A service mapping exercise of four health and social care staff mental health and wellbeing services, Resilience Hubs, to describe health service provision and interventions.

BACKGROUND: NHS England funded 40 Mental Health and Wellbeing Hubs to support health and social care staff affected by the COVID-19 pandemic. We aimed to document variations in how national guidance was adapted to the local contexts of four Hubs in the North of England. METHODS: We used a modified version of Price's (2019) service mapping methodology. Service level data were used to inform the analysis. A mapping template was adapted from a range of tools, including the European Service Mapping Schedule, and reviewed by Hub leads. Key data included service model; staffing; and interventions. Data were collected between March 2021 - March 2022 by site research assistants. Findings were accuracy-checked by Hub leads, and a logic model developed to theorise how the Hubs may effect change. RESULTS: Hub goals and service models closely reflected guidance; offering: proactive outreach; team-based support; clinical assessment; onward referral, and rapid access to mental health support (in-house and external). Implementation reflected a service context of a client group with high mental health need, and high waiting times at external mental health services. Hubs were predominantly staffed by experienced clinicians, to manage these mental health presentations and organisational working. Formulation-based psychological assessment and the provision of direct therapy were not core functions of the NHS England model, however all Hubs incorporated these adaptations into their service models in response to local contexts, such as extensive waiting lists within external services, and/or client presentations falling between gaps in existing service provision. Finally, a standalone clinical records system was seen as important to reassure Hub users of confidentiality. Other more nuanced variation depended on localised contexts. CONCLUSION: This study provides a map for setting up services, emphasising early understandings of how new services will integrate within existing systems. Local and regional contexts led to variation in service configuration. Whilst additional Hub functions are supported by available literature, further research is needed to determine whether these functions should comprise essential components of staff wellbeing services moving forward. Future research should also determine the comparative effectiveness of service components, and the limits of permissible variation. STUDY REGISTRATION: researchregistry6303.

Responsiveness to change in health status of the EQ-5D in patients treated for depression and anxiety.

BACKGROUND: The EQ-5D is a commonly used generic measure of health but evidence on its responsiveness to change in mental health is limited. This study aimed to explore the responsiveness of the five-level version of the instrument, the EQ-5D-5 L, in patients receiving treatment for depression and anxiety. METHODS: Patient data (N = 416) were collected at baseline and at end of treatment in an observational study in a Norwegian outpatient clinic. Patients were adults of working age (18-69 years) and received protocol-based metacognitive or cognitive therapy for depression or anxiety according to diagnosis. Responsiveness in the EQ-5D was compared to change in the Beck Depression Inventory-II (BDI-II) and the Beck Anxiety Inventory (BAI). Effect sizes (Cohen's d), Standardised response mean (SRM), and Pearson's correlation were calculated. Patients were classified as "Recovered", "Improved", or "Unchanged" during treatment using the BDI-II and the BAI. ROC analyses determined whether the EQ-5D could correctly classify patient outcomes. RESULTS: Effect sizes were large for the BAI, the BDI-II, the EQ-5D value and the EQ VAS, ranging from d = 1.07 to d = 1.84. SRM were also large (0.93-1.67). Pearson's correlation showed strong agreement between change scores of the EQ-5D value and the BDI-II (rs -0.54) and moderate between the EQ-5D value and the BAI (rs -0.43). The EQ-5D consistently identified "Recovered" patients versus "Improved" or "Unchanged" in the ROC analyses with AUROC ranging from 0.72 to 0.84. CONCLUSION: The EQ-5D showed good agreement with self-reported symptom change in depression and anxiety, and correctly identified recovered patients. These findings indicate that the EQ-5D may be appropriately responsive to change in patients with depression and anxiety disorders, although replication in other clinical samples is needed.

The EQ-5D is a questionnaire that people fill in to report their subjective health. It is often used in clinics or hospitals to better understand how patients are affected by their illnesses, and if their health improves after treatment. For this information to be trustworthy, we need to verify how accurately the EQ-5D measures health for the particular patients we want to use it with. This is often done by comparing EQ-5D scores with scores from other questionnaires. For example, if we want to use the EQ-5D with a group of patients with depression, we compare the scores of the EQ-5D with scores from questionnaires that are commonly used to measure depression symptoms.In this study, we compared the scores of the EQ-5D with scores from questionnaires measuring symptoms of depression and anxiety. Their performances were similar, and the EQ-5D scores could also correctly identify which patients had recovered during treatment. This implies that the EQ-5D can be a useful tool for understanding the impact of depression and anxiety and can help in decision-making regarding these patients.

An economic evaluation of universal and targeted case-finding strategies for identifying antenatal depression: a model-based analysis comparing common case-finding instruments.

