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Santos JD, Dawson S, Conefrey C, Isaacs T, Khanum M, Faisal S, Paramasivan S. Most UK cardiovascular disease trial protocols feature criteria that exclude ethnic minority participants: a systematic review. J Clin Epidemiol 2024; 167:111259. [PMID: 38215800 DOI: 10.1016/j.jclinepi.2024.111259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 12/12/2023] [Accepted: 01/08/2024] [Indexed: 01/14/2024]
Abstract
OBJECTIVES We systematically reviewed UK cardiovascular disease (CVD) randomized controlled trial (RCT) protocols to identify the proportion featuring eligibility criteria that may disproportionately exclude ethnic minority (EM) participants. METHODS We searched MEDLINE, Embase, and Cochrane Library databases, January 2014-June 2022, to identify UK CVD RCT protocols. We extracted nonclinical eligibility criteria from trial protocols and inductively categorized the trials by their language, consent, and broad (ambiguous) criteria. Findings are narratively reported. RESULTS Of the seventy included RCT protocols, most (87.1%; 61/70) mentioned consent within the eligibility criteria, with more than two-thirds (68.9%; 42/61) indicating a requirement for 'written' consent. Alternative consent pathways that can aid EM participation were absent. English language requirement was present in 22.9% (16/70) of the studies and 37.1% (26/70) featured broad criteria that are open to interpretation and subject to recruiter bias. Only 4.3% (3/70) protocols mentioned the provision of translation services. CONCLUSION Most UK CVD trial protocols feature eligibility criteria that potentially exclude EM groups. Trial eligibility criteria must be situated within a larger inclusive recruitment framework, where ethnicity is considered alongside other intersecting and disadvantaging identities.
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Affiliation(s)
- Jhulia Dos Santos
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Shoba Dawson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Carmel Conefrey
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Talia Isaacs
- UCL Centre for Applied Linguistics, IOE, UCL's Faculty of Education and Society, University College London, London, UK
| | - Mahwar Khanum
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Saba Faisal
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Sangeetha Paramasivan
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
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Carswell C, Cogley C, Bramham K, Chilcot J, Noble H, Siddiqi N. Chronic kidney disease and severe mental illness: a scoping review. J Nephrol 2023:10.1007/s40620-023-01599-8. [PMID: 37029882 PMCID: PMC10393892 DOI: 10.1007/s40620-023-01599-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 02/12/2023] [Indexed: 04/09/2023]
Abstract
BACKGROUND People who have severe mental illness experience higher rates of long-term conditions and die on average 15-20 years earlier than people who do not have severe mental illness, a phenomenon known as the mortality gap. Long-term conditions, such as diabetes, impact health outcomes for people who have severe mental illness, however there is limited recognition of the relationship between chronic kidney disease and severe mental illness. Therefore, the aim of this scoping review was to explore the available evidence on the relationship between chronic kidney disease and severe mental illness. METHODS Electronic databases, including MEDLINE, Embase, CINAHL, and PsycINFO were searched. The database searches were limited to articles published between January 2000-January 2022, due to significant progress that has been made in the detection, diagnosis and treatment of both SMI and CKD. Articles were eligible for inclusion if they explored the relationship between SMI and CKD (Stages 1-5) in terms of prevalence, risk factors, clinical outcomes, and access to treatment and services. Severe mental illness was defined as conditions that can present with psychosis, including schizophrenia, schizoaffective disorder, bipolar disorder, and other psychotic disorders. Thirty articles were included in the review. RESULTS The included studies illustrated that there is an increased risk of chronic kidney disease amongst people who have severe mental illness, compared to those who do not. However, people who have severe mental illness and chronic kidney disease are less likely to receive specialist nephrology care, are less likely to be evaluated for a transplant, and have higher rates of mortality. CONCLUSION In conclusion, there is a dearth of literature in this area, but the available literature suggests there are significant health inequalities in kidney care amongst people who have severe mental illness. Further research is needed to understand the factors that contribute to this relationship, and to develop strategies to improve both clinical outcomes and access to kidney care.
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Affiliation(s)
- Claire Carswell
- Department of Health Sciences, University of York, York, UK.
