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Background Staff sickness absenteeism and presenteeism (attending work while unwell) incur high costs to the NHS, are associated with adverse patient outcomes and have been exacerbated by the COVID-19 pandemic. The main causes are mental and musculoskeletal ill health with cardiovascular risk factors common. Objectives To undertake a feasibility study to inform the design of a definitive randomised controlled trial of the effectiveness and cost effectiveness of a health screening clinic in reducing absenteeism and presenteeism amongst the National Health Service staff. Design Individually randomised controlled pilot trial of the staff health screening clinic compared with usual care, including qualitative process evaluation. Setting Four United Kingdom National Health Service hospitals from two urban and one rural Trust. Participants Hospital employees who had not previously attended a pilot health screening clinic at Queen Elizabeth Hospital Birmingham. Interventions Nurse-led staff health screening clinic with assessment for musculoskeletal health (STarT musculoskeletal; STarT Back), mental health (patient health questionnaire-9; generalised anxiety disorder questionnaire-7) and cardiovascular health (NHS health check if aged ≥ 40, lifestyle check if < 40 years). Screen positives were given advice and/or referral to services according to UK guidelines. Main outcome measures The three coprimary outcomes were recruitment, referrals and attendance at referred services. These formed stop/go criteria when considered together. If any of these values fell into the ‘amber’ zone, then the trial would require modifications to proceed to full trial. If all were ‘red’, then the trial would be considered unfeasible. Secondary outcomes collected to inform the design of the definitive randomised controlled trial included: generalisability, screening results, individual referrals required/attended, health behaviours, acceptability/feasibility of processes, indication of contamination and costs. Outcomes related to the definitive trial included self-reported and employee records of absenteeism with reasons. Process evaluation included interviews with participants, intervention delivery staff and service providers. Descriptive statistics were presented and framework analysis conducted for qualitative data. Due to the COVID-19 pandemic, outcomes were captured up to 6 months only. Results Three hundred and fourteen participants were consented (236 randomised), the majority within 4 months. The recruitment rate of 314/3788 (8.3%) invited was lower than anticipated (meeting red for this criteria), but screening identified that 57/118 (48.3%) randomised were eligible for referral to either general practitioner (81%), mental health (18%) and/or physiotherapy services (30%) (green). Early trial closure precluded determination of attendance at referrals, but 31.6% of those eligible reported intending to attend (amber). Fifty-one of the 80 (63.75%) planned qualitative interviews were conducted. Quantitative and qualitative data from the process evaluation indicated that the electronic database-driven screening intervention and data collection were efficient, promoting good fidelity, although needing more personalisation at times. Recruitment and delivery of the full trial would benefit from a longer development period to better understand local context, develop effective strategies for engaging with underserved groups, provide longer training and better integration with referral services. Delivery of the pilot was limited by the impact of COVID-19 with staff redeployment, COVID-research prioritisation and reduced availability of community and in-house referral services. While recruitment was rapid, it did not fully represent ethnic minority groups and truncated follow-up due to funding limitations prevented full assessment of attendance at recommended services and secondary outcomes. Conclusions There is both a clinical need (evidenced by 48% screened eligible for a referral) and perceived benefit (data from the qualitative interviews) for this National Health Service staff health screening clinic. The three stop/go criteria were red, green and amber; therefore, the Trial Oversight Committee recommended that a full-scale trial should proceed, but with modifications to adapt to local context and adopt processes to engage better with underserved communities. Trial registration This trial is registered as ISRCTN10237475. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/42/42) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 23. See the NIHR Funding and Awards website for further award information. Plain language summary Sickness absenteeism and presenteeism (attendance at work while ill, with poor work performance) are major problems in the NHS and associated with worse patient health care. The most common causes of NHS staff sickness absenteeism and presenteeism are muscular complaints and mental ill health. Poor lifestyle and illnesses associated with heart disease are also important factors. Staff health checks might improve the health of NHS staff, but no studies have included screening tests to address the most common causes of poor staff health. This pilot study tested whether it would be possible to deliver a randomised controlled trial of an NHS staff health screening clinic, where some people get the screening check and others do not (chosen at random, like flipping a coin). We used an electronic database to capture all data. Participants completed initial questionnaires either at home or at work, then attended a face-to-face screening clinic using recognised screening questionnaires and tests to detect problems with muscular, mental or heart health. We considered how NHS staff and healthcare organisations would want the screening clinic and trial to run, how a diverse range of NHS staff could best be approached, how many staff might need to be invited and what their healthcare needs would be. The study ran in four UK NHS hospitals during the COVID-19 pandemic. Two hundred and thirty-six NHS staff participated, but early trial closure due to the pandemic meant that some results were unavailable. For the primary feasibility outcomes, although recruitment rates of around 8% were lower than anticipated, half of staff screened needed referral for further health care and one-third reported intending to attend. Staff felt that the clinic addressed an important health need. The Trial Oversight Committee recommended proceeding to a full-scale trial but with modifications to address findings from the process evaluation, including ways to encourage a wider group of NHS staff to take part. Scientific summary Background Staff sickness absenteeism and presenteeism (attending work while unwell) incur high costs to the NHS, are associated with adverse patient outcomes and have been exacerbated by the COVID-19 pandemic. The main causes are mental and musculoskeletal ill health with cardiovascular risk factors also common. Objectives The aim of this pilot trial was to assess the feasibility of a definitive randomised controlled trial (RCT) evaluating the clinical and cost effectiveness of a health screening clinic compared to usual care, in reducing sickness absenteeism and presenteeism amongst NHS staff. The key objectives were to: describe recruitment rates describe participant characteristics and assess generalisability compared to the hospital workforce describe intervention screening assessment results describe recommended referrals and their uptake assess the feasibility of measuring the outcomes relating to the definitive trial, and obtain an estimate of the standard deviation of the proposed primary outcomes for a full RCT assess levels of contamination between intervention and usual care arms to inform RCT design (individual vs. cluster RCT) describe and explain the fidelity to the intervention and evaluate the barriers and enablers to participation describe the views, experiences and satisfaction of participants and those delivering the health checks quantify the costs of undertaking the screening service and its consequences. Design A multicentre, two-arm, parallel group, open-label, 1 : 1 individually randomised pilot RCT of a complex intervention comparing a staff health screening clinic with usual care. Setting Three large urban hospitals and one rural district general hospital in the West Midlands. Participants All employees in the participating hospitals were eligible to participate except those who had previously attended a pilot health screening clinic at Queen Elizabeth Hospital Birmingham (QEHB) or who were currently taking part in another non-COVID drug trial or similar health and well-being trial. Participants were informed of the trial through staff meetings, noticeboards, posters and ward champions, and invited (with up to three reminders) through multiple approaches including e-mail and personal invitation. Wards were chosen to reflect the characteristics of the hospital. Data collection Potential participants joined the trial via weblink to a custom-designed electronic trial data collection platform hosted by the Birmingham Clinical Trials Unit. Eligibility questions, consent and a baseline questionnaire were completed prior to randomisation. Randomisation and blinding Participants were randomised to intervention or usual care (1 : 1 ratio) using an integrated randomisation module on the trial database, using a minimisation algorithm (with random element) to ensure balance on key characteristics. Interventions Intervention Staff health screening clinic with two stages: screening assessment for three components: mental health, musculoskeletal health and cardiovascular health, followed by appropriate advice and/or referral, according to level of risk, to appropriate services for management according to NHS/National Institute for Health and Care Excellence (NICE) recommendations. The screening assessment was delivered by trained research nurses using a standardised protocol. All data were captured by a customised database with prompts to guide the research nurses. Local pathways were used for referrals to lifestyle, physiotherapy, psychological and primary care services. Participants reporting relevant conditions already being treated did not receive the referral element of that component. A results letter detailing findings and recommendations was sent to participants and their general practitioners (GPs) for appropriate action. Usual care Standard access to medical services for management of any presenting condition. Main outcome measures This pilot trial was originally planned to have a 52-week follow-up period to fully test the processes for a definitive trial, but this was reduced to 26 weeks due to the pandemic delays and funding restrictions. Primary outcomes and stop/go criteria Three coprimary outcomes were originally planned to inform progression to the definitive trial: Recruitment (consented) as a proportion of those invited. Referral to any recommended services as a result of the three screening components (usually GP, local physiotherapy/community psychological services) – intervention arm only. Attendance at any recommended services at 26 weeks (self-report) – intervention arm only. We defined ‘referral’ as anyone who was eligible for a referral, that is they recorded a suitable risk value and were not already being treated for that condition. Due to the pandemic, only a small number of participants completed the 26-week follow-up assessment. Therefore, acceptance of the referral (signifying intention), which was collected during the screening assessment, was used as a proxy for attendance. The three coprimary outcomes formed stop/go criteria when considered together. If any of these values fell into the ‘amber’ zone, then the trial would require modifications to proceed to full trial. If all were ‘red’, then the trial would be considered unfeasible. Secondary outcomes were collected to inform the design of the definitive RCT and any modifications required. Secondary outcomes Comparison of baseline characteristics of included participants and hospital population. Description of intervention screening assessments results. Number/type of referrals to recommended services (intervention arm only). Attendance at each individual recommended service (intervention arm only). Lifestyle relevant to screening intervention advice and referrals (self-report at 26 weeks compared with baseline). Acceptability of intervention to participants and health screening clinic staff (interviews). Feasibility of trial processes (completeness of relevant data items, interviews). Indication of contamination (comparing pre/post data for health behaviours and health care/other service utilisation in control arm). Outcomes related to the definitive trial Absenteeism at 26 weeks with reasons, measured by days and spells. Self-reported absolute absenteeism, relative absenteeism and relative hours of work – for last 7 days and last 28 days [World Health Organization Health and Work Performance Questionnaire (WHO-HPQ)]. Self-reported absenteeism (6-month recall period). Employee records of absenteeism, the proposed primary outcome of the definitive trial. Routinely collected linked data from the NHS Electronic Staff Record Programme. Presenteeism at 26 weeks [self-reported absolute presenteeism and relative presenteeism for last 28 days (WHO-HPQ)]. Attendance at occupational health service at 26 weeks (self-report). Healthcare utilisation at 26 weeks (self-report) including GP consultations and hospital admissions. EuroQol-5 Dimensions, five-level version (EQ-5D-5L) index value measuring health-related quality of life (HRQoL) (EuroQol EQ-5D 5-level) at 26 weeks. Resource use and costs collected by self-report questionnaire to participants on health service utilisation and information from the screening assessment regarding duration and resources used. Sample size We aimed to recruit 480 participants (20 per week) in 24 weeks. With this sample size, the 95% confidence interval (CI) for the proportion of staff recruited could be estimated to be 4% either side of the estimate. Statistical methods Analyses were mainly descriptive. No statistical modelling was undertaken, and no p-values are reported. No subgroup analyses were planned. Process evaluation A mixed-methods process evaluation explored programme reach, fidelity of screening delivery, attendance at referrals and participants’ views of the intervention to support any modifications required for the design of the definitive trial. Quantitative data to support the process evaluation were obtained as above. Semistructured qualitative interviews/focus groups were conducted (choice of Zoom, telephone, face-to-face) to obtain views of relevant stakeholders [trial participants, enhancing the Health of NHS Staff (eTHOS) nurses, referral providers, outside agencies] on the feasibility and acceptability of the staff health screening intervention and trial and inform any protocol adaptations needed for a full trial. Due to the COVID-19 delays, a pragmatic approach was taken to sampling; all eligible participants in the intervention arm were invited to participate, and invitations were sent to all controls until the target number of participants had been reached. Data were recorded either on Zoom or an encrypted recorder and transferred via secure file transfer to an external company for transcription. Interviews were transcribed intelligent/clean verbatim and anonymised. A thematic analysis of content was informed by the framework analytical approach. Data collection and analysis ran concurrently so that the emergent analytical themes could inform further data collection. Health economic analysis A descriptive analysis was presented with average costs of screening per participant and quality of life obtained in the baseline questionnaire. Information was obtained from participating centres on estimated time taken for each screening clinic task, grade of the member of staff responsible and cost of individual blood tests. Staff time required for each task was then multiplied by the relevant unit costs obtained from standard source. The total cost of blood tests per participant was weighted according to the proportion who received each type of blood test. Quality of life of all participants was estimated using the EQ-5D-5L. Patient and public involvement Four to six clinical, administrative and retired NHS staff met on a regular basis throughout the project to provide advice. One hospital healthcare worker was included on the Trial Oversight Committee (TOC). Similarly, we consulted a stakeholder advisory group representing a wider body of professionals relevant to the trial, for example, GPs. Impact of COVID-19 pandemic on trial delivery It was not possible to commence the trial in March 2020 due to the COVID-19 pandemic. Two hospital sites commenced the trial in December 2020, but after 3–4 weeks, recruitment was paused. The trial recommenced in May 2021 in all four sites. The original trial was planned to include a 52-week follow-up; however, due to the delays, a 26-week follow-up was agreed with the funder, but only a few people reached this time point before trial closure. Results Three thousand seven hundred and eighty-eight of the 24,344 NHS staff across the four sites were invited to take part. Of the 353 eligible respondents, 314 consented (8.3% of those invited and 65.4% of our planned target of n = 480). Two hundred and thirty-six were randomised into the study; n = 118 to the intervention screening arm and 118 to usual care. One hundred and one (85.6%) attended and completed the screening clinic. Only 26/236 (11.0%) participants reached the 26-week follow-up. Primary outcomes and stop/go criteria Three hundred and fourteen of the 3788 [8.3% (95% CI 7.4% to 9.2%)] invited staff gave their consent to participate, which meets the red stop/go criterion for recruitment. Fifty-seven of the 118 [48.3% (95% CI 39.0% to 57.7%)] participants randomised to the intervention arm were eligible for referral to at least one service, which meets the green stop/go criterion for referral. Eighteen of the 57 [31.6% (95% CI 19.9% to 45.2%)] participants eligible for a referral accepted a referral to at least one service, which meets the amber stop–go progression criterion for attendance, although the CIs were wide. Secondary outcomes Assessing generalisability (programme reach) The invited population was similar to the hospital population, although those who participated in the trial were more likely to be white British (78.0% compared to 59.7%), allied health professionals (14.0% compared to 6.9%) and healthcare scientists (11.9% compared to 5.0%), and less likely to be from estates/ancillary, medical/dental and nursing/midwifery registered staff groups. Results of intervention screening assessments Most reported minimal/mild anxiety, but 11 (10.9%) were classified as having moderate and 5 (5.0%) severe anxiety. Most people reported minimal/mild depression, but 13 (12.9%) reported moderate/moderately severe depression and 4 (4.0%) severe depression. Most participants had no significant back pain, although eight (7.9%) were at medium risk and two (2.0%) at high risk on the StarT Back tool. Twenty-seven (27.0%) scored with medium risk for other types of pain and five (5.0%) high risk. Thirty-eight (38.0%) participants were classified as overweight and 32 (32.0%) obese. Forty-six (46.0%) were self-reported as physically active. Twelve (11.9%) reported increasing/higher risk of alcohol dependence and 10 (9.9%) were current smokers. Of those eligible for the cardiovascular risk score (QRISK2), nine (14.5%) had medium risk (10–19.9%) and two (3.2%) had a high risk of developing cardiovascular disease (CVD) in the next 10 years. Completeness of data items and attendance at screening clinic (fidelity) Sixty-six of the 314 (21.0%) consented participants did not complete the baseline questionnaire. One hundred and one of the 118 (86%) participants randomised to the intervention arm attended and completed the screening clinic. Individual data items were generally well completed and deoxyribonucleic acid (DNA) rates low. Costs and quality of life The maximum screening cost per participant (including blood tests) was £107.48 if the highest band staff were used and £99.98 if the lowest band staff ran the clinic. Complete EQ-5D-5L data were available for 233/236 randomised participants [mean score 0.793 (SD 0.168)]. Process evaluation We conducted 51 (63.8%) out of the 80 originally planned interviews. Four different hospital sites utilised a nurse-led screening intervention with prompts and electronic data collection, which was efficient and promoted good fidelity, although this was viewed as impersonal at times. Participants appreciated the convenience of the onsite service and valued time to focus on their own needs. However, some felt that it did not reflect or address their stress levels appropriately or meet their expectations in providing faster access to additional services. There were also concerns that it would not address the wider determinants of ill health and problems in the workplace, that it was just a ‘sticking plaster’. The eTHOS staff delivering the intervention generally found the delivery of the study feasible, although there were a number of suggestions from staff both delivering and receiving the intervention to adapt the approach for a full trial. Conclusions Despite significant delays, truncation and amendments required due to the COVID-19 pandemic, we were able to assess the most important aspects of the feasibility of a RCT to evaluate the clinical and cost effectiveness of a novel hospital-based staff health screening clinic in reducing absenteeism and presenteeism. Recruitment was feasible in a short space of time, and delivery of the intervention feasible, efficient and acceptable. Although a lower proportion of staff were recruited than anticipated, this was offset by the findings of the screening assessments which revealed significant health needs of those attending with 48% requiring referral to additional services. The three stop/go criteria were red, green and amber; therefore, the TOC recommended that a full-scale trial should proceed, but with modifications (see below) to adapt to local context and adopt processes to engage better with underserved communities, to improve both reach and effectiveness. Implications/modifications for full trial design There was no evidence of contamination; therefore, an individual RCT would remain the design of choice. Wait-list controls might also be a potential option to encourage people to participate. While our approach to recruitment was successful for many (most people responded to an e-mail), additional strategies would be needed to recruit the underserved groups, and specific minority staff network groups and leaders should be engaged in order to do so. Messaging to potential participants needs to be clearer in order to reduce concerns about confidentiality, optimise recruitment and manage expectations. More flexible clinic times/alternative options could be explored to improve inclusion. Electronic data capture was considered convenient, but extra training and practice should be provided to ensure sufficient familiarity and personalisation. Consideration (on a site-by-site basis) of clearer referral pathways is important for the full trial, in order to optimise attendance at referrals and realise health outcomes. Further consideration should also be given to the mental health screening tools used, as qualitative interviews with staff revealed their concerns that occupational stress and burnout may not be adequately identified and treated. There was no evidence from this study that self-reported absenteeism data should replace human resources (HR) data as the potential primary outcome as correlation between the two was poor. Acknowledging the 25% dropout between consent and randomisation, the amount of data collected and length of questionnaires should be reviewed prior to a full trial. Resource use and cost data were relatively straightforward to collect, although it was evident that more detailed site-by-site data collection would be required in a full trial, to reflect the full range of clinic organisation scenarios. Trial registration This trial is registered as ISRCTN10237475. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/42/42) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 23. See the NIHR Funding and Awards website for further award information.