Half of women with depression in the perinatal period are not identified in routine care, and missed cases reflect inequalities in other areas of maternity care. Case finding (screening) for depression in pregnant women may be a cost-effective strategy to improve identification, and targeted case finding directs finite resources towards the greatest need. We compared the cost-effectiveness of three case-finding strategies: no case finding, universal (all pregnant women), and targeted (only pregnant women with risk factors for antenatal depression, i.e. history of anxiety/depression, age < 20 years, and adverse life events). A decision tree model was developed to represent case finding (at around 20 weeks gestation) and subsequent treatment for antenatal depression (up to 40 weeks gestation). Costs include case finding and treatment. Health benefits are measured as quality-adjusted life years (QALYs). The sensitivity and specificity of case-finding instruments and prevalence and severity of antenatal depression were estimated from a cohort study of pregnant women. Other model parameters were derived from published literature and expert consultation. The most cost-effective case-finding strategy was a two-stage strategy comprising the Whooley questions followed by the PHQ-9. The mean costs were £52 (universal), £61 (no case finding), and £62 (targeted case finding). Both case-finding strategies improve health compared with no case finding. Universal case finding is cost-saving. Costs associated with targeted case finding are similar to no case finding, with greater health gains, although targeted case finding is not cost-effective compared with universal case finding. Universal case finding for antenatal depression is cost-saving compared to no case finding and more cost-effective than targeted case finding.

A framework for implementing Patient and Public Involvement in mental health research: The PATHWAY research programme benchmarked against NIHR standards.

BACKGROUND: Patient and Public Involvement (PPI) in research has become a key component recommended by research commissioners, grant award bodies and specified in government policies. Despite the increased call for PPI, few studies have demonstrated how to implement PPI within large-scale research studies. OBJECTIVE: The aim of the current study was to provide a case example of the implementation of a patient advisory group in a large-scale mental health research programme (PATHWAY) and to benchmark this against UK standards. METHOD: A PPI group was incorporated throughout the PATHWAY research programme, from grant development to dissemination. The group attended regular meetings and supported participant recruitment, evaluated patient-facing documents, supported the piloting of the research intervention and co-developed the dissemination and impact strategy. The implementation of PPI throughout the project was benchmarked against the UK standards for PPI. RESULTS: The inclusion of PPI in the PATHWAY project provided tangible changes to the research project (i.e., improving study documents, co-developing dissemination materials) but also proved to be a beneficial experience to PPI members through the development of new skills and the opportunity to provide a patient voice in research. We show how PPI was involved across seven study phases and provide examples of implementation of the six UK standards. The study did not include PPI in data analysis but met all the UK standards for PPI. Challenges regarding practical components (i.e., meeting frequency, language use), increasing diversity and PPI members' knowledge of research were highlighted as areas for further improvement. CONCLUSIONS: We provide a case example of how PPI can be implemented throughout a research lifecycle and we note the barriers faced and make suggestions for PPI in future implementation and research. PATIENT AND PUBLIC CONTRIBUTION: PPI members were involved throughout the lifecycle of the research programme. The PPI lead was a co-author on the manuscript and contributed to report writing.

Acknowledging Patient Heterogeneity in Economic Evaluations in Schizophrenia: A Systematic Review.

OBJECTIVES: Schizophrenia is a severe mental illness with heterogeneous etiology, range of symptoms, and course of illness. Cost-effectiveness analysis often applies averages from populations, which disregards patient heterogeneity even though there are a range of methods available to acknowledge patient heterogeneity. This review evaluates existing economic evaluations of interventions in schizophrenia to understand how patient heterogeneity is currently reflected in economic evaluation. METHODS: Electronic searches of MEDLINE, Embase, and PsycINFO via Ovid and the Health Technology Assessment database were run to identify full economic evaluations of interventions aiming to reduce the symptoms associated with schizophrenia. Two levels of screening were used, and explicit inclusion criteria were applied. Prespecified data extraction and critical appraisal were performed. RESULTS: Seventy-six relevant studies were identified. More than half (41 of 76) of the articles acknowledged patient heterogeneity in some way through discussion or methods. There was a range of patient characteristics considered, including demographics and socioeconomic factors (eg, age, educational level, ethnicity), clinical characteristics (eg, symptom severity, comorbidities), and preferences (eg, preferences related to outcomes or symptoms). Subgroup analyses were rarely reported (8 of 76). CONCLUSIONS: Patient heterogeneity was frequently mentioned in studies but was rarely thoroughly investigated in the identified economic evaluations. When investigated, included patient characteristics and methods were found to be heterogeneous. Understanding and acknowledging patient heterogeneity may alter the conclusions of cost-effectiveness evaluations; subsequently, we would encourage further research in this area.

