention components to a manageable number, it will now be possible to explore the perceived acceptability of selected BCTs in interviews with stroke survivors and healthcare professionals. This approach to intervention development should be generalisable to other chronic conditions and areas of behaviour change (e.g. exercise adherence).

Objectives The fit note replaced the sick note in the UK in 2010, with the aim of improving support for patients requiring sickness absence, yet there has been very little research into fit note use. This study aims to describe number of fit notes by condition, to improve our understanding of patterns of fit note use in primary care. Previous fit note research has relied on extracting diagnoses directly from fit notes, rather than extracting information from clinical records. In this paper, we extract information from clinical records to explore demographic factors and conditions associated with number of fit notes issued.Design This is a longitudinal study of clinical data. We analysed individual-level anonymised data from general practitioner consultations, including demographic information and condition recorded at first fit note. The latter encompassed diagnoses, individual symptoms and psychosocial issues.Setting A database called Lambeth DataNet, containing electronic clinical records on 326 415 adults (ages 16–60) from all 45 general practices within the London Borough of Lambeth from 1 January 2014 to 30 April 2017.Participants Our analytical sample contained 40 698 people with a condition recorded at first fit note.Primary outcome measure Predicted number of fit notes in the period January 2014–April 2017Results Of all studied diagnostic groups, mental illness had the highest predicted number of fit notes (n=3.3; 95% CI: 3.1 to 3.4) after controlling for demographic factors and long-term conditions. The highest predicted number of fit notes for any condition subgroup was among patients presenting for drug and/or alcohol misuse (n=4.5; 95% CI: 4.1 to 4.8).Conclusions For the first time, we show drug and/or alcohol misuse at first fit note are associated with the highest number of fit notes. Research is needed to understand the trajectories of individuals at highest risk of long-term sickness absence, in particular, people presenting with drug and/or alcohol misuse.

Background: Primary care in England is contracted to provide essential services. Many practices also provide additional services, termed ‘directed enhanced services’ (DES), for extra income. The optional nature of DES may result in inequitable service delivery. Aim: To determine the range of DES activity and equity of service provision. Design & setting: A cross-sectional analysis of data from general practices in England took place from 2018–2019. Method: DES were defined in terms of activity level and measured as total DES funding per registered patient. Linear regression modelling was used to explore the relationship between DES activity, practice, and population characteristics. Results: Data were available for 6873 practices providing up to 10 DES in the initial sample. Due to negative funding amounts and a list size of ≤750 registered patients, 24 practices were excluded. Of the final sample (n = 6849), highest DES provision was for influenza and pneumococcal immunisation (99.9%), pertussis immunisation (97.9%), rotavirus and shingles immunisation (99.9%), meningitis immunisation (99.7%), and childhood immunisation (99.6%); lowest provision was for extended hours access (72.4%), violent patient services (2.0%), and out-of-area urgent care (1.3%). Mean DES funding was £6.25 per patient. In deprived areas, DES funding was £0.35 lower (95% confidence interval [CI] = £0.60 to £0.10) per patient (most versus least deprived quintiles); ethnic group-related differences were not significant. DES funding was higher in practices with more GPs or practice nurses per patient. In deprived communities, there was less immunisation activity (including influenza, pneumococcal, meningitis, childhood, and rotavirus and shingles immunisation) and provision of extended hours access; however, learning disability checks provision was greater in these communities. Conclusion: DES provision is lower in deprived areas (notably for immunisations and some aspects of access) but higher in better staffed practices. Voluntary quality schemes may contribute to widening health inequalities.