Abstract Background The economic impact of managing long COVID in primary care is unknown. We estimated the costs of primary care consultations associated with long COVID and explored the relationship between risk factors and costs. Methods Data were obtained on non-hospitalised adults from the Clinical Practice Research Datalink Aurum primary care database. We used propensity score matching with an incremental cost method to estimate additional primary care consultation costs associated with long COVID (12 weeks after COVID-19) at an individual and UK national level. We applied multivariable regression models to estimate the association between risk factors and consultations costs beyond 12 weeks from acute COVID-19. Results Based on an analysis of 472,173 patients with COVID-19 and 472,173 unexposed individuals, the annual incremental cost of primary care consultations associated with long COVID was £2.44 per patient and £23,382,452 at the national level. Among patients with COVID-19, a long COVID diagnosis and reporting of longer-term symptoms were associated with a 43% and 44% increase in primary care consultation costs respectively, compared to patients without long COVID symptoms. Older age, female sex, obesity, being from a white ethnic group, comorbidities and prior consultation frequency were all associated with increased primary care consultation costs. Conclusions The costs of primary care consultations associated with long COVID in non-hospitalised adults are substantial. Costs are significantly higher among those diagnosed with long COVID, those with long COVID symptoms, older adults, females, and those with obesity and comorbidities.