A review of economic evaluations of health care for people at risk of psychosis and for first-episode psychosis.

BACKGROUND: Preventing psychotic disorders and effective treatment in first-episode psychosis are key priorities for the National Institute for Health and Care Excellence. This review assessed the evidence base for the cost-effectiveness of health and social care interventions for people at risk of psychosis and for first-episode psychosis. METHODS: Electronic searches were conducted using the PsycINFO, MEDLINE and Embase databases to identify relevant published full economic evaluations published before August 2020. Full-text English-language studies reporting a full economic evaluation of a health or social care intervention aiming to reduce or prevent symptoms in people at risk of psychosis or experiencing first-episode psychosis were included. Screening, data extraction, and critical appraisal were performed using pre-specified criteria and forms based on the NHS Economic Evaluation Database (EED) handbook and Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist for economic evaluations. The protocol was registered on the PROSPERO database (CRD42018108226). Results were summarised qualitatively. RESULTS: Searching identified 1,628 citations (1,326 following the removal of duplications). After two stages of screening 14 studies met the inclusion criteria and were included in the review. Interventions were varied and included multidisciplinary care, antipsychotic medication, psychological therapy, and assertive outreach. Evidence was limited in the at-risk group with only four identified studies, though all interventions were found to be cost-effective with a high probability (> 80%). A more substantial evidence base was identified for first-episode psychosis (11 studies), with a focus on early intervention (7/11 studies) which again had positive conclusions though with greater uncertainty. CONCLUSIONS: Study findings generally concluded interventions were cost-effective. The evidence for the population who are at-risk of psychosis was limited, and though there were more studies for the population with first-episode psychosis, limitations of the evidence base (including generalisability and heterogeneity across the methods used) affect the certainty of conclusions.

Development of a cost of illness inventory questionnaire for children with autism spectrum disorder in South Asia.

BACKGROUND: The economic burden of autism is substantial and includes a range of costs, including healthcare, education, productivity losses, informal care and respite care, among others. In India, approximately, 2 million children aged 2-9 years have autism. Given the likely substantial burden of illness and the need to identify effective and cost-effective interventions, this research aimed to produce a comprehensive cost of illness inventory (COII) suitable for children with autism in South Asia (India) to support future research. METHODS: A structured and iterative design process was followed to create the COII, including literature reviews, interviews with caregivers, pilot testing and translation. Across the development of the COII, thirty-two families were involved in the design and piloting of the tool. The COII was forward translated (from English to Hindi) and back translated. Each stage of the process of development of the COII resulted in the further refinement of the tool. RESULTS: Domains covered in the final COII include education, childcare, relocation, healthcare contacts (outpatient, inpatient, medical emergencies, investigations and medication), religious retreats and rituals, specialist equipment, workshops and training, special diet, support and care, certification, occupational adjustments and government rebates/schemes. Administration and completion of the COII determined it to be feasible to complete in 35 minutes by qualified and trained researchers. The final COII is hosted by REDCap Cloud and is a bilingual instrument (Hindi and English). CONCLUSIONS: The COII was developed using experiences gathered from an iterative process in a metropolitan area within the context of one low- and middle-income country (LMIC) setting, India. Compared to COII tools used for children with autism in high-income country settings, additional domains were required, such as complimentary medication (e.g. religious retreats and homeopathy). The COII will allow future research to quantify the cost of illness of autism in India from a broad perspective and will support relevant economic evaluations. Understanding the process of developing the questionnaire will help researchers working in LMICs needing to adapt the current COII or developing similar questionnaires.

Real-world evidence use in assessments of cancer drugs by NICE.

OBJECTIVE: To establish how real-world evidence (RWE) has been used to inform single technology appraisals (STAs) of cancer drugs conducted by the National Institute for Health and Care Excellence (NICE). METHODS: STAs published by NICE from April 2011 to October 2018 that evaluated cancer treatments were reviewed. Information regarding the use of RWE to directly inform the company-submitted cost-effectiveness analysis was extracted and categorized by topic. Summary statistics were used to describe emergent themes, and a narrative summary was provided for key case studies. RESULTS: Materials for a total of 113 relevant STAs were identified and analyzed, of which nearly all (96 percent) included some form of RWE within the company-submitted cost-effectiveness analysis. The most common categories of RWE use concerned the health-related quality of life of patients (71 percent), costs (46 percent), and medical resource utilization (40 percent). While sources of RWE were routinely criticized as part of the appraisal process, we identified only two cases where the use of RWE was overtly rejected; hence, in the majority of cases, RWE was accepted in cancer drug submissions to NICE. DISCUSSION: RWE has been used extensively in cancer submissions to NICE. Key criticisms of RWE in submissions to NICE are seldom regarding the use of RWE in general; instead, these are typically concerned with specific data sources and the applicability of these to the decision problem. Within an appropriate context, RWE constitutes an extremely valuable source of information to inform decision making; yet the development of best practice guidelines may improve current reporting standards.