Antibiotics in childhood have been linked with diseases including asthma, juvenile arthritis, type 1 diabetes, Crohn’s disease and mental illness. The underlying mechanisms are thought related to dysbiosis of the gut microbiome. We conducted a systematic review of the association between antibiotics and disruption of the pediatric gut microbiome. Searches used MEDLINE, EMBASE and Web of Science. Eligible studies: association between antibiotics and gut microbiome dysbiosis; children 0–18 years; molecular techniques of assessment; outcomes of microbiome richness, diversity or composition. Quality assessed by Newcastle–Ottawa Scale or Cochrane Risk of Bias Tool. Meta-analysis where possible. A total of 4,668 publications identified: 12 in final analysis (5 randomized controlled trials (RCTs), 5 cohort studies, 2 cross-sectional studies). Microbiome richness was measured in 3 studies, species diversity in 6, and species composition in 10. Quality of evidence was good or fair. 5 studies found a significant reduction in diversity and 3 a significant reduction in richness. Macrolide exposure was associated with reduced richness for twice as long as penicillin. Significant reductions were seen in Bifidobacteria (5 studies) and Lactobacillus (2 studies), and significant increases in Proteobacteria such as E. coli (4 studies). A meta-analysis of RCTs of the effect of macrolide (azithromycin) exposure on the gut microbiome found a significant reduction in alpha-diversity (Shannon index: mean difference −0.86 (95% CI −1.59, −0.13). Antibiotic exposure was associated with reduced microbiome diversity and richness, and with changes in bacterial abundance. The potential for dysbiosis in the microbiome should be taken into account when prescribing antibiotics for children. Systematic review registration number: CRD42018094188

Background: People of minority ethnic backgrounds may be disproportionately affected by severe COVID-19. Whether this relates to increased infection risk, more severe disease progression, or worse in-hospital survival is unknown. The contribution of comorbidities or socioeconomic deprivation to ethnic patterning of outcomes is also unclear. Methods: We conducted a case-control and a cohort study in an inner city primary and secondary care setting to examine whether ethnic background affects the risk of hospital admission with severe COVID-19 and/or in-hospital mortality. Inner city adult residents admitted to hospital with confirmed COVID-19 (n = 872 cases) were compared with 3,488 matched controls randomly sampled from a primary healthcare database comprising 344,083 people residing in the same region. For the cohort study, we studied 1827 adults consecutively admitted with COVID-19. The primary exposure variable was self-defined ethnicity. Analyses were adjusted for socio-demographic and clinical variables. Findings: The 872 cases comprised 48.1% Black, 33.7% White, 12.6% Mixed/Other and 5.6% Asian patients. In conditional logistic regression analyses, Black and Mixed/Other ethnicity were associated with higher admission risk than white (OR 3.12 [95% CI 2.63–3.71] and 2.97 [2.30–3.85] respectively). Adjustment for comorbidities and deprivation modestly attenuated the association (OR 2.24 [1.83–2.74] for Black, 2.70 [2.03–3.59] for Mixed/Other). Asian ethnicity was not associated with higher admission risk (adjusted OR 1.01 [0.70–1.46]). In the cohort study of 1827 patients, 455 (28.9%) died over a median (IQR) of 8 (4–16) days. Age and male sex, but not Black (adjusted HR 1.06 [0.82–1.37]) or Mixed/Other ethnicity (adjusted HR 0.72 [0.47–1.10]), were associated with in-hospital mortality. Asian ethnicity was associated with higher in-hospital mortality but with a large confidence interval (adjusted HR 1.71 [1.15–2.56]). Interpretation: Black and Mixed ethnicity are independently associated with greater admission risk with COVID-19 and may be risk factors for development of severe disease, but do not affect in-hospital mortality risk. Comorbidities and socioeconomic factors only partly account for this and additional ethnicity-related factors may play a large role. The impact of COVID-19 may be different in Asians. Funding: British Heart Foundation; the National Institute for Health Research; Health Data Research UK.

BackgroundEfforts 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 findingsWe 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.ConclusionsThese 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.

Introduction The Antidepressant Advisor Study is a feasibility trial of a computerised decision-support tool which uses an algorithm to provide antidepressant treatment guidance for general practitioners (GPs) in the UK primary care service. The tool is the first in the UK to implement national guidelines on antidepressant treatment guidance into a computerised decision-support tool.Methods and analysis The study is a parallel group, cluster-randomised controlled feasibility trial where participants are blind to treatment allocation. GPs were assigned to two treatment arms: (1) treatment-as-usual (TAU) and (2) computerised decision-support tool to assist with antidepressant choices. The study will assess recruitment and lost to follow-up rates, GP satisfaction with the tool and impact on health service use. A meaningful long-term roll-out unit cost will be calculated for the tool, and service use data will be collected at baseline and follow-up to inform a full economic evaluation of a future trial.Ethics and dissemination The study has received National Health Service ethical approval from the London—Camberwell St Giles Research Ethics Committee (ref: 17/LO/2074). The trial was pre-registered in the Clinical Trials.gov registry. The results of the study will be published in a pre-publication archive within 1 year of completion of the last follow-up assessment.Trial registration number NCT03628027.