Abstract Background Primary care electronic health records (EHR) are widely used to study long-term conditions in epidemiological and health services research. Therefore, it is important to understand how well the recorded prevalence of these conditions in EHRs, compares to other reliable sources overall, and varies by socio-demographic characteristics. We aimed to describe the prevalence and socio-demographic variation of cardiovascular, renal, and metabolic (CRM) and mental health (MH) conditions in a large, nationally representative, English primary care database and compare with prevalence estimates from other population-based studies. Methods This was a cross-sectional study using the Clinical Practice Research Datalink (CPRD) Aurum primary care database. We calculated prevalence of 18 conditions and used logistic regression to assess how this varied by age, sex, ethnicity, and socio-economic status. We searched the literature for population prevalence estimates from other sources for comparison with the prevalences in CPRD Aurum. Results Depression (16.0%, 95%CI 16.0–16.0%) and hypertension (15.3%, 95%CI 15.2–15.3%) were the most prevalent conditions among 12.4 million patients. Prevalence of most conditions increased with socio-economic deprivation and age. CRM conditions, schizophrenia and substance misuse were higher in men, whilst anxiety, depression, bipolar and eating disorders were more common in women. Cardiovascular risk factors (hypertension and diabetes) were more prevalent in black and Asian patients compared with white, but the trends in prevalence of cardiovascular diseases by ethnicity were more variable. The recorded prevalences of mental health conditions were typically twice as high in white patients compared with other ethnic groups. However, PTSD and schizophrenia were more prevalent in black patients. The prevalence of most conditions was similar or higher in the primary care database than diagnosed disease prevalence reported in national health surveys. However, screening studies typically reported higher prevalence estimates than primary care data, especially for PTSD, bipolar disorder and eating disorders. Conclusions The prevalence of many clinically diagnosed conditions in primary care records closely matched that of other sources. However, we found important variations by sex and ethnicity, which may reflect true variation in prevalence or systematic differences in clinical presentation and practice. Primary care data may underrepresent the prevalence of undiagnosed conditions, particularly in mental health.

Objectives Analysis of routinely collected electronic health data is a key tool for long-term condition research and practice for hospitalised patients. This requires accurate and complete ascertainment of a broad range of diagnoses, something not always recorded on an admission document at a single point in time. This study aimed to ascertain how far back in time electronic hospital records need to be interrogated to capture long-term condition diagnoses.Design Retrospective observational study of routinely collected hospital electronic health record data.Setting Queen Elizabeth Hospital Birmingham (UK)-linked data held by the PIONEER acute care data hub.Participants Patients whose first recorded admission for chronic obstructive pulmonary disease (COPD) exacerbation (n=560) or acute stroke (n=2142) was between January and December 2018 and who had a minimum of 10 years of data prior to the index date.Outcome measures We identified the most common International Classification of Diseases version 10-coded diagnoses received by patients with COPD and acute stroke separately. For each diagnosis, we derived the number of patients with the diagnosis recorded at least once over the full 10-year lookback period, and then compared this with shorter lookback periods from 1 year to 9 years prior to the index admission.Results Seven of the top 10 most common diagnoses in the COPD dataset reached >90% completeness by 6 years of lookback. Atrial fibrillation and diabetes were >90% coded with 2–3 years of lookback, but hypertension and asthma completeness continued to rise all the way out to 10 years of lookback. For stroke, 4 of the top 10 reached 90% completeness by 5 years of lookback; angina pectoris was >90% coded at 7 years and previous transient ischaemic attack completeness continued to rise out to 10 years of lookback.Conclusion A 7-year lookback captures most, but not all, common diagnoses. Lookback duration should be tailored to the conditions being studied.

Introduction Coexisting multiple health conditions is common among older people, a population that is increasing globally. The potential for polypharmacy, adverse events, drug interactions and development of additional health conditions complicates prescribing decisions for these patients. Artificial intelligence (AI)-generated decision-making tools may help guide clinical decisions in the context of multiple health conditions, by determining which of the multiple medication options is best. This study aims to explore the perceptions of healthcare professionals (HCPs) and patients on the use of AI in the management of multiple health conditions.Methods and analysis A qualitative study will be conducted using semistructured interviews. Adults (≥18 years) with multiple health conditions living in the West Midlands of England and HCPs with experience in caring for patients with multiple health conditions will be eligible and purposively sampled. Patients will be identified from Clinical Practice Research Datalink (CPRD) Aurum; CPRD will contact general practitioners who will in turn, send a letter to patients inviting them to take part. Eligible HCPs will be recruited through British HCP bodies and known contacts. Up to 30 patients and 30 HCPs will be recruited, until data saturation is achieved. Interviews will be in-person or virtual, audio recorded and transcribed verbatim. The topic guide is designed to explore participants’ attitudes towards AI-informed clinical decision-making to augment clinician-directed decision-making, the perceived advantages and disadvantages of both methods and attitudes towards risk management. Case vignettes comprising a common decision pathway for patients with multiple health conditions will be presented during each interview to invite participants’ opinions on how their experiences compare. Data will be analysed thematically using the Framework Method.Ethics and dissemination This study has been approved by the National Health Service Research Ethics Committee (Reference: 22/SC/0210). Written informed consent or verbal consent will be obtained prior to each interview. The findings from this study will be disseminated through peer-reviewed publications, conferences and lay summaries.

Background: Rather than first diagnosing and then deciding on treatment, GPs may intuitively decide on treatment and justify this through choice of diagnosis. Aim: To investigate the relationship between choice of a medicalising diagnosis and antibiotic treatment for throat-related consultations. Design & setting: A retrospective cohort study in a large database of UK electronic primary care records between 1 January 2010 and 1 January 2020. Method: All first throat-related consultations were included, categorised as either pharyngitis/tonsillitis or sore throat. The outcome was any antibiotic prescription on the consultation date. GP-level random effects on prescribing and on diagnosis were estimated in a series of mixed-effects regression models, including age, sex, weekday, month, and clinician characteristics as fixed effects. GPs were grouped into quintiles by antibiotic prescribing propensity, and described the proportion of patients they diagnosed with pharyngitis/tonsillitis or sore throat in each quintile. Results: The analysis dataset included 393 590 throat-related consultations with 6881 staff. Diagnosis of pharyngitis/tonsillitis was strongly associated with antibiotic prescribing (adjusted odds ratio = 13.41, 95% confidence interval = 12.8 to 14.04). GP random effect accounted for 18% of variation in prescribing and for 26% of variation in diagnosis. GPs in the lowest quintile of antibiotic prescribing propensity diagnosed pharyngitis/tonsillitis on 31% of occasions, compared with 55% in the highest quintile. Conclusion: There is substantial variation among GPs in diagnosis and treatment of throat-related problems. Preference for a medicalising diagnosis is associated with a preference for antibiotics, suggesting a common propensity to both diagnose and treat.

Background: Depression screening instruments are commonly used to assess the presence and severity of depression symptoms. However, there is little information on variation in depression screening scores over time within the same individual. Methods: A systematic review and meta-analysis was performed of studies reporting the within-subject variability of the Beck's Depression Inventory (BDI), Hospital Anxiety and Depression Scale (HADS), Patient Health Questionnaire-9 (PHQ-9) and Patient Health Questionnaire-2 (PHQ-2). Multiple databases were searched from inception to 14th July 2023. Title and abstract screening was performed in duplicate, full text screening and data extraction by one reviewer and verified by a second. Risk of bias was assessed with a modified COSMIN tool. Results: Of 2798 titles and abstracts and 157 full text articles screened, 41 met the inclusion criteria. No studies were on patients with depression, most had only two measurements, less than two weeks apart. The pooled estimates of ICCs (Intraclass Correlations) and 95 % confidence intervals for BDI, HADS, PHQ-9 and PHQ-2 were 0.89 (0.84–0.93), 0.89 (0.85–0.93), 0.84 (0.81–0.88) and 0.75 (0.56–0.93), respectively.Studies in healthy subgroups showed lower ICC than those with physical illness. Limitations: Assessment of variability is not the main aim of most papers assessing depression measurement instruments, so it is possible that some relevant papers have been missed. Conclusions: Within-subject scores for BDI, HADS and PHQ-9, show generally excellent agreement over periods of up to two weeks. However published data on within-subject variability is lacking over longer time periods and for patients with depression.

