Consideration of factors associated with inequalities in interventions that support health-care professionals' interaction with patients to reduce inappropriate antimicrobial use: a systematic review.

BACKGROUND: Tackling the public health challenge of antimicrobial resistance (AMR) requires promotion of appropriate antimicrobial use by health-care professionals. The objective of this review was to identify interventions that facilitate appropriate antimicrobial behaviours when health-care professionals interact with patients and any considerations for factors associated with health inequalities. METHODS: For this systematic review, we searched electronic databases (MEDLINE, EMBASE, Web of Science and Google Scholar) from Jan 31, 2023, to Feb 8, 2023. We included search terms such as antimicrobial use/prescribing, health-care professionals, and AMR programmes. We included any relevant primary study published from year 2010 and in English. We conducted forward and backward citation searching from included studies on March 27, 2023. We extracted information on the interventions following the Template for Intervention Description and Replication (TIDieR) guideline and examined reports on how the interventions might impact on inequalities. We performed quality assessment using the Mixed Methods Appraisal Tool (MMAT). We conducted descriptive synthesis. The protocol is registered with PROSPERO (CRD42023395642). FINDINGS: After screening 4979 records, we included 59 studies. Most studies were randomised trials (n=25) and qualitative/mixed methods studies (n=16). Included studies covered 16 countries, particularly the UK (n=16) and the USA (n=13). Most studies (n=34) fulfilled at least 80% of the relevant quality criteria, but 12 studies fulfilled less than 50%. Many interventions were established strategies (eg, TARGET: Treat Antibiotics Responsibly, Guidance, Education and Tools). Patient interaction elements of the interventions often involved using education materials (eg, digital/paper leaflets, and videos) and point-of-care testing. While many studies (n=49) included participants from disadvantaged groups, only three examined how outcomes differ between groups. In those studies, antimicrobial prescription was not associated with age, sex, and level of learning disability. Some other studies reported issues with language barriers and potential digital exclusion, especially for older people. INTERPRETATION: We might have missed some relevant studies due to publication year and language restrictions. Notwithstanding, this review showed that the potential impact of factors associated with health inequalities are not routinely considered during the implementation and evaluation of interventions to improve health-care professionals' interaction with patients. Future work should routinely consider this to help mitigate potential inequalities. FUNDING: UK Health Security Agency.

How and to what extent did the Coventry City of Culture 'City Host' volunteer programme effect the volunteers' mental wellbeing? A qualitative study.

BACKGROUND: A team of volunteers, known as City Hosts, were recruited to support UK City of Culture 2021 awarded to Coventry. City Hosts held various roles facilitating cultural event delivery and promoting a positive experience for visitors. This study aimed to (i) understand how and to what extent the volunteering programme impacted volunteer subjective wellbeing, and (ii) explore the mechanisms of change and intermediate outcomes between volunteering and subjective wellbeing. METHODS: This qualitative study comprised inductive and deductive analysis of data collected through semi-structured interviews, conducted between December 2021-May 2022 with City Hosts. This was complimented with secondary qualitative analysis of free text responses within Monitoring and Evaluation data collected from City Hosts in surveys conducted in August and November 2021, and April 2022. RESULTS: Approximately 180 City Hosts responded to the free text questions in each survey and 27 completed interviews. Analysis of data collected from City Hosts suggested positive wellbeing impacts from volunteering and supported theorised pathways to improved wellbeing. Strengths of the City Host programme included (i) facilitating the full range of mechanisms of change that mediate improved volunteer wellbeing, particularly promoting social connections and developing a strong role and group identity and (ii) flexibility around what volunteers do, how much, and how often. CONCLUSIONS: This study offers lessons for others designing volunteering programmes who wish to promote wellbeing among associated volunteers. We also offer evidence that exposure to culture may be one mechanism by which volunteering can improve wellbeing.

Investigating informed choice in screening programmes: a mixed methods analysis.

BACKGROUND: Screening programmes aim to identify individuals at higher risk of developing a disease or condition. While globally, there is agreement that people who attend screening should be fully informed, there is no consensus about how this should be achieved. We conducted a mixed methods study across eight different countries to understand how countries address informed choice across two screening programmes: breast cancer and fetal trisomy anomaly screening. METHODS: Fourteen senior level employees from organisations who produce and deliver decision aids to assist informed choice were interviewed, and their decision aids (n = 15) were evaluated using documentary analysis. RESULTS: We discovered that attempts to achieve informed choice via decision aids generate two key tensions (i) between improving informed choice and increasing uptake and (ii) between improving informed choice and comprehensibility of the information presented. Comprehensibility is fundamentally at tension with an aim of being fully informed. These tensions emerged in both the interviews and documentary analysis. CONCLUSION: We conclude that organisations need to decide whether their overarching aim is ensuring high levels of uptake or maximising informed choice to participate in screening programmes. Consideration must then be given to all levels of development and distribution of information produced to reflect each organisation's aim. The comprehensibility of the DA must also be considered, as this may be reduced when informed choice is prioritised.