ObjectiveThis study evaluated whether serious bacterial infections are more frequent at family practices with lower antibiotic prescribing rates.DesignCohort study.Setting706 UK family practices in the Clinical Practice Research Datalink from 2002 to 2017.Participants10.1 million registered patients with 69.3 million patient-years’ follow-up.ExposuresAll antibiotic prescriptions, subgroups of acute and repeat antibiotic prescriptions, and proportion of antibiotic prescriptions associated with specific-coded indications.Main outcome measuresFirst episodes of serious bacterial infections. Poisson models were fitted adjusting for age group, gender, comorbidity, deprivation, region and calendar year, with random intercepts representing family practice-specific estimates.ResultsThe age-standardised antibiotic prescribing rate per 1000 patient-years increased from 2002 (male 423; female 621) to 2012 (male 530; female 842) before declining to 2017 (male 449; female 753). The median family practice had an antibiotic prescribing rate of 648 per 1000 patient-years with 95% range for different practices of 430–1038 antibiotic prescriptions per 1000 patient-years. Specific coded indications were recorded for 58% of antibiotic prescriptions at the median family practice, the 95% range at different family practices was from 10% to 75%. There were 139 759 first episodes of serious bacterial infection. After adjusting for covariates and the proportion of coded consultations, there was no evidence that serious bacterial infections were lower at family practices with higher total antibiotic prescribing. The adjusted rate ratio for 20% higher total antibiotic prescribing was 1.03, (95% CI 1.00 to 1.06, p=0.074).ConclusionsWe did not find population-level evidence that family practices with lower total antibiotic prescribing might have more frequent occurrence of serious bacterial infections overall. Improving the recording of infection episodes has potential to inform better antimicrobial stewardship in primary care.

Abstract Background Research evaluating lifestyle interventions for prevention of cardiovascular disease (CVD) may not reach those most at risk. We compared the response rate to a randomised controlled trial (RCT) of a lifestyle intervention by CVD risk, ethnicity and level of deprivation. Methods Primary care patients with a QRisk2 score ≥ 20% were invited to participate in a RCT of an intensive lifestyle intervention versus usual care. This cross-sectional analysis compares anonymised data of responders and non-responders with multiple logistic regression, using adjusted odds ratios (AORs) for QRisk2 score, ethnicity, Index of Multiple Deprivation (IMD 2010) quintile, age and sex. Results From 60 general practices, 8902 patients were invited and 1489 responded. The mean age was 67.3 years and 21.0% were female. Of all patients invited, 69.9% were of white ethnic background, 13.9% ethnic minority backgrounds and 16.2% had no ethnicity data recorded in their medical records. Likelihood of response decreased as QRisk2 score increased (AOR 0.82 per 5 percentage points, 95% CI 0.77–0.88). Black African or Caribbean patients (AOR 0.67; 95% CI 0.45–0.98) and those with missing ethnicity data (AOR 0.55; 95% CI 0.46–0.66) were less likely to respond compared to participants of white ethnicity, but there was no difference in the response rates between south Asian and white ethnicity (AOR 1.08; 95% CI 0.84–1.38). Patients residing in the fourth (AOR 0.70; 95% CI 0.56–0.87) and fifth (AOR 0.52; 95% CI 0.40–0.68) most deprived IMD quintile were less likely to respond compared to the least deprived quintile. Conclusions Evaluations of interventions intended for those at high risk of CVD may fail to reach those at highest risk. Hard to reach patient groups may require different recruitment strategies to maximise participation in future trials. Improvements in primary care ethnicity data recording is required to aid understanding of how successfully study samples represent the target population. Trial registration ISRCTN, ISRCTN84864870. Registered 15 May 2012, https://doi.org/10.1186/ISRCTN84864870.