BackgroundMultimorbidity, characterised by the coexistence of multiple chronic conditions in an individual, is a rising public health concern. While much of the existing research has focused on cross-sectional patterns of multimorbidity, there remains a need to better understand the longitudinal accumulation of diseases. This includes examining the associations between important sociodemographic characteristics and the rate of progression of chronic conditions.Methods and findingsWe utilised electronic primary care records from 13.48 million participants in England, drawn from the Clinical Practice Research Datalink (CPRD Aurum), spanning from 2005 to 2020 with a median follow-up of 4.71 years (IQR: 1.78, 11.28). The study focused on 5 important chronic conditions: cardiovascular disease (CVD), type 2 diabetes (T2D), chronic kidney disease (CKD), heart failure (HF), and mental health (MH) conditions. Key sociodemographic characteristics considered include ethnicity, social and material deprivation, gender, and age. We employed a flexible spline-based parametric multistate model to investigate the associations between these sociodemographic characteristics and the rate of different disease transitions throughout multimorbidity development. Our findings reveal distinct association patterns across different disease transition types. Deprivation, gender, and age generally demonstrated stronger associations with disease diagnosis compared to ethnic group differences. Notably, the impact of these factors tended to attenuate with an increase in the number of preexisting conditions, especially for deprivation, gender, and age. For example, the hazard ratio (HR) (95% CI; p-value) for the association of deprivation with T2D diagnosis (comparing the most deprived quintile to the least deprived) is 1.76 ([1.74, 1.78]; p < 0.001) for those with no preexisting conditions and decreases to 0.95 ([0.75, 1.21]; p = 0.69) with 4 preexisting conditions. Furthermore, the impact of deprivation, gender, and age was typically more pronounced when transitioning from an MH condition. For instance, the HR (95% CI; p-value) for the association of deprivation with T2D diagnosis when transitioning from MH is 2.03 ([1.95, 2.12], p < 0.001), compared to transitions from CVD 1.50 ([1.43, 1.58], p < 0.001), CKD 1.37 ([1.30, 1.44], p < 0.001), and HF 1.55 ([1.34, 1.79], p < 0.001). A primary limitation of our study is that potential diagnostic inaccuracies in primary care records, such as underdiagnosis, overdiagnosis, or ascertainment bias of chronic conditions, could influence our results.ConclusionsOur results indicate that early phases of multimorbidity development could warrant increased attention. The potential importance of earlier detection and intervention of chronic conditions is underscored, particularly for MH conditions and higher-risk populations. These insights may have important implications for the management of multimorbidity.

Abstract Background Staff absenteeism and presenteeism incur high costs to the NHS and are associated with adverse health outcomes. The main causes are musculoskeletal complaints and mental ill-health, which are potentially modifiable, and cardiovascular risk factors are also common. We will test the feasibility of an RCT to evaluate the clinical and cost-effectiveness of an employee health screening clinic on reducing sickness absenteeism and presenteeism. Methods This is an individually randomised controlled pilot trial aiming to recruit 480 participants. All previously unscreened employees from four hospitals within three UK NHS hospital Trusts will be eligible. Those randomised to the intervention arm will be invited to attend an employee health screening clinic consisting of a screening assessment for musculoskeletal (STarT MSK and STarT Back), mental (PHQ-9 and GAD-7) and cardiovascular (NHS Health Check if aged ≥ 40, lifestyle check if < 40 years) health. Screen positives will be given advice and/or referral to recommended services. Those randomised to the control arm will receive usual care. Participants will complete a questionnaire at baseline and 26 weeks; anonymised absenteeism and staff demographics will also be collected from personnel records. The co-primary outcomes are as follows: recruitment, referrals and uptake of recommended services in the intervention arm. Secondary outcomes include the following: results of screening assessments, uptake of individual referrals, reported changes in health behaviours, acceptability and feasibility of intervention, indication of contamination and costs. Outcomes related to the definitive trial include self-reported and employee records of absenteeism with reasons. Process evaluation to inform a future trial includes interviews with participants, intervention delivery staff and service providers receiving referrals. Analyses will include presentation of descriptive statistics, framework analysis for qualitative data and costs and consequences presented for health economics. Discussion The study will provide data to inform the design of a definitive RCT which aims to find an effective and cost-effective method of reducing absenteeism and presenteeism amongst NHS staff. The feasibility study will test trial procedures, and process outcomes, including the success of strategies for including underserved groups, and provide information and data to help inform the design and sample size for a definitive trial. Trial registration ISRCTN reference number 10237475 .

Background: The UK introduced financial incentives for management of atrial fibrillation (AF) in 2006, after which there was an increase in the proportion of patients with AF diagnosed as resolved. Removal of incentives in Scotland provides a natural experiment to investigate the effects of withdrawal of an incentive on diagnosis of resolved AF. Aim: To investigate the effects of introduction and withdrawal of financial incentives on the diagnosis of resolved AF. Design & setting: Cohort study in a large database of UK primary care records, before and after introduction of incentives in April 2006 in Scotland, England, and Northern Ireland, and their withdrawal in April 2016 in Scotland. Method: Interrupted time-series analysis of monthly rates of resolved AF from January 2000–September 2019. Results: A total of 251 526 adult patients with AF were included, of whom 14 674 were diagnosed as resolved AF. In April 2006 there were similar shift-changes in rates of resolved AF per 1000 in England 1.55 (95% confidence interval [CI] = 1.11 to 2.00) and Northern Ireland 1.54 (95% CI = 0.91 to 2.18), and a smaller increase in Scotland 0.79 (95% CI = 0.04 to 1.53). There were modest downward post-introduction trends in all countries. After Scotland’s withdrawal of the incentive in April 2016 there was a small, statistically non-significant, downward shift in rate of resolved AF per 1000 (0.39 [95% CI = -3.21 to 2.42]) and no change in post-removal trend. Conclusion: Introduction of a financial incentive coincided with an increase in resolved AF but no evidence was found that its withdrawal led to a reduction.

Abstract Introduction Renin-angiotensin system (RAS) inhibitors have been postulated to influence susceptibility to Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). This study investigated whether there is an association between their prescription and the incidence of COVID-19 and all-cause mortality. Methods We conducted a propensity-score matched cohort study comparing the incidence of COVID-19 among patients with hypertension prescribed angiotensin-converting enzyme I (ACE) inhibitors or angiotensin II type-1 receptor blockers (ARBs) to those treated with calcium channel blockers (CCBs) in a large UK-based primary care database (The Health Improvement Network). We estimated crude incidence rates for confirmed/suspected COVID-19 in each drug exposure group. We used Cox proportional hazards models to produce adjusted hazard ratios for COVID-19. We assessed all-cause mortality as a secondary outcome. Results The incidence rate of COVID-19 among users of ACE inhibitors and CCBs was 9.3 per 1000 person-years (83 of 18,895 users [0.44%]) and 9.5 per 1000 person-years (85 of 18,895 [0.45%]), respectively. The adjusted hazard ratio was 0.92 (95% CI 0.68 to 1.26). The incidence rate among users of ARBs was 15.8 per 1000 person-years (79 out of 10,623 users [0.74%]). The adjusted hazard ratio was 1.38 (95% CI 0.98 to 1.95). There were no significant associations between use of RAS inhibitors and all-cause mortality. Conclusion Use of ACE inhibitors was not associated with the risk of COVID-19 whereas use of ARBs was associated with a statistically non-significant increase compared to the use of CCBs. However, no significant associations were observed between prescription of either ACE inhibitors or ARBs and all-cause mortality.