Artificial intelligence software for analysing chest X-ray images to identify suspected lung cancer: an evidence synthesis early value assessment.

Background: Lung cancer is one of the most common types of cancer in the United Kingdom. It is often diagnosed late. The 5-year survival rate for lung cancer is below 10%. Early diagnosis may improve survival. Software that has an artificial intelligence-developed algorithm might be useful in assisting with the identification of suspected lung cancer. Objectives: This review sought to identify evidence on adjunct artificial intelligence software for analysing chest X-rays for suspected lung cancer, and to develop a conceptual cost-effectiveness model to inform discussion of what would be required to develop a fully executable cost-effectiveness model for future economic evaluation. Data sources: The data sources were MEDLINE All, EMBASE, Cochrane Database of Systematic Reviews, Cochrane CENTRAL, Epistemonikos, ACM Digital Library, World Health Organization International Clinical Trials Registry Platform, clinical experts, Tufts Cost-Effectiveness Analysis Registry, company submissions and clinical experts. Searches were conducted from 25 November 2022 to 18 January 2023. Methods: Rapid evidence synthesis methods were employed. Data from companies were scrutinised. The eligibility criteria were (1) primary care populations referred for chest X-ray due to symptoms suggestive of lung cancer or reasons unrelated to lung cancer; (2) study designs that compared radiology specialist assessing chest X-ray with adjunct artificial intelligence software versus radiology specialists alone and (3) outcomes relating to test accuracy, practical implications of using artificial intelligence software and patient-related outcomes. A conceptual decision-analytic model was developed to inform a potential full cost-effectiveness evaluation of adjunct artificial intelligence software for analysing chest X-ray images to identify suspected lung cancer. Results: None of the studies identified in the searches or submitted by the companies met the inclusion criteria of the review. Contextual information from six studies that did not meet the inclusion criteria provided some evidence that sensitivity for lung cancer detection (but not nodule detection) might be higher when chest X-rays are interpreted by radiology specialists in combination with artificial intelligence software than when they are interpreted by radiology specialists alone. No significant differences were observed for specificity, positive predictive value or number of cancers detected. None of the six studies provided evidence on the clinical effectiveness of adjunct artificial intelligence software. The conceptual model highlighted a paucity of input data along the course of the diagnostic pathway and identified key assumptions required for evidence linkage. Limitations: This review employed rapid evidence synthesis methods. This included only one reviewer conducting all elements of the review, and targeted searches that were conducted in English only. No eligible studies were identified. Conclusions: There is currently no evidence applicable to this review on the use of adjunct artificial intelligence software for the detection of suspected lung cancer on chest X-ray in either people referred from primary care with symptoms of lung cancer or people referred from primary care for other reasons. Future work: Future research is required to understand the accuracy of adjunct artificial intelligence software to detect lung nodules and cancers, as well as its impact on clinical decision-making and patient outcomes. Research generating key input parameters for the conceptual model will enable refinement of the model structure, and conversion to a full working model, to analyse the cost-effectiveness of artificial intelligence software for this indication. Study registration: This study is registered as PROSPERO CRD42023384164. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135755) and is published in full in Health Technology Assessment; Vol. 28, No. 50. See the NIHR Funding and Awards website for further award information.

Lung cancer is one of the most common types of cancer in the United Kingdom. Early diagnosis may improve survival, as lung cancer is often diagnosed late. Chest X-rays can be used to identify features of lung cancer. There can be delays in getting X-rays, and sometimes features of lung cancer are not seen on them. Artificial intelligence software may help by finding features of cancer on chest X-rays and highlighting them. A radiologist will look at the X-rays and information from the software. There is a lack of information about how lung cancer diagnosis could change if artificial intelligence software is used and what the costs may be to the National Health Service. This project looked at the use of artificial intelligence software in the detection of lung cancer in people referred from primary care. Software companies were invited to provide evidence. There were no studies that looked at this topic among people from primary care. We summarised the closest evidence we could find instead. All of this had flaws, so we could not tell if the results were accurate or helpful to this review. It was not clear if artificial intelligence helped to find cancers or improve people's health. We made a theoretical model to discuss the best way to assess if artificial intelligence software might be cost-effective in detecting lung cancer and what evidence would be needed to do this in a fully working model. Costs and alternative pricing models provided by five companies were used to calculate the cost of adding artificial intelligence software to review chest X-rays in people referred from their general practitioner, for the first 5 years, based on one National Health Service trust. Future studies are needed to identify the impact of adjunct artificial intelligence on test accuracy, clinical decision-making and patient outcomes (e.g. mortality and morbidity).