Background: Motivational interviewing (MI) enhanced with behaviour change techniques (BCTs) and deployed by health trainers targeting multiple risk factors for cardiovascular disease (CVD) may be more effective than interventions targeting a single risk factor. Objectives: The clinical effectiveness and cost-effectiveness of an enhanced lifestyle motivational interviewing intervention for patients at high risk of CVD in group settings versus individual settings and usual care (UC) in reducing weight and increasing physical activity (PA) were tested. Design: This was a three-arm, single-blind, parallel randomised controlled trial. Setting: A total of 135 general practices across all 12 South London Clinical Commissioning Groups were recruited. Participants: A total of 1742 participants aged 40–74 years with a ≥ 20.0% risk of a CVD event in the following 10 years were randomised. Interventions: The intervention was designed to integrate MI and cognitive–behavioural therapy (CBT), delivered by trained healthy lifestyle facilitators in 10 sessions over 1 year, in group or individual format. The control group received UC. Randomisation: Simple randomisation was used with computer-generated randomisation blocks. In each block, 10 participants were randomised to the group, individual or UC arm in a 4 : 3 : 3 ratio. Researchers were blind to the allocation. Main outcome measures: The primary outcomes are change in weight (kg) from baseline and change in PA (average number of steps per day over 1 week) from baseline at the 24-month follow-up, with an interim follow-up at 12 months. An economic evaluation estimates the relative cost-effectiveness of each intervention. Secondary outcomes include changes in low-density lipoprotein cholesterol and CVD risk score. Results: The mean age of participants was 69.75 years (standard deviation 4.11 years), 85.5% were male and 89.4% were white. At the 24-month follow-up, the group and individual intervention arms were not more effective than UC in increasing PA [mean 70.05 steps, 95% confidence interval (CI) –288 to 147.9 steps, and mean 7.24 steps, 95% CI –224.01 to 238.5 steps, respectively] or in reducing weight (mean –0.03 kg, 95% CI –0.49 to 0.44 kg, and mean –0.42 kg, 95% CI –0.93 to 0.09 kg, respectively). At the 12-month follow-up, the group and individual intervention arms were not more effective than UC in increasing PA (mean 131.1 steps, 95% CI –85.28 to 347.48 steps, and mean 210.22 steps, 95% CI –19.46 to 439.91 steps, respectively), but there were reductions in weight for the group and individual intervention arms compared with UC (mean –0.52 kg, 95% CI –0.90 to –0.13 kg, and mean –0.55 kg, 95% CI –0.95 to –0.14 kg, respectively). The group intervention arm was not more effective than the individual intervention arm in improving outcomes at either follow-up point. The group and individual interventions were not cost-effective. Conclusions: Enhanced MI, in group or individual formats, targeted at members of the general population with high CVD risk is not effective in reducing weight or increasing PA compared with UC. Future work should focus on ensuring objective evidence of high competency in BCTs, identifying those with modifiable factors for CVD risk and improving engagement of patients and primary care. Trial registration: Current Controlled Trials ISRCTN84864870. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 23, No. 69. See the NIHR Journals Library website for further project information. This research was part-funded by the NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London.

Abstract Background/aims Use of electronic health records and information technology to deliver more efficient clinical trials is attracting the attention of research funders and researchers. We report on methodological issues and data quality for a comparison of ‘automated’ and manual (or ‘in-practice’) methods for recruitment and randomisation in a large randomised controlled trial, with individual patient allocation in primary care. Methods We conducted a three-arm randomised controlled trial in primary care to evaluate interventions to improve the uptake of invited NHS health checks for cardiovascular risk assessment. Eligible participants were identified using a borough-wide health check management information system. An in-practice recruitment and randomisation method used at 12 general practices required the research team to complete monthly visits to each general practice. For the fully automated method, employed for six general practices, randomisation of eligible participants was performed automatically and remotely using a bespoke algorithm embedded in the health check management information system. Results There were 8588 and 4093 participants recruited for the manual and automated methods, respectively. The in-practice method was ready for implementation 3 months sooner than the automated method and the in-practice method allowed for full control and documentation of the randomisation procedure. However the in-practice approach was labour intensive and the requirement for participant records to be stored locally resulted in the loss of data for 10 practice months. No records for participants allocated using the automated method were lost. A fixed-effects meta-analysis showed that effect estimates for the primary outcome were consistent for the two allocation methods. Conclusions This trial demonstrated the feasibility of automated recruitment and randomisation methods into a randomised controlled trial performed in primary care. Future research should explore the application of these techniques in other clinical contexts and health care settings. Trial registration Current Controlled Trials, ID: ISRCTN42856343. Registered on 21 March 2013