Background Severe mental illness (SMI; schizophrenia, bipolar disorders (BDs), and other nonorganic psychoses) is associated with increased risk of cardiovascular disease (CVD) and CVD-related mortality. To date, no systematic review has investigated changes in population level CVD-related mortality over calendar time. It is unclear if this relationship has changed over time in higher-income countries with changing treatments. Methods and findings To address this gap, a systematic review was conducted, to assess the association between SMI and CVD including temporal change. Seven databases were searched (last: November 30, 2021) for cohort or case–control studies lasting ≥1 year, comparing frequency of CVD mortality or incidence in high-income countries between people with versus without SMI. No language restrictions were applied. Random effects meta-analyses were conducted to compute pooled hazard ratios (HRs) and rate ratios, pooled standardised mortality ratios (SMRs), pooled odds ratios (ORs), and pooled risk ratios (RRs) of CVD in those with versus without SMI. Temporal trends were explored by decade. Subgroup analyses by age, sex, setting, world region, and study quality (Newcastle–Ottawa scale (NOS) score) were conducted. The narrative synthesis included 108 studies, and the quantitative synthesis 59 mortality studies (with (≥1,841,356 cases and 29,321,409 controls) and 28 incidence studies (≥401,909 cases and 14,372,146 controls). The risk of CVD-related mortality for people with SMI was higher than controls across most comparisons, except for total CVD-related mortality for BD and cerebrovascular accident (CVA) for mixed SMI. Estimated risks were larger for schizophrenia than BD. Pooled results ranged from SMR = 1.55 (95% confidence interval (CI): 1.33 to 1.81, p < 0.001), for CVA in people with BD to HR/rate ratio = 2.40 (95% CI: 2.25 to 2.55, p < 0.001) for CVA in schizophrenia. For schizophrenia and BD, SMRs and pooled HRs/rate ratios for CHD and CVD mortality were larger in studies with outcomes occurring during the 1990s and 2000s than earlier decades (1980s: SMR = 1.14, 95% CI: 0.57 to 2.30, p = 0.71; 2000s: SMR = 2.59, 95% CI: 1.93 to 3.47, p < 0.001 for schizophrenia and CHD) and in studies including people with younger age. The incidence of CVA, CVD events, and heart failure in SMI was higher than controls. Estimated risks for schizophrenia ranged from HR/rate ratio 1.25 (95% CI: 1.04 to 1.51, p = 0.016) for total CVD events to rate ratio 3.82 (95% CI: 3.1 to 4.71, p < 0.001) for heart failure. Incidence of CHD was higher in BD versus controls. However, for schizophrenia, CHD was elevated in higher-quality studies only. The HR/rate ratios for CVA and CHD were larger in studies with outcomes occurring after the 1990s. Study limitations include the high risk of bias of some studies as they drew a comparison cohort from general population rates and the fact that it was difficult to exclude studies that had overlapping populations, although attempts were made to minimise this. Conclusions In this study, we found that SMI was associated with an approximate doubling in the rate ratio of CVD-related mortality, particularly since the 1990s, and in younger groups. SMI was also associated with increased incidence of CVA and CHD relative to control participants since the 1990s. More research is needed to clarify the association between SMI and CHD and ways to mitigate this risk. Amanda Lambert and co-workers study associations between severe mental illness and cardiovascular disease outcomes over time. Author summary Why was this study done? Previous research has identified higher incidence and mortality from cardiovascular disease (CVD) in people with severe mental illness (SMI) than those without SMI. It is not known whether the gap has changed over time. What did the researchers do and find? We conducted a comprehensive systematic review and meta-analysis of 108 cohort and case–control studies, including over 30 million participants. Compared to the general population, people with SMI, particularly schizophrenia, generally had higher levels of cardiovascular-related mortality and a higher incidence of CVD. For schizophrenia and bipolar disorder (BD), the rate ratios for coronary heart disease (CHD) mortality and cardiovascular mortality were larger in the 1990s and 2000s than in earlier studies, and the rate ratios were larger in younger people. What do these findings mean? We confirmed a strong association between SMI and incidence of and mortality from CVD. This association became stronger in the 1990s and 2000s.

Introduction Individuals with COVID-19 frequently experience symptoms and impaired quality of life beyond 4–12 weeks, commonly referred to as Long COVID. Whether Long COVID is one or several distinct syndromes is unknown. Establishing the evidence base for appropriate therapies is needed. We aim to evaluate the symptom burden and underlying pathophysiology of Long COVID syndromes in non-hospitalised individuals and evaluate potential therapies.Methods and analysis A cohort of 4000 non-hospitalised individuals with a past COVID-19 diagnosis and 1000 matched controls will be selected from anonymised primary care records from the Clinical Practice Research Datalink, and invited by their general practitioners to participate on a digital platform (Atom5). Individuals will report symptoms, quality of life, work capability and patient-reported outcome measures. Data will be collected monthly for 1 year.Statistical clustering methods will be used to identify distinct Long COVID-19 symptom clusters. Individuals from the four most prevalent clusters and two control groups will be invited to participate in the BioWear substudy which will further phenotype Long COVID symptom clusters by measurement of immunological parameters and actigraphy.We will review existing evidence on interventions for postviral syndromes and Long COVID to map and prioritise interventions for each newly characterised Long COVID syndrome. Recommendations will be made using the cumulative evidence in an expert consensus workshop. A virtual supportive intervention will be coproduced with patients and health service providers for future evaluation.Individuals with lived experience of Long COVID will be involved throughout this programme through a patient and public involvement group.Ethics and dissemination Ethical approval was obtained from the Solihull Research Ethics Committee, West Midlands (21/WM/0203). Research findings will be presented at international conferences, in peer-reviewed journals, to Long COVID patient support groups and to policymakers.Trial registration number 1567490.

Abstract Background The database used for the NHS Bowel Cancer Screening Programme (BCSP) derives participant information from primary care records. Combining predictors with FOBTs has shown to improve referral decisions and accuracy. The richer data available from GP databases could be used to complement screening referral decisions by identifying those at greatest risk of colorectal cancer. We determined the availability of data for key predictors and whether this information could be used to inform more accurate screening referral decisions. Methods An English BCSP cohort was derived using the electronic notifications received from the BCSP database to GP records. The cohort covered a period between 13th May 2009 to 17th January 2017. Completeness of variables and univariable associations were assessed. Risk prediction models were developed using Cox regression and multivariable fractional polynomials with backwards elimination. Optimism adjusted performance metrics were reported. The sensitivity and specificity of a combined approach using the negative FOBT model plus FOBT positive patients was determined using a probability equivalent to a 3% PPV NICE guidelines level. Results 292,059 participants aged 60–74 were derived for the BCSP screening cohort. A model including the screening test result had a C-statistic of 0.860, c-slope of 0.997, and R2 of 0.597. A model developed for negative screening results only had a C-statistic of 0.597, c-slope of 0.940, and R2 of 0.062. Risk predictors included in the models included; age, sex, alcohol consumption, IBS diagnosis, family history of gastrointestinal cancer, smoking status, previous negatives and whether a GP had ordered a blood test. For the combined screening approach, sensitivity increased slightly from 53.90% (FOBT only) to 58.82% but at the expense of an increased referral rate. Conclusions This research has identified several potential predictors for CRC in a BCSP population. A risk prediction model developed for BCSP FOBT negative patients was not clinically useful due to a low sensitivity and increased referral rate. The predictors identified in this study should be investigated in a refined algorithm combining the quantitative FIT result. Combining data from multiple sources enables fuller patient profiles using the primary care and screening database interface.

BackgroundResearch conducted in the United States suggests that two primes (citrus smells and pictures of a person's eyes) can increase hand gel dispenser use on the day they are introduced in hospital. The current study, conducted at a hospital in the United Kingdom, evaluated the effectiveness of these primes, both in isolation and in combination, at the entry way to four separate wards, over a longer duration than the previous work.MethodsA crossover randomized controlled trial was conducted. Four wards were allocated for 6 weeks of observation to each of four conditions, including “control,” “olfactory,” “visual,” or “both” (i.e., “olfactory” and “visual” combined). It was hypothesized that hand hygiene compliance would be greater in all priming conditions relative to the control condition. The primary outcome was whether people used the gel dispenser when they entered the wards. After the trial, a follow up survey of staff at the same hospital assessed the barriers to, and facilitators of, hand hygiene compliance. The trial data were analyzed using regression techniques and the survey data were analyzed using descriptive statistics.ResultsThe total number of individuals observed in the trial was 9,811 (female = 61%), with similar numbers across conditions, including “control” N = 2,582, “olfactory” N = 2,700, “visual” N = 2,488, and “both” N = 2,141. None of the priming conditions consistently increased hand hygiene. The lowest percentage compliance was observed in the “both” condition (7.8%), and the highest was observed in the “visual” condition (12.7%). The survey was completed by 97 staff (female = 81%). “Environmental resources” and “social influences” were the greatest barriers to staff cleaning their hands.ConclusionsTaken together, the current findings suggest that the olfactory and visual priming interventions investigated do not influence hand hygiene consistently. To increase the likelihood of such interventions succeeding, future research should focus on prospectively determined mechanisms of action.

Background: Statins and antihypertensive agents are recommended for primary prevention of cardiovascular disease (CVD), but they are not always prescribed to eligible patients. Design & setting: A systematic review of qualitative studies. Aim: To explore health professionals’ and patients’ attitudes towards cardiovascular preventive drugs. Method: MEDLINE, Embase, PsychINFO, CINAHL, ASSIA, HMIC, Conference Proceedings Citation Index, and Open Grey were searched for studies of qualitative design without restrictions on date or language. Two reviewers performed study selection, data extraction, quality assessment, and thematic synthesis. Results: In total, 2585 titles and abstracts were screened, yielding 27 studies, of which five met eligibility criteria on full text assessment. These included 62 patients and 47 health professionals. Five themes emerged about patient attitudes: questioning preventive drugs; perceived benefit and risks, such as improving quality of life; patient preferences; trust in health professional judgement; and family, friends, and media influences. Five themes emerged about health professional attitudes: addressing patient concerns and information; duty as a health professional to prescribe; uncertainty about preventive drug prescribing; recognising consequences of prescribing, such as unnecessary medicalisation; and personalised treatment. Conclusion: The attitudes of patients and health professionals regarding drug initiation for primary prevention reflect the complexity of the patient–health professional encounter in primary practice. For prescribing to be more adherent to guidelines, research should further investigate the patient–health professional relationship and the appropriate communication methods required when discussing drug initiation, specifically for primary prevention.