Cost-Effectiveness Evaluations of Psychological Therapies for Schizophrenia and Bipolar Disorder: A Systematic Review.

OBJECTIVES: This review aims to assess the cost-effectiveness of psychological interventions for schizophrenia/bipolar disorder (BD), to determine the robustness of current evidence and identify gaps in the available evidence. METHODS: Electronic searches (PsycINFO, MEDLINE, Embase) identified economic evaluations relating incremental cost to outcomes in the form of an incremental cost-effectiveness ratio published in English since 2000. Searches were concluded in November 2018. Inclusion criteria were: adults with schizophrenia/BD; any psychological/psychosocial intervention (e.g., psychological therapy and integrated/collaborative care); probability of cost-effectiveness at explicitly defined thresholds reported. Comparators could be routine practice, no intervention, or alternative psychological therapies. Screening, data extraction, and critical appraisal were performed using pre-specified criteria and forms. Results were summarized qualitatively. The protocol was registered on the PROSPERO database (CRD42017056579). RESULTS: Of 3,864 studies identified, 12 met the criteria for data extraction. All were integrated clinical and economic randomized controlled trials. The most common intervention was cognitive behavioral therapy (CBT, 6/12 studies). The most common measure of health benefit was the quality-adjusted life-year (6/12). Follow-up ranged from 6 months to 5 years. Interventions were found to be cost-effective in most studies (9/12): the probability of cost-effectiveness ranged from 35-99.5 percent. All studies had limitations and demonstrated uncertainty (particularly related to incremental costs). CONCLUSIONS: Most studies concluded psychological interventions for schizophrenia/BD are cost-effective, including CBT, although there was notable uncertainty. Heterogeneity across studies makes it difficult to reach strong conclusions. There is a particular need for more evidence in the population with BD and for longer-term evidence across both populations.

Making Use of Technology to Improve Stated Preference Studies.

The interest in quantifying stated preferences for health and healthcare continues to grow, as does the technology available to support and improve health preference studies. Technological advancements in the last two decades have implications and opportunities for preference researchers designing, administering, analysing, interpreting and applying the results of stated preference surveys. In this paper, we summarise selected technologies and how these can benefit a preference study. We discuss empirical evaluations of the technology in preference research, with examples from health where possible. The technologies reviewed include serious games, virtual reality, eye tracking, innovative formats and decision aids with values clarification components. We conclude with a critical reflection on the benefits and limitations of implementing (often costly) technology alongside stated preference studies.

Health outcomes in Deaf signing populations: A systematic review.

OBJECTIVES: (i) To identify peer reviewed publications reporting the mental and/or physical health outcomes of Deaf adults who are sign language users and to synthesise evidence; (ii) If data available, to analyse how the health of the adult Deaf population compares to that of the general population; (iii) to evaluate the quality of evidence in the identified publications; (iv) to identify limitations of the current evidence base and suggest directions for future research. DESIGN: Systematic review. DATA SOURCES: Medline, Embase, PsychINFO, and Web of Science. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: The inclusion criteria were Deaf adult populations who used a signed language, all study types, including methods-focused papers which also contain results in relation to health outcomes of Deaf signing populations. Full-text articles, published in peer-review journals were searched up to 13th June 2023, published in English or a signed language such as ASL (American Sign Language). DATA EXTRACTION: Supported by the Rayyan systematic review software, two authors independently reviewed identified publications at each screening stage (primary and secondary). A third reviewer was consulted to settle any disagreements. Comprehensive data extraction included research design, study sample, methodology, findings, and a quality assessment. RESULTS: Of the 35 included studies, the majority (25 out of 35) concerned mental health outcomes. The findings from this review highlighted the inequalities in health and mental health outcomes for Deaf signing populations in comparison with the general population, gaps in the range of conditions studied in relation to Deaf people, and the poor quality of available data. CONCLUSIONS: Population sample definition and consistency of standards of reporting of health outcomes for Deaf people who use sign language should be improved. Further research on health outcomes not previously reported is needed to gain better understanding of Deaf people's state of health.

The cost-effectiveness of mental health interventions amongst prison populations: a systematic review (research letter to the editor).