Abstract Background Breast and cancer screening uptake has been found to be lower among women with serious mental illness (SMI). This study aims to corroborate these findings in the UK and to identify variation in screening uptake by illness/treatment factors, and primary care consultation frequency. Methods Linked population-based primary and secondary care data from the London borough of Lambeth (UK) were used to compare breast and cervical screening receipt among linked eligible SMI patients (n = 625 and n = 1393), to those without SMI known only to primary care (n = 106,554 and n = 25,385) using logistic regression models adjusted first for socio-demographic factors and second, additionally for primary care consultation frequency. Results Eligible SMI patients were less likely to have received breast (adjusted odds ratio (OR) 0.69, 95 % confidence interval (CI), 0.57 - 0.84, p

Background: PSYCHLOPS, a patient-generated mental health outcome questionnaire, invites clients to describe the problem that troubles them most. PSYCHLOPS was utilised in Polish primary care in the context of a brief CBT-based intervention for mild to moderate mental health problems. Aim: To explore how patients conceptualise their problems and the consequences of these problems with the aid of PSYCHLOPS. Method: 243 patients were recruited from a primary care setting; 241 completed PSYCHLOPS. Free-text data were obtained from the Problem and Function domains of PSYCHLOPS, blind translated into English and independently analysed using a pre-existing thematic framework. A total of 780 free-text responses were analysed. Results: The most commonly reported responses to the pre-therapy Problem domain category were “somatic” (denoting responses relating to physical health); the most common responses to the Function domain category were “competence/performance” (denoting responses relating to the respondents’ perceived ability to achieve, cope, function). Compared with pre-therapy Problem 1 domain categories, during-therapy responses revealed a higher proportion of the “interpersonal” category (denoting responses relating to social relationships) and a lower proportion of the “somatic” category. Conclusions: Despite the brevity of clients' responses, PSYCHLOPS allowed an insight into patients' most troubling problems and their consequences. Possible reasons underlying the transition from a somatic to an interpersonal problem reporting during the course of talking therapy are discussed.

Background: Unnecessary prescribing of antibiotics in primary care is contributing to the emergence of antimicrobial drug resistance. Objectives: To develop and evaluate a multicomponent intervention for antimicrobial stewardship in primary care, and to evaluate the safety of reducing antibiotic prescribing for self-limiting respiratory infections (RTIs). Interventions: A multicomponent intervention, developed as part of this study, including a webinar, monthly reports of general practice-specific data for antibiotic prescribing and decision support tools to inform appropriate antibiotic prescribing. Design: A parallel-group, cluster randomised controlled trial. Setting: The trial was conducted in 79 general practices in the UK Clinical Practice Research Datalink (CPRD). Participants: All registered patients were included. Main outcome measures: The primary outcome was the rate of antibiotic prescriptions for self-limiting RTIs over the 12-month intervention period. Cohort study: A separate population-based cohort study was conducted in 610 CPRD general practices that were not exposed to the trial interventions. Data were analysed to evaluate safety outcomes for registered patients with 45.5 million person-years of follow-up from 2005 to 2014. Results: There were 41 intervention trial arm practices (323,155 patient-years) and 38 control trial arm practices (259,520 patient-years). There were 98.7 antibiotic prescriptions for RTIs per 1000 patient-years in the intervention trial arm (31,907 antibiotic prescriptions) and 107.6 per 1000 patient-years in the control arm (27,923 antibiotic prescriptions) [adjusted antibiotic-prescribing rate ratio (RR) 0.88, 95% confidence interval (CI) 0.78 to 0.99; p = 0.040]. There was no evidence of effect in children aged

An amendment to this paper has been published and can be accessed via the original article.

An amendment to this paper has been published and can be accessed via the original article.

Following publication of the original article [1], the authors notified us of an error in the reported percentages in Table 3.