The ADO (age, dyspnoea, airflow obstruction) score predicts 3-year overall mortality among chronic obstructive pulmonary disease (COPD) patients. Information on the changes in COPD prognostic scores is sparse and it is unclear if the ADO score should be measured serially. We followed 4804 UK COPD patients with three or more ADO measurements from The Health Improvement Network (2005–2014) in a retrospective open cohort design. Patient's ADO scores were calculated once per year unless an obstruction or dyspnoea measurement was missing. Cox regression models assessed the independent role of serial ADO scores on mortality. The associations between baseline patient characteristics and long-term change in ADO scores were assessed using linear mixed effect models. Fewer than 7% of patients had worsened (i.e. increased) by ≥1 point per year after a median follow-up of 4.4 years. There was strong evidence that patients with more rapid worsening in ADO scores had increased mortality (hazard ratio 2.00 (95% CI 1.59–2.52) per 1 point increase in ADO per year). More rapid ADO score worsening was seen among current smokers (rate difference 0.059 (95% CI 0.031–0.087); p=0.001) and ex-smokers (0.028 (95% CI 0.003–0.054); p=0.032) and patients with depression (0.038 (95% CI 0.005–0.071); p=0.022), while overweight (−0.0347 (95% CI −0.0544– −0.0150); p=0.001) and obese (−0.0412 (95% CI −0.0625– −0.0198); p

Background: Atrial fibrillation (AF) is the most common type of cardiac arrhythmia and is associated with an increased risk of stroke and congestive heart failure. Lead-I electrocardiogram (ECG) devices are handheld instruments that can be used to detect AF at a single time point in people who present with relevant signs or symptoms. Objective: To assess the diagnostic test accuracy, clinical impact and cost-effectiveness of using single time point lead-I ECG devices for the detection of AF in people presenting to primary care with relevant signs or symptoms, and who have an irregular pulse compared with using manual pulse palpation (MPP) followed by a 12-lead ECG in primary or secondary care. Data sources: MEDLINE, MEDLINE Epub Ahead of Print and MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, PubMed, Cochrane Databases of Systematic Reviews, Cochrane Central Database of Controlled Trials, Database of Abstracts of Reviews of Effects and the Health Technology Assessment Database. Methods: The systematic review methods followed published guidance. Two reviewers screened the search results (database inception to April 2018), extracted data and assessed the quality of the included studies. Summary estimates of diagnostic accuracy were calculated using bivariate models. An economic model consisting of a decision tree and two cohort Markov models was developed to evaluate the cost-effectiveness of lead-I ECG devices. Results: No studies were identified that evaluated the use of lead-I ECG devices for patients with signs or symptoms of AF. Therefore, the diagnostic accuracy and clinical impact results presented are derived from an asymptomatic population (used as a proxy for people with signs or symptoms of AF). The summary sensitivity of lead-I ECG devices was 93.9% [95% confidence interval (CI) 86.2% to 97.4%] and summary specificity was 96.5% (95% CI 90.4% to 98.8%). One study reported limited clinical outcome data. Acceptability of lead-I ECG devices was reported in four studies, with generally positive views. The de novo economic model yielded incremental cost-effectiveness ratios (ICERs) per quality-adjusted life-year (QALY) gained. The results of the pairwise analysis show that all lead-I ECG devices generated ICERs per QALY gained below the £20,000–30,000 threshold. Kardia Mobile (AliveCor Ltd, Mountain View, CA, USA) is the most cost-effective option in a full incremental analysis. Limitations: No published data evaluating the diagnostic accuracy, clinical impact or cost-effectiveness of lead-I ECG devices for the population of interest are available. Conclusions: Single time point lead-I ECG devices for the detection of AF in people with signs or symptoms of AF and an irregular pulse appear to be a cost-effective use of NHS resources compared with MPP followed by a 12-lead ECG in primary or secondary care, given the assumptions used in the base-case model. Future work: Studies assessing how the use of lead-I ECG devices in this population affects the number of people diagnosed with AF when compared with current practice would be useful. Study registration: This study is registered as PROSPERO CRD42018090375. Funding: The National Institute for Health Research Health Technology Assessment programme.

Abstract Background The risk of chronic kidney disease (CKD) is known to be elevated in patients with diabetes mellitus but the risk of young adults aged 18 to 40 years with impaired glucose tolerance/impaired fasting glucose (IGT/IFG) developing CKD is not well characterised. Furthermore, progression of IGT/IFG to diabetes and subsequent CKD development is not well understood. Methods A retrospective cohort study was undertaken using The Health Improvement Network (THIN) database, a large dataset of electronic patient records. THIN database is jointly managed by IMS Health Real World Evidence Solution (http://www.epic-uk.org/index.html) and In Practice System (InPs). Cases were aged 18 to 40, with a diagnosis of IGT/IFG and registered at a practice contributing to THIN between 2000 and 2015. The study population consisted of 40,092 patients, including 21,454 (53.5%) female and 18,638 (46.5%) male. The median follow-up was approximately 2 years. The outcome was a diagnosis of CKD determined from either clinical coding or laboratory results. For the primary analysis the unadjusted and adjusted relative risk of CKD in IGT/IFG was compared to age, sex and practice matched controls with normoglycaemia. For the secondary analysis we compared the incidence of CKD before to after a diagnosis of type 2 diabetes (T2DM) in the IGT/IFG study cohort. Results The Incidence Rate Ratio (IRR) for CKD for IGT/IFG compared to normoglycaemia was 4.0 [95% confidence interval (CI), 3.2 to 5.1, P

Plain English summary What is the problem and why is this important? Mini-strokes are similar to full strokes, but symptoms last less than 24 h. Many people (up to 70%) have long-term problems after a mini-stroke, such as anxiety; depression; problems with brain functioning (like memory loss); and fatigue (feeling tired). However, the current healthcare pathway only focuses on preventing another stroke and care for other long-term problems is not routinely given. Without proper treatment, people with long-term problems after a mini-stroke could have worse quality of life and may find it difficult to return to work and their social activities. What is the aim of the research? We wanted to understand the research priorities of patients, health care professionals and key stakeholders relating to the long-term impact of mini-stroke. How did we address the problem? We invited patients, clinicians, researchers and other stakeholders to attend a meeting. At the meeting people discussed the issues relating to the long-term impact of mini-stroke and came to an agreement on their research priorities. There were three stages: (1) people wrote down their individual research suggestions; (2) in smaller groups people came to an agreement on what their top research questions were; and (3) the whole group agreed final research priorities. What did we find? Eleven people attended who were representatives for patients, GPs, stroke consultants, stroke nurses, psychologists, the Stroke Association (charity) and stroke researchers, The group agreed on eleven research questions which they felt were the most important to improve health and well-being for people who have had a mini-stroke. The eleven research questions encompass a range of categories, including: understanding the existing care patients receive (according to diagnosis and geographical location); exploring what optimal care post-TIA/minor stroke should comprise (identifying and treating impairments, information giving and support groups) and how that care should be delivered (clinical setting and follow-up pathway); impact on family members; and education/training for health care professionals. Abstract Background Clinical management after transient ischaemic attack (TIA) and minor stroke focuses on stroke prevention. However, evidence demonstrates that many patients experience ongoing residual impairments. Residual impairments post-TIA and minor stroke may affect patients’ quality of life and return to work or social activities. Research priorities of patients, health care professionals and key stakeholders relating to the long-term impact of TIA and minor stroke are unknown. Methods Our objective was to establish the top shared research priorities relating to the long-term impact of TIA and minor stroke through stakeholder-centred consensus. A one-day priority setting consensus meeting took place with representatives from different stakeholder groups in October 2016 (Birmingham, UK). Nominal group technique was used to establish research priorities. This involved three stages: (i) gathering research priorities from individual stakeholders; (ii) interim prioritisation in three subgroups; and (iii) final priority setting. Results The priority setting consensus meeting was attended by 11 stakeholders. The individual stakeholders identified 34 different research priorities. During the interim prioritisation exercise, the three subgroups generated 24 unique research priorities which were discussed as a whole group. Following the final consensus discussion, 11 shared research priorities were unanimously agreed. The 11 research questions encompass a range of categories, including: understanding the existing care patients receive (according to diagnosis and geographical location); exploring what optimal care post-TIA/minor stroke should comprise (identifying and treating impairments, information giving and support groups) and how that care should be delivered (clinical setting and follow-up pathway); impact on family members; and education/training for health care professionals. Conclusions Eleven different research priorities were established through stakeholder-centred consensus. These research questions could usefully inform the research agenda and policy decisions for TIA and minor stroke. Inclusion of stakeholders in setting research priorities is important to increase the relevance of research and reduce research waste.