- School of Nursing and Midwifery, Queen's University Belfast, Belfast, Northern Ireland, UK.
| | - Clodagh Cogley
- School of Psychology, University College Dublin, Dublin, Ireland
| | | | - Joseph Chilcot
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Helen Noble
- School of Nursing and Midwifery, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Najma Siddiqi
- Department of Health Sciences, University of York, York, UK
- Hull York Medical School, York, UK
- Bradford District Care NHS Foundation Trust, Bradford, UK
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Australasian Genetic Counselors' Perceptions of Their Role in Supporting Clients' Behavior Change. J Pers Med 2022; 13:jpm13010030. [PMID: 36675691 PMCID: PMC9863991 DOI: 10.3390/jpm13010030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/09/2022] [Accepted: 12/21/2022] [Indexed: 12/24/2022] Open
Abstract
Genetic testing does not always change health behavior. Effective behavior change requires a theory-driven coordinated set of activities (behavior change techniques). Genetic counselors are ideally positioned to facilitate behavior change. We aimed to explore genetic counselors' perceptions of their role in supporting clients' behavior change to inform the design of an intervention. Recruitment was via a professional organization and genetics services. Data were collected from 26 genetic counselors via qualitative focus groups/interview. Transcripts were analyzed using thematic analysis and mapped to the COM-B model. We identified three behaviors genetic counselors wanted clients to change: attend appointments, access information, and share information with family members. Strategies for changing clients' behavior included: assessing needs and capabilities, providing information and support, enabling and monitoring behavior change. Barriers included lack of behavior change skills and knowledge, lack of time, and beliefs about ownership of healthcare, directiveness of behavior change, and scope of practice. Equipping genetic counselors to deliver behavior change requires (i) education in behavior change theory and behavior change techniques, (ii) integration of capability, opportunity and motivation assessment into existing practice, and (iii) development of evidence-based strategies using behavior change tools to focus discussions and promote clients' agency to change their behavior.
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Bradley T, Campbell E, Dray J, Bartlem K, Wye P, Hanly G, Gibson L, Fehily C, Bailey J, Wynne O, Colyvas K, Bowman J. Systematic review of lifestyle interventions to improve weight, physical activity and diet among people with a mental health condition. Syst Rev 2022; 11:198. [PMID: 36085250 PMCID: PMC9462072 DOI: 10.1186/s13643-022-02067-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 09/01/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND People with a mental health condition experience an elevated risk of chronic disease and greater prevalence of health and behaviours. Lifestyle interventions aim to reduce this risk by modifying health behaviours such as physical activity and diet. Previous reviews exploring the efficacy of such interventions for this group have typically limited inclusion to individuals with severe mental illness (SMI), with a focus of impact on weight. This review assessed the efficacy of lifestyle interventions delivered in community or outpatient settings to people with any mental health condition, on weight, physical activity and diet. METHODS Eligible studies were randomised or cluster-randomised controlled trials published between January 1999 and February 2019 aiming to improve weight, physical activity or diet, for people with any mental health condition. Two reviewers independently completed study screening, data extraction and assessment of methodological quality. Primary outcome measures were weight, physical activity and diet. Secondary outcome measures were body mass index (BMI), waist circumference, sedentary behaviour and mental health. Where possible, meta-analyses were conducted. Narrative synthesis using vote counting based on direction of effect was used where studies were not amenable to meta-analysis. RESULTS Fifty-seven studies were included (49 SMI only), with 46 contributing to meta-analyses. Meta-analyses revealed significant (< 0.05) effect of interventions on mean weight loss (-1.42 kg), achieving 5% weight loss (OR 2.48), weight maintenance (-2.05 kg), physical activity (IPAQ MET minutes: 226.82) and daily vegetable serves (0.51), but not on fruit serves (0.01). Significant effects were also seen for secondary outcomes of BMI (-0.48 units) and waist circumference (-0.87cm), but not mental health (depression: SMD -0.03; anxiety: SMD -0.49; severity of psychological symptoms: SMD 0.72). Studies reporting sedentary behaviour were not able to be meta-analysed. Most trials had high risk of bias, quality of evidence for weight and physical activity were moderate, while quality of evidence for diet was low. CONCLUSION Lifestyle interventions delivered to people with a mental health condition made statistically significant improvements to weight, BMI, waist circumference, vegetable serves and physical activity. Further high-quality trials with greater consistency in measurement and reporting of outcomes are needed to better understand the impact of lifestyle interventions on physical activity, diet, sedentary behaviour and mental health and to understand impact on subgroups. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42019137197.