The link between imprisonment and adverse mental health is well established and linked to both recidivism and prison misconduct, with negative consequences for prisoners, the prison system and society. To help minimise these impacts, appropriate mental health interventions are required. However, owing to finite resources to deliver healthcare in prisons, interventions must be both clinically and cost-effective. A systematic literature search was conducted using various medical and economic databases. The search aimed to identify full economic evaluations (comparing costs and consequences of two or more interventions) of mental health interventions for adult prisoners during incarceration. Results were intended to identify evidence gaps and highlight areas for future research. Only one publication met all eligibility requirements, with several limitations identified. This finding highlighted a clear lack of cost-effectiveness evidence for use by decision makers within the prison setting. This emphasises the need for future research to incorporate economic evaluation during the early stages of research design. Research should aim to incorporate both intervention costs and wider healthcare resource use, which may be affected, and generic outcomes, such as quality-adjusted life years (QALYs), which enable comparison across various disease areas and against pre-determined thresholds.

Generating EQ-5D-3L health utility scores from the Edinburgh Postnatal Depression Scale: a perinatal mapping study.

BACKGROUND: Perinatal depression (PND) describes depression experienced by parents during pregnancy or in the first year after a baby is born. The EQ-5D instrument (a generic measure of health status) is not often collected in perinatal research, however disease-specific measures, such as the Edinburgh Postnatal Depression Scale (EPDS) are widely used. Mapping can be used to estimate generic health utility index values from disease-specific measures like the EPDS. OBJECTIVE: To develop a mapping algorithm to estimate EQ-5D utility index values from the EPDS. METHODS: Patient-level data from the BaBY PaNDA study (English observational cohort study) provided 1068 observations with paired EPDS and EQ-5D (3-level version; EQ-5D-3L) responses. We compared the performance of six alternative regression model types, each with four specifications of covariates (EPDS score and age: base, squared, and cubed). Model performance (ability to predict utility values) was assessed by ranking mean error, mean absolute error, and root mean square error. Algorithm performance in 3 external datasets was also evaluated. RESULTS: There was moderate correlation between EPDS score and utility values (coefficient: - 0.42). The best performing model type was a two-part model, followed by ordinary least squared. Inclusion of squared and cubed covariates improved model performance. Based on graphs of observed and predicted utility values, the algorithm performed better when utility was above 0.6. CONCLUSIONS: This direct mapping algorithm allows the estimation of health utility values from EPDS scores. The algorithm has good external validity but is likely to perform better in samples with higher health status.

Advances in Addressing Patient Heterogeneity in Economic Evaluation: A Review of the Methods Literature.

Cost-effectiveness analyses commonly use population or sample averages, which can mask key differences across subgroups and may lead to suboptimal resource allocation. Despite there being several new methods developed over the last decade, there is no recent summary of what methods are available to researchers. This review sought to identify advances in methods for addressing patient heterogeneity in economic evaluations and to provide an overview of these methods. A literature search was conducted using the Econlit, Embase and MEDLINE databases to identify studies published after 2011 (date of a previous review on this topic). Eligible studies needed to have an explicit methodological focus, related to how patient heterogeneity can be accounted for within a full economic evaluation. Sixteen studies were included in the review. Methodologies were varied and included regression techniques, model design and value of information analysis. Recent publications have applied methodologies more commonly used in other fields, such as machine learning and causal forests. Commonly noted challenges associated with considering patient heterogeneity included data availability (e.g., sample size), statistical issues (e.g., risk of false positives) and practical factors (e.g., computation time). A range of methods are available to address patient heterogeneity in economic evaluation, with relevant methods differing according to research question, scope of the economic evaluation and data availability. Researchers need to be aware of the challenges associated with addressing patient heterogeneity (e.g., data availability) to ensure findings are meaningful and robust. Future research is needed to assess whether and how methods are being applied in practice.

Motiv8: a study protocol for a cluster-randomised feasibility trial of a weight management intervention for adults with severe mental illness in secure forensic services.