What is the best way to evaluate social prescribing? A qualitative feasibility assessment for a national impact evaluation study in England.

OBJECTIVES: Despite significant investment in social prescribing in England over the last decade, we still do not know if it works, or how models of social prescribing fit within wider health and care policy and practice. This study explores current service delivery structures and assesses the feasibility of a national evaluation of the link worker model. METHODS: Semi-structured interviews were conducted between May and September 2020, with 25 key informants from across social prescribing services in England. Participants included link workers, voluntary, community and social enterprise staff, and those involved in policy and decision-making for social prescribing services. Interview and workshop transcripts were analysed thematically, adopting a framework approach. RESULTS: We found differences in how services are provided, including by individual link workers, and between organisations and regions. Standards, referral pathways, reporting, and monitoring structures differ or are lacking in voluntary services as compared to clinical services. People can self-refer to a link worker or be referred by a third party, but the lack of standardised processes generated confusion in both public and professional perceptions of the link worker model. We identified challenges in determining the appropriate outcomes and outcome measures needed to assess the impact of the link worker model. CONCLUSIONS: The current varied service delivery structures in England poses major challenges for a national impact evaluation. Any future rigorous evaluation needs to be underpinned with national standardised outcomes and process measures which promote uniform data collection.

Improving healthcare professionals' interactions with patients to tackle antimicrobial resistance: a systematic review of interventions, barriers, and facilitators.

Introduction: Antimicrobial resistance (AMR) is a major public health threat. With the growing emphasis on patient-centred care/ shared decision making, it is important for healthcare professionals' (HCPs) who prescribe, dispense, administer and/or monitor antimicrobials to be adequately equipped to facilitate appropriate antimicrobial use. We systematically identified existing interventions which aim to improve HCPs interaction with patients and examined barriers and facilitators of appropriate the use of such interventions and appropriate antimicrobial use among both HCPs and patientsantimicrobial use while using these interventions. Methods: We searched MEDLINE, EMBASE, Web of Science, Google Scholar, and internet (via Google search engine). We included primary studies, published in English from 2010 to 2023 [PROSPERO (CRD42023395642)]. The protocol was preregistered with PROSPERO (CRD42023395642). We performed quality assessment using mixed methods appraisal tool. We applied narrative synthesis and used the COM-B (Capability, Opportunity, Motivation -Behaviour) as a theoretical framework for barriers and facilitators at HCP and patient levels. Results: Of 9,172 citations retrieved from database searches, From 4,979 citations remained after removal of duplicates. We included 59 studies spanning over 13 countries. Interventions often involved multiple components beyond HCPs' interaction with patients. From 24 studies reporting barriers and facilitators, we identified issues relating to capability (such as, knowledge/understanding about AMR, diagnostic uncertainties, awareness of interventions and forgetfulness); opportunity (such as, time constraint and intervention accessibility) and motivation (such as, patient's desire for antibiotics and fear of litigation). Conclusion: The findings of this review should be considered by intervention designers/adopters and policy makers to improve utilisation and effectiveness.

Health inequalities in infectious diseases: a systematic overview of reviews.

OBJECTIVES: The aim of this systematic overview of reviews was to synthesise available evidence on inequalities in infectious disease based on three dimensions of inequalities; inclusion health groups, protected characteristics and socioeconomic inequalities. METHODS: We searched MEDLINE, Embase, Web of Science and OpenGrey databases in November 2021. We included reviews published from the year 2000 which examined inequalities in the incidence, prevalence or consequences of infectious diseases based on the dimensions of interest. Our search focused on tuberculosis, HIV, sexually transmitted infections, hepatitis C, vaccination and antimicrobial resistance. However, we also included eligible reviews of any other infectious diseases. We appraised the quality of reviews using the Assessment of Multiple Systematic Reviews V.2 (AMSTAR2) checklist. We conducted a narrative data synthesis. RESULTS: We included 108 reviews in our synthesis covering all the dimensions of inequalities for most of the infectious disease topics of interest, however the quality and volume of review evidence and consistency of their findings varied. The existing literature reviews provide strong evidence that people in inclusion health groups and lower socioeconomic status are consistently at higher risk of infectious diseases, antimicrobial resistance and incomplete/delayed vaccination. In the protected characteristics dimension, ethnicity, and sexual orientation are important factors contributing to inequalities across the various infectious disease topics included in this overview of reviews. CONCLUSION: We identified many reviews that provide evidence of various types of health inequalities in different infectious diseases, vaccination, and antimicrobial resistance. We also highlight areas where reviews may be lacking. The commonalities in the associations and their directions suggest it might be worth targeting interventions for some high risk-groups that may have benefits across multiple infectious disease outcomes rather than operating purely in infectious disease siloes.