Background: Socioeconomic and ethnic factors are established determinants of cardiovascular health inequalities. The role of low proficiency in the majority language as a mediator of these inequalities is uncertain. Aim: This study aimed to investigate the association between non-English language preference and cardiovascular health inequalities in a community in London. Design & setting: Retrospective, cross-sectional analysis of anonymised patient-level data collected from general practices in Lambeth, south London Method: Cardiovascular disease prevalence, monitoring, and risk-identification data were compared between non-English and English language groups using multiple logistic regression. Results: Of the total number of patients registered at the 49 participating practices, 302 404 (83%) patients were aged ≥18 years. Preferred language was recorded by 69.4%: English 53.6%, Portuguese 3.2%, Spanish 2.6%, French 1.6%, Polish 1.4%, Somali 0.5%, and others 7.1%; 30.6% had no record of language preference. The non-English language preference group had a greater likelihood of coronary heart disease ([CHD], odds ratio [OR] 1.18, 95% confidence interval [CI] = 1.03 to 1.34); diabetes mellitus ([DM], OR = 1.33, 95% CI = 1.23 to 1.43); obesity (OR = 1.08, 95% CI = 1.04 to 1.13); and smoking (OR = 1.18, 95% CI = 1.14 to 1.21), but no difference in the prevalence of hypertension or stroke. Cardiovascular monitoring was not less intense in this group. Portuguese-speakers (the largest non-English language preference group) had a greater likelihood of hypertension (OR = 1.43, 95% CI = 1.30 to 1.57); DM (OR = 1.74, 95% CI = 1.50 to 2.02); stroke (OR = 1.40, 95% CI = 1.08 to 1.81); obesity (OR = 1.53, 95% CI = 1.36 to 1.73); and smoking (OR = 1.13, 95% CI = 1.02 to 1.25). Conclusion: The non-English language preference group was associated with a greater risk of some aspects of cardiovascular disease than the English language preference group, probably reflecting shared cultural and behavioural risk. Non-English language preference was not associated with lower rates of cardiovascular monitoring, providing some evidence of equitable primary care access in this group.

Background: This study focuses on health care received by people with serious mental illness (SMI). The aim is to examine the economic implications of different locations of management of care and the views of service users and staff regarding services set up as alternatives to secondary care. Objectives: Specific objectives are to (1) identify people with SMI managed in primary or secondary care; (2) identify those who could be potentially transferred to primary care; (3) compare the characteristics of these groups; (4) compare service use and costs; (5) generate models to estimate cost changes following transfer between settings; (6) identify characteristics associated with time to transition to secondary care; (7) investigate experiences of patients receiving support from community-based interventions; and (8) assess the economic impact of interventions to facilitate transfer of care management. Methods: (1) Quantitative component – using linked primary and secondary care data we examined differences between those discharged to primary care (n = 1410) and those still in secondary care (n = 1629). Service use and costs were compared and predictors of costs were identified using regression models. (2) Qualitative component – interviews following a topic guide were conducted at two time points with 31 people using and 10 people working in services set up as alternatives to secondary care. (3) Economic modelling – an analysis of the health-care costs of the above services compared with usual care was conducted using decision modelling. Data were obtained from local services where possible, and the time horizon was 12 months. Results: (1) Quantitative component – characteristics of those discharged to primary care (n = 1410) were similar to those still in secondary care (n = 1629). Costs for those discharged to primary care were 48% lower than for those remaining in secondary care. Other variables strongly associated with costs were a history of violence and a diagnosis of schizophrenia or bipolar disorder. Few patients in secondary care had a high probability of primary care management and, therefore, excess costs were only around £150,000 across the sample. (2) Qualitative component – service users’ views about a community options team and a primary care support service were positive and compared favourably to services used previously. Views about peer support were slightly less consistent. Staff had concerns with regard to caseload sizes and staff turnover. (3) Economic modelling – services to help transition had costs that were 40% of those for standard care. The results of this showed that triaging patients into these services would save £1578 over a 1-year period and that the results were robust to changes in most parameters. Limitations: Analysis was hindered by the extent to which data were available. Qualitative analyses were limited by the fact that most of the participants did not have a SMI as usually defined and that many had been out of contact with secondary services for a long period of time. Conclusions: Costs are substantially lower in primary care than secondary care, even after controlling for service-user patient differences. Generally, there is satisfaction with services to help facilitate primary care provision and these appear to be cost saving. Future work should continue the analysis of linked data and involve a more comprehensive evaluation of the specific services investigated here. Funding: The National Institute for Health Research Health Services and Delivery Research programme.