INTRODUCTION: People with severe mental illness have physical comorbidities which result in significant reductions in quality of life and premature mortality. Effective interventions are required that are suitable for people in secure forensic mental health services. We conducted pilot work of a multidisciplinary weight management intervention (Motiv8) which showed improvements in physical and mental health and high levels of satisfaction. We aim to test the feasibility of Motiv8 under cluster randomised conditions, with an aim to investigate the acceptability, feasibility and potential effectiveness of this intervention to supplement standard secure care. METHODS AND ANALYSIS: A randomised waitlist-controlled feasibility trial of a lifestyle intervention (Motiv8) + TAU compared with TAU (+ Motiv8 waitlist) for adults on secure mental health units will be conducted. Thirty-two people (4 cohorts) will be recruited from secure services in Greater Manchester Mental Health NHS Foundation Trust. Participants will be randomly allocated to Motiv8 or TAU + Motiv8 waitlist. All participants will receive Motiv8 during the trial. Assessor-blinded physical/mental health and lifestyle assessments will be conducted at baseline, 10 weeks (post-intervention/waitlist), and after 12 weeks (post-waitlist intervention/follow-up). Motiv8 is a multidisciplinary intervention including exercise sessions, cooking/nutrition classes, physical health education, psychology sessions, sleep hygiene, peer support and medication review by pharmacy. A nested qualitative study will be conducted with a subsample of participants (n = 10) to explore their experiences of taking part. The analysis will focus on feasibility outcomes and tabulated success indicators of the study (e.g. Recruitment rates, retention rates, follow-up retention and response rates, attendance at sessions, the experience of involvement in the trial and delivery of the intervention, assessment of safety, development of a manualised intervention). Thematic analysis will be conducted through qualitative interviews. The analysis will aim to inform the development of a definitive trial. ETHICS AND DISSEMINATION: The trial has been granted ethical approval from the NHS Health Research Authority and adopted onto the UK Clinical Research Network Portfolio. Findings will be disseminated via peer-reviewed publications, professional and public networks, conferences and clinical services. TRIAL REGISTRATION: ISRCTN13539285.

The Resilience Hub approach for addressing mental health of health and social care workers during the COVID-19 pandemic: a mixed-methods evaluation.

Background: Resilience Hubs provide mental health screening, facilitation of access and direct provision of psychosocial support for health and social care keyworkers in England affected by the coronavirus disease 2019 pandemic. Aim: To explore implementation of the Hubs, including characteristics of staff using the services, support accessed, costing data and a range of stakeholder perspectives on the barriers and enablers to Hub use and implementation of staff well-being support within the context of the pandemic. Design: Mixed-methods evaluation. Setting: Four Resilience Hubs. Methods: Findings were integrated via mixed-method case studies, including: analyses of Hub mental health screening (N = 1973); follow-up questionnaire data (N = 299) on service use and health status of Hub clients; economic information provided by the Hubs; 63 interviews with Hub staff, wider stakeholders, Hub clients and keyworkers who did not use the Hubs. Results: Findings were consistent across Hubs and workstreams. Most Hub clients were NHS staff. Under-represented groups included men, keyworkers from minority ethnic communities, care homes and emergency services staff. Clients reported comorbid mental health needs across multiple domains (anxiety; depression; post-traumatic stress; alcohol use; functioning). Their health status was lower than population norms and relevant pre-pandemic data. Several factors predicted higher needs, but having pre-pandemic emotional well-being concerns was one of the most robust predictors of higher need. Sixty per cent of participants who completed follow-up questionnaires reported receiving mental health support since Hub screening, most of which was directly or indirectly due to Hub support. High levels of satisfaction were reported. As in many services, staffing was the central component of Hub cost. Hubs were predominantly staffed by senior clinicians; this staffing model was consistent with the generally severe difficulties experienced by clients and the need for systemic/team-based working. Costs associated with health and social care use for Hub clients were low, which may be due to barriers to accessing support in general. Enablers to accessing Hubs included: a clear understanding of the Hubs, how to self-refer, and managerial support. Barriers included confusion between Hubs and other support; unhelpful beliefs about job roles, unsupportive managers, negative workplace cultures and difficulties caused by systemic issues. Some keyworkers highlighted a perceived need for further diversity and cultural competency training to improve reach to under-represented communities. Other barriers for these groups included prior negative experiences of services, structural inequalities and stigma. Some wider stakeholders had concerns around growing waiting times for Hub-provided therapy, and insufficient data on Hub usage and outcomes. Feedback was otherwise very positive. Limitations: Main limitations included lack of comparative and pre-pandemic/baseline data, small numbers from under-represented groups limiting fine-grained analysis, and participant self-selection. Conclusions: Findings highlighted the value of the Hub model of outreach, screening, support navigation and provision of direct support during the coronavirus disease 2019 pandemic, and as a potential model to respond to future crises. The research provided recommendations to improve Hub promotion, equality/diversity/inclusion access issues, management of specialist resources and collection of relevant data on Hub outcomes and activities. Broader recommendations for the primary prevention of mental health difficulties across the health and care system are made, as individual support offers should be an adjunct to, not a replacement for, resolutions to systemic challenges. Research recommendations are made to conduct more robust evaluations of the clinical and cost-effectiveness of the Hubs, using larger data sets and comparative data. Study registration: This study is registered as researchregistry6303. 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: NIHR132269) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 29. See the NIHR Funding and Awards website for further award information.

