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.