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Affiliation(s)
- Tegan Bradley
- University of Newcastle, University Drive, Callaghan, NSW 2308 Australia
- Hunter Medical Research Institute, Lot 1, Kookaburra Cct, New Lambton Heights, NSW 2305 Australia
| | - Elizabeth Campbell
- Hunter New England Population Health, Locked Bag 10, Wallsend, NSW 2287 Australia
| | - Julia Dray
- University of Newcastle, University Drive, Callaghan, NSW 2308 Australia
- Hunter Medical Research Institute, Lot 1, Kookaburra Cct, New Lambton Heights, NSW 2305 Australia
| | - Kate Bartlem
- University of Newcastle, University Drive, Callaghan, NSW 2308 Australia
- Hunter Medical Research Institute, Lot 1, Kookaburra Cct, New Lambton Heights, NSW 2305 Australia
| | - Paula Wye
- University of Newcastle, University Drive, Callaghan, NSW 2308 Australia
| | - Grace Hanly
- University of Newcastle, University Drive, Callaghan, NSW 2308 Australia
- Hunter Medical Research Institute, Lot 1, Kookaburra Cct, New Lambton Heights, NSW 2305 Australia
| | - Lauren Gibson
- University of Newcastle, University Drive, Callaghan, NSW 2308 Australia
- Hunter Medical Research Institute, Lot 1, Kookaburra Cct, New Lambton Heights, NSW 2305 Australia
| | - Caitlin Fehily
- University of Newcastle, University Drive, Callaghan, NSW 2308 Australia
- Hunter Medical Research Institute, Lot 1, Kookaburra Cct, New Lambton Heights, NSW 2305 Australia
| | - Jacqueline Bailey
- University of Newcastle, University Drive, Callaghan, NSW 2308 Australia
| | - Olivia Wynne
- University of Newcastle, University Drive, Callaghan, NSW 2308 Australia
| | - Kim Colyvas
- University of Newcastle, University Drive, Callaghan, NSW 2308 Australia
| | - Jenny Bowman
- University of Newcastle, University Drive, Callaghan, NSW 2308 Australia
- Hunter Medical Research Institute, Lot 1, Kookaburra Cct, New Lambton Heights, NSW 2305 Australia
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Zabeen S, Lawn S, Venning A, Fairweather K. Why Do People with Severe Mental Illness Have Poor Cardiovascular Health?-The Need for Implementing a Recovery-Based Self-Management Approach. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182312556. [PMID: 34886281 PMCID: PMC8656807 DOI: 10.3390/ijerph182312556] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 11/20/2021] [Accepted: 11/27/2021] [Indexed: 12/04/2022]
Abstract
People with severe mental illness (SMI) die significantly earlier than their well counterparts, mainly due to preventable chronic conditions such as cardiovascular disease (CVD). Based on the existing research, this perspective paper summarises the key contributors to CVD in people with SMI to better target the areas that require more attention to reduce, and ultimately resolve this health inequity. We discuss five broad factors that, according to current international evidence, are believed to be implicated in the development and maintenance of CVD in people with SMI: (1) bio-psychological and lifestyle-related factors; (2) socio-environmental factors; (3) health system-related factors; (4) service culture and practice-related factors; and (5) research-related gaps on how to improve the cardiovascular health of those with SMI. This perspective paper identifies that CVD in people with SMI is a multi-faceted problem involving a range of risk factors. Furthermore, existing chronic care or clinical recovery models alone are insufficient to address this complex problem, and none of these models have identified the significant roles that family caregivers play in improving a person’s self-management behaviours. A new framework is proposed to resolve this complex health issue that warrants a collaborative approach within and between different health and social care sectors.
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Affiliation(s)
- Sara Zabeen
- College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia; (S.L.); (A.V.); (K.F.)
- Menzies School of Health Research, Charles Darwin University, Darwin 0811, Australia
- Correspondence: ; Tel.: +61-0481-525-497
| | - Sharon Lawn
- College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia; (S.L.); (A.V.); (K.F.)
| | - Anthony Venning
- College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia; (S.L.); (A.V.); (K.F.)
| | - Kate Fairweather
- College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia; (S.L.); (A.V.); (K.F.)