Background: A national programme of health checks to identify risk of cardiovascular disease (CVD) is being rolled out but is encountering difficulties because of low uptake. Objective: To evaluate the effectiveness of an enhanced invitation method using the question–behaviour effect (QBE), with or without the offer of a financial incentive to return the QBE questionnaire, at increasing the uptake of health checks. The research went on to evaluate the reasons for the low uptake of invitations and compare the case mix for invited and opportunistic health checks. Design: Three-arm randomised trial and cohort study. Participants: All participants invited for a health check from 18 general practices. Individual participants were randomised. Interventions: (1) Standard health check invitation only; (2) QBE questionnaire followed by a standard invitation; and (3) QBE questionnaire with offer of a financial incentive to return the questionnaire, followed by a standard invitation. Main outcome measures: The primary outcome was completion of the health check within 6 months of invitation. A p-value of 0.0167 was used for significance. In the cohort study of all health checks completed during the study period, the case mix was compared for participants responding to invitations and those receiving ‘opportunistic’ health checks. Participants were not aware that several types of invitation were in use. The research team were blind to trial arm allocation at outcome data extraction. Results: In total, 12,459 participants were included in the trial and health check uptake was evaluated for 12,052 participants for whom outcome data were collected. Health check uptake was as follows: standard invitation, 590 out of 4095 (14.41%); QBE questionnaire, 630 out of 3988 (15.80%); QBE questionnaire and financial incentive, 629 out of 3969 (15.85%). The increase in uptake associated with the QBE questionnaire was 1.43% [95% confidence interval (CI) –0.12% to 2.97%; p = 0.070] and the increase in uptake associated with the QBE questionnaire and offer of financial incentive was 1.52% (95% CI –0.03% to 3.07%; p = 0.054). The difference in uptake associated with the offer of an incentive to return the QBE questionnaire was –0.01% (95% CI –1.59% to 1.58%; p = 0.995). During the study period, 58% of health check cardiovascular risk assessments did not follow a trial invitation. People who received an ‘opportunistic’ health check had greater odds of a ≥ 10% CVD risk than those who received an invited health check (adjusted odds ratio 1.70, 95% CI 1.45 to 1.99; p

Background: Bariatric surgery is known to be an effective treatment for extreme obesity but access to these procedures is currently limited. Objective: This study aimed to evaluate the costs and outcomes of increasing access to bariatric surgery for severe and morbid obesity. Design and methods: Primary care electronic health records from the UK Clinical Practice Research Datalink were analysed for 3045 participants who received bariatric surgery and 247,537 general population controls. The cost-effectiveness of bariatric surgery was evaluated in severe and morbid obesity through a probabilistic Markov model populated with empirical data from electronic health records. Results: In participants who did not undergo bariatric surgery, the probability of participants with morbid obesity attaining normal body weight was 1 in 1290 annually for men and 1 in 677 for women. Costs of health-care utilisation increased with body mass index category but obesity-related physical and psychological comorbidities were the main drivers of health-care costs. In a cohort of 3045 adult obese patients with first bariatric surgery procedures between 2002 and 2014, bariatric surgery procedure rates were greatest among those aged 35–54 years, with a peak of 37 procedures per 100,000 population per year in women and 10 per 100,000 per year in men. During 7 years of follow-up, the incidence of diabetes diagnosis was 28.2 [95% confidence interval (CI) 24.4 to 32.7] per 1000 person-years in controls and 5.7 (95% CI 4.2 to 7.8) per 1000 person-years in bariatric surgery patients (adjusted hazard ratio was 0.20, 95% CI 0.13 to 0.30; p

BackgroundPsychological outcome measures are evolving into measures that depict progress over time. Interval measurement during therapy has not previously been reported for a patient-generated measure in primary care. We aimed to determine the sensitivity to change throughout therapy, using 'PSYCHLOPS' (Psychological Outcome Profiles), and to determine if new problems appearing during therapy diminish overall improvement.MethodsResponses to PSYCHLOPS, pre-, during- and post-therapy were compared.Settingpatients offered brief cognitive behaviour therapy in primary care in Poland.Results238 patients completed the pre-therapy questionnaire, 194 (81.5%) the during-therapy questionnaire and 142 the post-therapy questionnaire (59.7%). For those completing all three questionnaires (n = 135), improvement in total scores produced an overall Effect Size of 3.1 (2.7 to 3.4). We estimated change using three methods for dealing with missing values. Single and multiple imputation did not significantly change the Effect Size; 'Last Value Carried Forward', the most conservative method, produced an overall Effect Size of 2.3 (1.9 to 2.6). New problems during therapy were reported by 81 patients (60.0%): new problem and original problem scores were of similar magnitude and change scores were not significantly different when compared to patients who did not report new problems.ConclusionA large proportion of outcome data is lost when outcome measures depend upon completed end of therapy questionnaires. The use of a during-therapy measure increases data capture. Missing data still produce difficulties in interpreting overall effect sizes for change. We found no evidence that new problems appearing during therapy hampered overall recovery.