Evaluation of an organisational-level monetary incentive to promote the health and wellbeing of workers in small and medium-sized enterprises: A mixed-methods cluster randomised controlled trial.

We conducted an independent evaluation on the effectiveness of an organisational-level monetary incentive to encourage small and medium-sized enterprises (SMEs) to improve employees' health and wellbeing. This was A mixed-methods cluster randomised trial with four arms: high monetary incentive, low monetary incentive, and two no monetary incentive controls (with or without baseline measurements to examine 'reactivity' The consequence of particpant awareness of being studied, and potential impact on participant behavior effects). SMEs with 10-250 staff based in West Midlands, England were eligible. We randomly selected up to 15 employees at baseline and 11 months post-intervention. We elicited employee perceptions of employers' actions to improve health and wellbeing; and employees' self-reported health behaviours and wellbeing. We also interviewed employers and obtained qualitative data. One hundred and fifty-two SMEs were recruited. Baseline assessments were conducted in 85 SMEs in three arms, and endline assessments in 100 SMEs across all four arms. The percentage of employees perceiving "positive action" by their employer increased after intervention (5 percentage points, pp [95% Credible Interval -3, 21] and 3pp [-9, 17], in models for high and low incentive groups). Across six secondary questions about specific issues the results were strongly and consistently positive, especially for the high incentive. This was consistent with qualitative data and quantitative employer interviews. However, there was no evidence of any impact on employee health behaviour or wellbeing outcomes, nor evidence of 'reactivity'. An organisational intervention (a monetary incentive) changed employee perceptions of employer behaviour but did not translate into changes in employees' self-reports of their own health behaviours or wellbeing. Trial registration: AEARCTR-0003420, registration date: 17.10.2018, retrospectively registered (delays in contracts and identfying a suitable trial registry). The authors confirm that there are no ongoing and related trials for this intervention.

The influence of the urban food environment on diet, nutrition and health outcomes in low-income and middle-income countries: a systematic review.

INTRODUCTION: Diet and nutrition are leading causes of global morbidity and mortality. Our study aimed to identify and synthesise evidence on the association between food environment characteristics and diet, nutrition and health outcomes in low-income and middle-income countries (LMICs), relevant to urban settings, to support development and implementation of appropriate interventions. METHODS: We conducted a comprehensive search of 9 databases from 1 January 2000 to 16 September 2020 with no language restrictions. We included original peer-reviewed observational studies, intervention studies or natural experiments conducted in at least one urban LMIC setting and reporting a quantitative association between a characteristic of the food environment and a diet, nutrition or health outcome. Study selection was done independently in duplicate. Data extraction and quality appraisal using the National Heart Lung and Blood Institute checklists were completed based on published reports using a prepiloted form on Covidence. Data were synthesised narratively. RESULTS: 74 studies met eligibility criteria. Consistent evidence reported an association between availability characteristics in the neighbourhood food environment and dietary behaviour (14 studies, 10 rated as good quality), while the balance of evidence suggested an association with health or nutrition outcomes (17 of 24 relevant studies). We also found a balance of evidence that accessibility to food in the neighbourhood environment was associated with diet (10 of 11 studies) although evidence of an association with health outcomes was contradictory. Evidence on other neighbourhood food environment characteristics was sparse and mixed. Availability in the school food environment was also found to be associated with relevant outcomes. Studies investigating our other primary outcomes in observational studies of the school food environment were sparse, but most interventional studies were situated in schools. We found very little evidence on how workplace and home food environments are associated with relevant outcomes. This is a substantial evidence gap. CONCLUSION: 'Zoning' or 'healthy food cart' interventions to alter food availability may be appropriate in urban LMIC. PROSPERO REGISTRATION NUMBER: CRD42020207475.