Many health and social care staff struggled with mental health difficulties during the coronavirus disease 2019 pandemic. The study evaluated new National Health Service services ('Resilience Hubs') that were set up to help these keyworkers. We worked with four Hubs to: (1) look at who accessed the Hubs and what difficulties they had; (2) ask Hub 'clients' which support they used, and how helpful they found the Hubs; (3) look at what resources are needed to run the Hubs, to understand their 'value for money'; (4) interview people who worked with or used the Hubs (e.g. Hub staff, Hub clients, but also keyworkers who did not use the Hubs) to have their feedback. We used this information to make recommendations for the Hubs and the organisations that work with them. We found that Hub clients were mainly National Health Service staff. Many had several mental health difficulties, including anxiety, depression and post-traumatic stress disorder. Few men, staff from minority ethnic communities, care home workers and emergency service staff used the Hubs. People were generally happy with the support they had from the Hubs; clients who completed a follow-up questionnaire rated the helpfulness of support provided by Hubs as 92 out of 100 on average. Staffing was the main cost, as Hubs were mainly staffed by experienced clinicians. Things that made it easier for people to use the Hubs were clear understandings of Hub support and how to access it, and the support of their managers/employers. Some keyworkers from minority ethnic communities wanted greater diversity in the Hub teams. Some had concerns around waiting times and about not knowing enough about how well these services worked. Feedback was otherwise very positive. Our recommendations included how to: better promote the Hubs; improve inclusion of and support for individuals from minority groups; get better data on how well and for whom they work; and for employers to pay more attention to the mental health and well-being of keyworkers beyond the coronavirus disease 2019 pandemic.

Study protocol for an adaptive, multi-arm, multi-stage (MAMS) randomised controlled trial of brief remotely delivered psychosocial interventions for people with serious mental health problems who have experienced a recent suicidal crisis: Remote Approaches to Psychosocial Intervention Delivery (RAPID).

BACKGROUND: People with serious mental health problems (SMHP) are more likely to be admitted to psychiatric hospital following contact with crisis services. Admissions can have significant personal costs, be traumatic and are the most expensive form of mental health care. There is an urgent need for treatments to reduce suicidal thoughts and behaviours and reduce avoidable psychiatric admissions. METHODS: A multi-stage, multi-arm (MAMS) randomised controlled trial (RCT) with four arms conducted over two stages to determine the clinical and cost effectiveness of three psychosocial treatments, compared to treatment as usual (TAU), for people with SMHP who have had recent suicidal crisis. Primary outcome is any psychiatric hospital admissions over a 6-month period. We will assess the impact on suicidal thoughts and behaviour, hope, recovery, anxiety and depression. The remote treatments delivered over 3 months are structured peer support (PREVAIL); a safety planning approach (SAFETEL) delivered by assistant psychologists; and a CBT-based suicide prevention app accessed via a smartphone (BrighterSide). Recruitment is at five UK sites. Stage 1 includes an internal pilot with a priori progression criteria. In stage 1, the randomisation ratio was 1:1:1:2 in favour of TAU. This has been amended to 2:2:3 in favour of TAU following an unplanned change to remove the BrighterSide arm following the release of efficacy data from an independent RCT. Randomisation is via an independent remote web-based randomisation system using randomly permuted blocks, stratified by site. An interim analysis will be performed using data from the first 385 participants from PREVAIL, SAFETEL and TAU with outcome data at 6 months. If one arm is dropped for lack of benefit in stage 2, the allocation ratio of future participants will be 1:1. The expected total sample size is 1064 participants (1118 inclusive of BrighterSide participants). DISCUSSION: There is a need for evidence-based interventions to reduce psychiatric admissions, via reduction of suicidality. Our focus on remote delivery of established brief psychosocial interventions, utilisation of different modalities of delivery that can provide sustainable and scalable solutions, which are also suitable for a pandemic or national crisis context, will significantly advance treatment options. TRIAL REGISTRATION: ISRCTN33079589. Registered on June 20, 2022.

An Investigation into the Relationship Between Choice of Model Structure and How to Adjust for Subsequent Therapies Using a Case Study in Oncology.