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Hassan S, Heinkel S, Burton A, Blackburn R, McCloud T, Ross J, Osborn D, Walters K. A qualitative study exploring the barriers and facilitators of implementing a cardiovascular disease risk reducing intervention for people with severe mental illness into primary care contexts across England: the 'PRIMROSE' trial. BMC Health Serv Res 2020; 20:753. [PMID: 32799925 PMCID: PMC7429749 DOI: 10.1186/s12913-020-05643-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Accepted: 08/11/2020] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND People with severe mental illness (SMI) are at greater risk of earlier mortality due to physical health problems including cardiovascular disease (CVD). There is limited work exploring whether physical health interventions for people with SMI can be embedded and/or adopted within specific healthcare settings. This information is necessary to optimise the development of services and interventions within healthcare settings. This study explores the barriers and facilitators of implementing a nurse-delivered intervention ('PRIMROSE') designed to reduce CVD risk in people with SMI in primary care, using Normalisation Process Theory (NPT), a theory that explains the dynamics of embedding or 'normalising' a complex intervention within healthcare settings. METHODS Semi-structured interviews were conducted between April-December 2016 with patients with SMI at risk of CVD who received the PRIMROSE intervention, and practice nurses and healthcare assistants who delivered it in primary care in England. Interviews were audio recorded, transcribed and analysed using thematic analysis. Emergent themes were then mapped on to constructs of NPT. RESULTS Fifteen patients and 15 staff participated. The implementation of PRIMROSE was affected by the following as categorised by the NPT domains: 1) Coherence, where both staff and patients expressed an understanding of the purpose and value of the intervention, 2) Cognitive participation, including mental health stigma and staff perceptions of the compatibility of the intervention to primary care contexts, 3) Collective action, including 3.1. Interactional workability in terms of lack of patient engagement despite flexible appointment scheduling. The structured nature of the intervention and the need for additional nurse time were considered barriers, 3.2. Relational integration i.e. whereby positive relationships between staff and patients facilitated implementation, and access to 'in-house' staff support was considered important, 3.3. Skill-set workability in terms of staff skills, knowledge and training facilitated implementation, 3.4. Contextual integration regarding the accessibility of resources sometimes prevented collective action. 4) Reflexive monitoring, where the staff commonly appraised the intervention by suggesting designated timeslots and technology may improve the intervention. CONCLUSIONS Future interventions for physical health in people with SMI could consider the following items to improve implementation: 1) training for practitioners in CVD risk prevention to increase practitioners knowledge of physical interventions 2) training in SMI to increase practitioner confidence to engage with people with SMI and reduce mental health stigma and 3) access to resources including specialist services, additional staff and time. Access to specialist behaviour change services may be beneficial for patients with specific health goals. Additional staff to support workload and share knowledge may also be valuable. More time for appointments with people with SMI may allow practitioners to better meet patient needs.
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Affiliation(s)
- Suzan Hassan
- Research Department of Primary Care and Population Health, University College London, Upper Third Floor, UCL Medical School (Royal Free Campus), Rowland Hill Street, London, NW3 2PF, UK.
| | - Samira Heinkel
- Division of Psychiatry, University College London, 6th Floor, Wing B, Maple House, 149 Tottenham Court Road, London, W1T 7NF, UK
| | - Alexandra Burton
- Division of Psychiatry, University College London, 6th Floor, Wing B, Maple House, 149 Tottenham Court Road, London, W1T 7NF, UK
| | - Ruth Blackburn
- Division of Psychiatry, University College London, 6th Floor, Wing B, Maple House, 149 Tottenham Court Road, London, W1T 7NF, UK
| | - Tayla McCloud
- Division of Psychiatry, University College London, 6th Floor, Wing B, Maple House, 149 Tottenham Court Road, London, W1T 7NF, UK
| | - Jamie Ross
- Research Department of Primary Care and Population Health, University College London, Upper Third Floor, UCL Medical School (Royal Free Campus), Rowland Hill Street, London, NW3 2PF, UK
| | - David Osborn
- Division of Psychiatry, University College London, 6th Floor, Wing B, Maple House, 149 Tottenham Court Road, London, W1T 7NF, UK.,Camden and Islington NHS Foundation Trust, 4 St Pancras Way, London, NW1 0PE, UK
| | - Kate Walters
- Research Department of Primary Care and Population Health, University College London, Upper Third Floor, UCL Medical School (Royal Free Campus), Rowland Hill Street, London, NW3 2PF, UK
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Hassan S, Ross J, Marston L, Burton A, Osborn D, Walters K. Exploring how health behaviours are supported and changed in people with severe mental illness: A qualitative study of a cardiovascular risk reducing intervention in Primary Care in England. Br J Health Psychol 2020; 25:428-451. [PMID: 32281720 DOI: 10.1111/bjhp.12415] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 03/19/2020] [Indexed: 11/29/2022]
Abstract