BackgroundAtrial fibrillation (AF) is the most common type of cardiac arrhythmia and is associated with increased risk of stroke and congestive heart failure. Lead-I electrocardiogram (ECG) devices are handheld instruments that can detect AF at a single-time point.PurposeTo assess the diagnostic test accuracy, clinical impact and cost effectiveness of single-time point lead-I ECG devices compared with manual pulse palpation (MPP) followed by a 12-lead ECG for the detection of AF in symptomatic primary care patients with an irregular pulse.MethodsElectronic databases (MEDLINE, MEDLINE Epub Ahead of Print and MEDLINE In-Process, EMBASE, PubMed and Cochrane Databases of Systematic Reviews, Cochrane Central Database of Controlled Trials, Database of Abstracts of Reviews of Effects, Health Technology Assessment Database) were searched to March 2018. Two reviewers screened the search results, extracted data and assessed study quality. Summary estimates of diagnostic accuracy were calculated using bivariate models. Cost-effectiveness was evaluated using an economic model consisting of a decision tree and two cohort Markov models.ResultsDiagnostic accuracy The diagnostic accuracy (13 publications reporting on nine studies) and clinical impact (24 publications reporting on 19 studies) results are derived from an asymptomatic population (used as a proxy for people with signs or symptoms of AF). The summary sensitivity of lead-I ECG devices was 93.9% (95% confidence interval [CI]: 86.2% to 97.4%) and summary specificity was 96.5% (95% CI: 90.4% to 98.8%). Cost effectiveness The de novo economic model yielded incremental cost effectiveness ratios (ICERs) per quality adjusted life year (QALY) gained. The results of the pairwise analysis show that all lead-I ECG devices generate ICERs per QALY gained below the £20,000-£30,000 threshold. Kardia Mobile is the most cost effective option in a full incremental analysis. Lead-I ECG tests may identify more AF cases than the standard diagnostic pathway. This comes at a higher cost but with greater patient benefit in terms of mortality and quality of life.LimitationsNo published data evaluating the diagnostic accuracy, clinical impact or cost effectiveness of lead-I ECG devices for the target population are available.ConclusionsThe use of single-time point lead-I ECG devices in primary care for the detection of AF in people with signs or symptoms of AF and an irregular pulse appears to be a cost effective use of NHS resources compared with MPP followed by a 12-lead ECG, given the assumptions used in the base case model.RegistrationThe protocol for this review is registered on PROSPERO as CRD42018090375.

Objective: We investigate (1) the influence of ethnic, gender, and age concordance with interviewers and (2) how expression of qualitative data varies between interviews delivered in English and community languages (Punjabi/Urdu) with monolingual and bilingual participants across three generations of the Indian Sikh and Pakistani Muslim communities living in the UK. Methods: We analyzed and interpreted semi-structured interview transcripts that were designed to collect data about lifestyles, disease management, community practices/beliefs, and social networks. First, qualitative content analysis was applied to transcripts. Second, a framework was applied as a guide to identify cross-language illustrations where responses varied in length, expression and depth. Results: Participant responses differed by language and topic. First-generation migrants when discussing religion, culture, or family practice were far likelier to use group or community narratives and give a longer response, indicating familiarity with or importance of such issues. Ethnic and gender concordance generated greater rapport between researchers and participants centered on community values and practices. Further, open-ended questions that were less direct were better suited for first-generation migrants. Conclusion: Community-based researchers need more time to complete interviews in second languages, need to acknowledge that narratives can be contextualized in both personal and community views, and reframe questions that may lead to greater expression. Furthermore, we detail a number of recommendations with regard to validating the translation of interviews from community languages to English as well as measures for testing language proficiency.

Background: Patients with symptoms of possible colorectal cancer are not always referred for investigation. Aim: To ascertain barriers and facilitators to GP referral of patients meeting the National Institute for Health and Care Excellence (NICE) guidelines for urgent referral for suspected colorectal cancer. Design & setting: Qualitative study in the context of a feasibility study using information technology in GP practices to flag-up patients meeting urgent referral criteria for colorectal cancer. Method: Semi-structured interview with 18 GPs and 12 practice managers, focusing on early detection of colorectal cancer, issues in the use of information technology to identify patients and GP referral of these patients for further investigation were audiotaped, transcribed verbatim, and analysed according to emergent themes. Results: There were two main themes: wide variation in willingness to refer and uncertainty about whether to refer; and barriers to referral. Three key messages emerged: there was a desire to avoid over-referral, lack of knowledge of guidelines, and the use of individually-derived decision rules for further investigation or referral of symptoms. Some GPs were unaware that iron deficiency anaemia or persistent diarrhoea are urgent referral criteria. Alternatives to urgent referral included undertaking no investigations, trials of iron therapy, use of faecal occult blood tests (FOBt) and non-urgent referral. In minority ethnic groups (South Asians) anaemia was often accepted as normal. Concerns about over-referral were linked to financial pressures and perceived criticism by healthcare commissioners, and a reluctance to scare patients by discussing suspected cancer. Conclusion: GPs’ lack of awareness of referral guidelines and concerns about over-referral are barriers to early diagnosis of colorectal cancer.

BackgroundPatient-reported outcome measures (PROMs) can provide valuable information which may assist with the care of patients with chronic kidney disease (CKD). However, given the large number of measures available, it is unclear which PROMs are suitable for use in research or clinical practice. To address this we comprehensively evaluated studies that assessed the measurement properties of PROMs in adults with CKD.MethodsFour databases were searched; reference list and citation searching of included studies was also conducted. The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist was used to appraise the methodological quality of the included studies and to inform a best evidence synthesis for each PROM.ResultsThe search strategy retrieved 3,702 titles/abstracts. After 288 duplicates were removed, 3,414 abstracts were screened and 71 full-text articles were retrieved for further review. Of these, 24 full-text articles were excluded as they did not meet the eligibility criteria. Following reference list and citation searching, 19 articles were retrieved bringing the total number of papers included in the final analysis to 66. There was strong evidence supporting internal consistency and moderate evidence supporting construct validity for the Kidney Disease Quality of Life-36 (KDQOL-36) in pre-dialysis patients. In the dialysis population, the KDQOL-Short Form (KDQOL-SF) had strong evidence for internal consistency and structural validity and moderate evidence for test-retest reliability and construct validity while the KDQOL-36 had moderate evidence of internal consistency, test-retest reliability and construct validity. The End Stage Renal Disease-Symptom Checklist Transplantation Module (ESRD-SCLTM) demonstrated strong evidence for internal consistency and moderate evidence for test-retest reliability, structural and construct validity in renal transplant recipients.ConclusionsWe suggest considering the KDQOL-36 for use in pre-dialysis patients; the KDQOL-SF or KDQOL-36 for dialysis patients and the ESRD-SCLTM for use in transplant recipients. However, further research is required to evaluate the measurement error, structural validity, responsiveness and patient acceptability of PROMs used in CKD.

Stroke is a leading cause of death and disability; worldwide it is estimated that 16.9 million people have a first stroke each year. Lipid-lowering, anticoagulant, and antihypertensive drugs can prevent strokes, but may be underused.We analysed anonymised electronic primary care records from a United Kingdom (UK) primary care database that covers approximately 6% of the UK population. Patients with first-ever stroke/transient ischaemic attack (TIA), ≥18 y, with diagnosis between 1 January 2009 and 31 December 2013, were included. Drugs were considered under-prescribed when lipid-lowering, anticoagulant, or antihypertensive drugs were clinically indicated but were not prescribed prior to the time of stroke or TIA. The proportions of strokes or TIAs with prevention drugs under-prescribed, when clinically indicated, were calculated. In all, 29,043 stroke/TIA patients met the inclusion criteria; 17,680 had ≥1 prevention drug clinically indicated: 16,028 had lipid-lowering drugs indicated, 3,194 anticoagulant drugs, and 7,008 antihypertensive drugs. At least one prevention drug was not prescribed when clinically indicated in 54% (9,579/17,680) of stroke/TIA patients: 49% (7,836/16,028) were not prescribed lipid-lowering drugs, 52% (1,647/3,194) were not prescribed anticoagulant drugs, and 25% (1,740/7,008) were not prescribed antihypertensive drugs. The limitations of our study are that our definition of under-prescribing of drugs for stroke/TIA prevention did not address patients' adherence to medication or medication targets, such as blood pressure levels.In our study, over half of people eligible for lipid-lowering, anticoagulant, or antihypertensive drugs were not prescribed them prior to first stroke/TIA. We estimate that approximately 12,000 first strokes could potentially be prevented annually in the UK through optimal prescribing of these drugs. Improving prescription of lipid-lowering, anticoagulant, and antihypertensive drugs is important to reduce the incidence and burden of stroke and TIA.

Background There are many different potential strategies for identification of patients eligible for primary prevention of cardiovascular disease. The ability to use a more efficient strategy has a value. This paper models the costs and benefits of a number of identification strategies and estimates the additional value of an information-based strategy. Design Modelling study. Methods Ten-year Framingham cardiovascular risk was calculated for each individual in a population of 4471 persons aged 35_74 drawn from the Health Survey for England (equivalent to a total practice population of 12 000). Estimated Framingham risk was calculated using limited risk factor information and default risk factors. Costs of risk factor assessment were calculated using standard NHS costs. The outcomes of risk factor assessment were the total number of patients identified as eligible for treatment and the total burden of cardiovascular disease in eligible patients. Several strategies for prioritising patients for assessment were defined: opportunistic, diabetics and treated hypertensives first, ranked by estimated cardiovascular risk. The costs and outcomes of assessing increasing numbers of patients under each strategy were presented in graphical form. Results To identify 70% of the burden of cardiovascular disease in this population opportunistically costs '82 102; under a 'diabetics and hypertensives first' strategy it costs '72 916; under a strategy prioritising by estimated cardiovascular risk, '27 795. The value of information in this scenario is therefore at least '45 121. Conclusions Because strategies prioritising patients by estimated cardiovascular risk dominate alternative strategies, it is possible to estimate the value of information in terms of reduced resources to achieve the same results. These resource savings largely represent savings in staff time.