BACKGROUND: A common challenge in health technology assessments (HTAs) of cancer treatments is how subsequent therapy use within the trial follow-up may influence cost-effectiveness model outcomes. Although overall survival (OS) is often a key driver of model results, there are no guidelines to advise how to adjust for this potential confounding, with different approaches available dependent on the model structure. OBJECTIVE: We compared a partitioned survival analysis (PartSA) with a semi-Markov multi-state model (MSM) structure, with and without attempts to adjust for the impact of subsequent therapies on OS using a case study describing outcomes for people with relapsed/refractory multiple myeloma. METHODS: Both model structures included three health states: pre-progression, progressed disease and death. Three traditional crossover methods were considered within the context of the PartSA, whereas for the MSM, the probability of post-progression death was pooled across arms. Impacts on the model incremental cost-effectiveness ratio (ICER) were recorded. RESULTS: The unadjusted PartSA produced an ICER of £623,563, and after adjustment yielded an ICER range of £381,340-£386,907. The unadjusted MSM produced an ICER of £1,283,780. Adjusting OS in the MSM resulted in an ICER of £345,486. CONCLUSIONS: The simplicity of the PartSA is lost when the decision problem becomes more complex (for example, when OS data are confounded by subsequent therapies). In this setting, the MSM structure may be considered more flexible, with fewer and less restrictive assumptions required versus the PartSA. Researchers should consider important study design features that may influence the generalisability of data when undertaking model conceptualisation.

Cost-effectiveness of home-based cardiac rehabilitation: a systematic review.

OBJECTIVE: Centre-based cardiac rehabilitation (CR) is recognised as cost-effective for individuals following a cardiac event. However, home-based alternatives are becoming increasingly popular, especially since COVID-19, which necessitated alternative modes of care delivery. This review aimed to assess whether home-based CR interventions are cost-effective (vs centre-based CR). METHODS: Using the MEDLINE, Embase and PsycINFO databases, literature searches were conducted in October 2021 to identify full economic evaluations (synthesising costs and effects). Studies were included if they focused on home-based elements of a CR programme or full home-based programmes. Data extraction and critical appraisal were completed using the NHS EED handbook, Consolidated Health Economic Evaluation Reporting Standards and Drummond checklists and were summarised narratively. The protocol was registered on the PROSPERO database (CRD42021286252). RESULTS: Nine studies were included in the review. Interventions were heterogeneous in terms of delivery, components of care and duration. Most studies were economic evaluations within clinical trials (8/9). All studies reported quality-adjusted life years, with the EQ-5D as the most common measure of health status (6/9 studies). Most studies (7/9 studies) concluded that home-based CR (added to or replacing centre-based CR) was cost-effective compared with centre-based options. CONCLUSIONS: Evidence suggests that home-based CR options are cost-effective. The limited size of the evidence base and heterogeneity in methods limits external validity. There were further limitations to the evidence base (eg, limited sample sizes) that increase uncertainty. Future research is needed to cover a greater range of home-based designs, including home-based options for psychological care, with greater sample sizes and the potential to acknowledge patient heterogeneity.

A Systematic Review of Methods to Incorporate External Evidence into Trial-Based Survival Extrapolations for Health Technology Assessment.

BACKGROUND: External evidence is commonly used to inform survival modeling for health technology assessment (HTA). While there are a range of methodological approaches that have been proposed, it is unclear which methods could be used and how they compare. PURPOSE: This review aims to identify, describe, and categorize established methods to incorporate external evidence into survival extrapolation for HTA. DATA SOURCES: Embase, MEDLINE, EconLit, and Web of Science databases were searched to identify published methodological studies, supplemented by hand searching and citation tracking. STUDY SELECTION: Eligible studies were required to present a novel extrapolation approach incorporating external evidence (i.e., data or information) within survival model estimation. DATA EXTRACTION: Studies were classified according to how the external evidence was integrated as a part of model fitting. Information was extracted concerning the model-fitting process, key requirements, assumptions, software, application contexts, and presentation of comparisons with, or validation against, other methods. DATA SYNTHESIS: Across 18 methods identified from 22 studies, themes included use of informative prior(s) (n = 5), piecewise (n = 7), and general population adjustment (n = 9), plus a variety of "other" (n = 8) approaches. Most methods were applied in cancer populations (n = 13). No studies compared or validated their method against another method that also incorporated external evidence. LIMITATIONS: As only studies with a specific methodological objective were included, methods proposed as part of another study type (e.g., an economic evaluation) were excluded from this review. CONCLUSIONS: Several methods were identified in this review, with common themes based on typical data sources and analytical approaches. Of note, no evidence was found comparing the identified methods to one another, and so an assessment of different methods would be a useful area for further research.HighlightsThis review aims to identify methods that have been used to incorporate external evidence into survival extrapolations, focusing on those that may be used to inform health technology assessment.We found a range of different approaches, including piecewise methods, Bayesian methods using informative priors, and general population adjustment methods, as well as a variety of "other" approaches.No studies attempted to compare the performance of alternative methods for incorporating external evidence with respect to the accuracy of survival predictions. Further research investigating this would be valuable.