Asthma and depression are common health problems in primary care. Evidence of a relationship between asthma and depression is conflicting.to determine 1. The incidence rate and incidence rate ratio of depression in primary care patients with asthma compared to those without asthma, and 2. The standardized mortality ratio of depressed compared to non-depressed patients with asthma.A historical cohort and nested case control study using data derived from the United Kingdom General Practice Research Database.11,275 incident cases of asthma recorded between 1/1/95 and 31/12/96 age, sex and practice matched with non-cases from the database (ratio 1:1) and followed up through the database for 10 years. 1,660 cases were matched by date of asthma diagnosis with 1,660 controls.number of cases diagnosed with depression, the number of deaths over the study period.The rate of depression in patients with asthma was 22.4/1,000 person years and without asthma 13.8 /1,000 person years. The incident rate ratio (adjusted for age, sex, practice, diabetes, cardiovascular disease, cerebrovascular disease, smoking) was 1.59 (95% CI 1.48-1.71). The increased rate of depression was not associated with asthma severity or oral corticosteroid use. It was associated with the number of consultations (odds ratio per visit 1.09; 95% CI 1.07-1.11). The age and sex adjusted standardized mortality ratio for depressed patients with asthma was 1.87 (95% CI: 1.54-2.27).Asthma is associated with depression. This was not related to asthma severity or oral corticosteroid use but was related to service use. This suggests that a diagnosis of depression is related to health seeking behavior in patients with asthma. There is an increased mortality rate in depressed patients with asthma. The cause of this needs further exploration. Consideration should be given to case-finding for depression in this population.

BACKGROUND: We aimed to determine whether family practices' achievement of diabetes quality of care targets is associated with diabetic retinal disease in registered patients. METHODS: Data for achievement of diabetes quality of care targets, including the proportion of patients with HbA1c < or = 7.5%, for 144 family practices in London UK, for the years 2004/5 to 2007/8, were linked to data from a population-based diabetes eye screening programme collected from September 2007 to February 2009. Analyses were adjusted for age, sex, duration and type of diabetes, unadjusted diabetes prevalence, ethnicity and deprivation category. RESULTS: Data were analysed for 24,458 participants with one or more eye screening results in the period. There were 9,332 (38%) with any diabetic retinopathy and 2,819 (11.5%) with sight threatening diabetic retinopathy (STDR), including 2,654 (10.9%) with maculopathy. Among participants registered at 13 family practices that were in the highest quartile for achievement of the HbA1c quality of care target for all four years of study, the relative odds of any diabetic retinopathy were 0.78 (0.69 to 0.88) P

BackgroundElectronic patient records from primary care databases are increasingly used in public health and health services research but methods used to identify cases with disease are not well described. This study aimed to evaluate the relevance of different codes for the identification of acute stroke in a primary care database, and to evaluate trends in the use of different codes over time.MethodsData were obtained from the General Practice Research Database from 1997 to 2006. All subjects had a minimum of 24 months of up-to-standard record before the first recorded stroke diagnosis. Initially, we identified stroke cases using a supplemented version of the set of codes for prevalent stroke used by the Office for National Statistics in Key health statistics from general practice 1998 (ONS codes). The ONS codes were then independently reviewed by four raters and a restricted set of 121 codes for 'acute stroke' was identified but the kappa statistic was low at 0.23.ResultsInitial extraction of data using the ONS codes gave 48,239 cases of stroke from 1997 to 2006. Application of the restricted set of codes reduced this to 39,424 cases. There were 2,288 cases whose index medical codes were for 'stroke annual review' and 3,112 for 'stroke monitoring'. The frequency of stroke review and monitoring codes as index codes increased from 9 per year in 1997 to 1,612 in 2004, 1,530 in 2005 and 1,424 in 2006. The one year mortality of cases with the restricted set of codes was 29.1% but for 'stroke annual review,' 4.6% and for 'stroke monitoring codes', 5.7%.ConclusionIn the analysis of electronic patient records, different medical codes for a single condition may have varying clinical and prognostic significance; utilisation of different medical codes may change over time; researchers with differing clinical or epidemiological experience may have differing interpretations of the relevance of particular codes. There is a need for greater transparency in the selection of sets of codes for different conditions, for the reporting of sensitivity analyses using different sets of codes, as well as sharing of code sets among researchers.