Estudo transversal de base populacional sobre altura de crianças de 12 a 59 meses (n = 2.632) foi realizado em Porto Alegre, Brasil. Usou-se regressão linear multinível para investigar o efeito de condições sócio-econômicas, demográficas, de saúde e dos ambientes físico e social sobre a altura, medida em escores-z do padrão de altura para idade do National Center for Health Statisrics. A área de localização do domicílio foi classificada como bem e mal provida em infra-estrutura habitacional. A altura foi, em média, -0,18 escore-z, estando positivamente associada a escolaridade e qualificação ocupacional dos pais, renda, qualidade de moradia, idade materna, intervalo interpartal e peso de nascimento, e negativamente relacionada a prematuridade, número de menores de cinco anos no domicílio e hospitalização nos dois primeiros anos de vida. O efeito da educação materna foi o dobro nas áreas mal providas em infra-estrutura habitacional. O efeito positivo da qualificação ocupacional dos pais foi evidente apenas nas áreas mal providas. Provavelmente, a área de residência modifica o efeito das condições sócio-econômicas sobre o crescimento. Programas habitacionais e de saneamento são potencialmente úteis para diminuir o efeito de condições sócio-econômicas desfavoráveis sobre o crescimento da criança.A cross-sectional household survey of height among children under five years of age (n = 2,632) was conducted in the city of Porto Alegre, Rio Grande do Sul State, Brazil. Multi-level linear regression was applied to investigate the effect of socioeconomic and demographic factors, physical and social environment, and health conditions on children’s height, measured by the height-for-age z-scores of the National Center for Health Statistics standards. Area of residence (census tract) was classified as good versus poor in terms of housing and sanitation standards. On average, children’s height was -0.18 z-score. Average height increased with maternal and paternal schooling, parents’ work skills, per capita family income, improved housing, maternal age, birth intervals, and birth weight. Height decreased with hospitalization in the first two years of life, number of under-five children in the household, and preterm birth. In the poor residential areas, the effect of maternal schooling was twice as great as in the better-off areas. The effect of parental work skills was only evident in the more deprived areas. Area of residence modified the effects of socioeconomic conditions on children’s growth. Housing and sanitation programs are potentially beneficial to offset the negative effect of social disadvantage on children’s growth.

Despite the proven efficacy of warfarin, its use in patients with Atrial Fibrillation (AF) is reportedly low. We investigated the underuse and overuse of warfarin in the management of AF in general practices in the United Kingdom (UK) against the National Institute of Clinical Excellence (NICE, UK) guidelines whilst seeking to identify subgroups of AF patients to inform efforts to optimise warfarin use.A retrospective database analysis to determine warfarin prescribing using tree models based on 50,361 patients with AF (classified as low, moderate and high risk of stroke using CHADS2) from 430 general practices in the UK.Over one-third (37.0%, 4573/12,351) of low risk AF patients were on warfarin, compared with 47.1% (8349/17,709) moderate risk AF patients and 54.9% (11,142/20,301) high risk AF patients. Clinical subgroups (n = 15 low risk subgroups, n = 15 medium risk subgroups, n = 22 high risk subgroups) were identified. Several factors not supported by current guidelines (age, BMI, dementia, gender) were associated with the use of warfarin. Gender and BMI were associated with warfarin use in low and medium risk AF patients but not in high risk AF patients.Whilst NICE guidelines suggest that all high risk AF patients should be on warfarin, half of those at moderate risk should be on warfarin and none of those at low risk should be on warfarin, we found evidence of over and under use of warfarin. Interventions to optimise warfarin therapy tailored to and targeting specific subgroups of AF patients identified by the tree models are required.

Guidelines indicate eligibility for lipid lowering drugs, but it is not known to what extent GPs' follow guidelines in routine clinical practice or whether additional clinical factors systematically influence their prescribing decisions.A retrospective cohort analysis was undertaken using electronic primary care records from 421 UK general practices. At baseline (May 2008) patients were aged 30 to 74 years, free from cardiovascular disease and not taking lipid lowering drugs. The outcome was prescription of a lipid lowering drug within the next two years. The proportions of eligible and ineligible patients prescribed lipid lowering drugs were reported and multivariable logistic regression models were used to investigate associations between age, sex, cardiovascular risk factors and prescribing.Of 365,718 patients with complete data, 13.8% (50,558) were prescribed lipid lowering drugs: 28.5% (21,101/74,137) of those eligible and 10.1% (29,457/291,581) of those ineligible. Only 41.7% (21,101/50,558) of those prescribed lipid lowering drugs were eligible. In multivariable analysis prescribing was most strongly associated with increasing age (OR for age ≥ 65 years 4.21; 95% CI 4.05-4.39); diabetes (OR 4.49; 95% CI 4.35-4.64); total cholesterol level ≥ 7 mmol/L (OR 2.20; 95% CI 2.12-2.29); and ≥ 4 blood pressure measurements in the past year (OR 4.24; 95% CI 4.06-4.42). The predictors were similar in eligible and ineligible patients.Most lipid lowering drugs for primary prevention are prescribed to ineligible patients. There is underuse of lipid lowering drugs in eligible patients.

Background and aimWe wished to establish the frequency of unexpected hypoglycemia observed in non diabetic patients outside the intensive care unit and to determine if they have a plausible clinical explanation.MethodsWe analysed data for 2010 from three distinct sources to identify non diabetic hypoglycaemic patients: bedside and laboratory blood glucose measurements; medication records for those treatments (high-strength glucose solution and glucagon) commonly given to reverse hypoglycemia; and diagnostic codes for hypoglycemia. We excluded from the denominator admissions of patients with a diagnosis of diabetes or prescribed diabetic medication. Case notes of patients identified were reviewed. We used capture-recapture methods to establish the likely frequency of hypoglycemia in non-diabetic in-patients outside intensive care unit at different cut-off points for hypoglycemia. We also recorded co-morbidities that might have given rise to hypoglycemia.ResultsAmong the 37,898 admissions, the triggers identified 71 hypoglycaemic episodes at a cut-off of 3.3 mmol/l. Estimated frequency at 3.3 mmol/l was 50(CI 33-93), at 3.0 mmol/l, 36(CI 24-64), at 2.7 mmol/l, 13(CI 11-19), at 2.5 mmol/l, 11(CI 9-15) and at 2.2 mmol/l, 8(CI 7-11) per 10,000 admissions. Admissions of patients aged above 65 years were approximately 50% more likely to have an episode of hypoglycemia. Most were associated with important co-morbidities.ConclusionSignificant non-diabetic hypoglycemia in hospital in-patients (at or below 2.7 mmol/l) outside critical care is rare. It is sufficiently rare for occurrences to merit case-note review and diagnostic blood tests, unless an obvious explanation is found.

Guidelines for the management of blood pressure (BP) in primary care generally suggest that decisions be made on the basis of specific threshold values (e.g. BP 140/90 mmHg); but this fails to adequately accommodate a common cause of variation--the play of chance.To determine the impact of chance variability in BP readings on the clinical decision making of general practitioners (GPs) regarding anti-hypertensive treatment and cardiovascular risk management.We used an internet based study design, where 109 GPs were assigned to manage one of eight case vignettes (guidelines would recommend treatment for only one of the eight) and presented with blood pressure readings that were randomly selected from an underlying population.Seventeen (15.6%, 17/109) GPs consulted the vignette for whom treatment was recommended, but only 7/17 (41.2%) GPs prescribed treatment, whereas 14/92 (15.2%) GPs prescribed medication to the other vignettes. When deciding to follow-up a vignette GPs were influenced by threshold values for systolic and diastolic BP, but not by the overall cardiovascular risk. If the first reading was a low BP (systolic 90 or systolic BP≥140). Similar factors predicted the decision to prescribe a drug, although the vignette's cardiovascular risk (>20%) was now statistically significant (p = 0.03).GP decision making, whilst generally consistent with guidelines, appears to be compromised by chance variation leading to under and over treatment. Interventions to adequately accommodate chance variability into clinical decision making are required.

Estudo transversal de base populacional sobre altura de crianças de 12 a 59 meses (n = 2.632) foi realizado em Porto Alegre, Brasil. Usou-se regressão linear multinível para investigar o efeito de condições sócio-econômicas, demográficas, de saúde e dos ambientes físico e social sobre a altura, medida em escores-z do padrão de altura para idade do National Center for Health Statisrics. A área de localização do domicílio foi classificada como bem e mal provida em infra-estrutura habitacional. A altura foi, em média, -0,18 escore-z, estando positivamente associada a escolaridade e qualificação ocupacional dos pais, renda, qualidade de moradia, idade materna, intervalo interpartal e peso de nascimento, e negativamente relacionada a prematuridade, número de menores de cinco anos no domicílio e hospitalização nos dois primeiros anos de vida. O efeito da educação materna foi o dobro nas áreas mal providas em infra-estrutura habitacional. O efeito positivo da qualificação ocupacional dos pais foi evidente apenas nas áreas mal providas. Provavelmente, a área de residência modifica o efeito das condições sócio-econômicas sobre o crescimento. Programas habitacionais e de saneamento são potencialmente úteis para diminuir o efeito de condições sócio-econômicas desfavoráveis sobre o crescimento da criança.