Objectives This study explored how health behaviours were supported and changed in people with severe mental illness by primary health care professionals trained in delivering behaviour change techniques (BCTs) within a cardiovascular disease risk reducing intervention. Design Secondary qualitative analysis of 30 staff and patient interviews. Methods We mapped coded data to the BCT Taxonomy (version 1) to identify BCT application. Thematic analysis was conducted to explore the barriers and facilitators of supporting and changing health behaviours. Themes were then interpreted using the Capability, Opportunity, Motivation, and Behaviour model to gain greater explanation behind the processes. Results Twenty BCTs were identified. Staff and patients perceived that health behaviours were commonly affected by both automatic and reflective motivation, sometimes in turn affected by psychological capability, social, and physical opportunity. Staff and patients suggested that motivation was enhanced by both patient and staff ability to observe health benefits, in some cases patients' health knowledge, mental health status, and social support networks. It was suggested that engaging in/sustaining healthy behaviours was influenced by physical opportunities to engrain behaviours into routine. Conclusions According to staff and patients, health behaviour change in this population was driven by complex processes. It was suggested that capability, opportunity, and motivation were in some cases enhanced by BCTs, but variable. Behaviour change may be optimized by individualized behavioural assessments, identifying drivers of behaviour and applying a range of BCTs may help to target individual needs. Patient peer-led approaches, techniques to encourage awareness of visible success, and normalizing health behaviours may increase behaviour change. Statement of contribution What is already known on this subject? Poorer health behaviours may contribute to early mortality rates in people with severe mental illness. Health care professionals are encouraged to target the uptake of healthy behaviours, but there is limited guidance on how. The processes that cause or inhibit health behaviour change within interventions that use behaviour change techniques by health care practitioners are unclear. What does the study add? Staff and patients suggested that behaviour change techniques (BCTs) in some cases increased capability, opportunity, and motivation to engage in healthy behaviours, but in other cases had variable success. Staff and patients reported that in some cases, motivation impacted health behaviour change and was in turn affected by psychological capability, social, and physical opportunity. Individualized behavioural assessments, flexible approaches to BCT application, involvement from patient peer support and different ways of targeting patient motivation may help to increase healthy behaviour changes in this population.
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Affiliation(s)
- Suzan Hassan
- Department of Primary Care and Population Health, University College London, UK
| | - Jamie Ross
- Department of Primary Care and Population Health, University College London, UK
| | - Louise Marston
- Department of Primary Care and Population Health, University College London, UK
| | | | - David Osborn
- Division of Psychiatry, University College London, UK.,Camden and Islington NHS Foundation Trust, London, UK
| | - Kate Walters
- Department of Primary Care and Population Health, University College London, UK
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Walton H, Spector A, Williamson M, Tombor I, Michie S. Developing quality fidelity and engagement measures for complex health interventions. Br J Health Psychol 2020; 25:39-60. [PMID: 31693797 PMCID: PMC7004004 DOI: 10.1111/bjhp.12394] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Revised: 10/04/2019] [Indexed: 11/27/2022]
Abstract
OBJECTIVES To understand whether interventions are effective, we need to know whether the interventions are delivered as planned (with fidelity) and engaged with. To measure fidelity and engagement effectively, high-quality measures are needed. We outline a five-step method which can be used to develop quality measures of fidelity and engagement for complex health interventions. We provide examples from a fidelity study conducted within an evaluation of an intervention aimed to increase independence in dementia. METHODS We propose five steps that can be systematically used to develop fidelity checklists for researchers, providers, and participants to measure fidelity and engagement. These steps include the following: (1) reviewing previous measures, (2) analysing intervention components and developing a framework outlining the content of the intervention, (3) developing fidelity checklists and coding guidelines, (4) obtaining feedback about the content and wording of checklists and guidelines, and (5) piloting and refining checklists and coding guidelines to assess and improve reliability. RESULTS Three fidelity checklists that can be used reliably were developed to measure fidelity of and engagement with, the Promoting Independence in Dementia (PRIDE) intervention. As these measures were designed to be used by researchers, providers, and participants, we developed two versions of the checklists: one for participants and one for researchers and providers. CONCLUSIONS The five steps that we propose can be used to develop psychometrically robust and implementable measures of fidelity and engagement for complex health interventions that can be used by different target audiences. By considering quality when developing measures, we can be more confident in the interpretation of intervention outcomes drawn from fidelity and engagement studies. Statement of contribution What is already known on the subject? Fidelity and engagement can be measured using a range of methods, such as observation and self-report. Studies seldom report psychometric and implementation qualities of fidelity measures. What does this study add? A method for developing fidelity and engagement measures for complex health interventions. Guidance on how to consider quality when developing fidelity and engagement measures.
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Affiliation(s)
- Holly Walton
- Department of Applied Health ResearchUniversity College LondonUK
| | - Aimee Spector
- Department of Clinical, Educational and Health PsychologyUniversity College LondonUK
| | | | - Ildiko Tombor
- Department of Behavioural Science and HealthUniversity College LondonUK
| | - Susan Michie
- Department of Clinical, Educational and Health PsychologyUniversity College LondonUK
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Is there an association between perceived social support and cardiovascular health behaviours in people with severe mental illnesses? Soc Psychiatry Psychiatr Epidemiol 2020; 55:1659-1669. [PMID: 32424502 PMCID: PMC7585561 DOI: 10.1007/s00127-020-01879-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2019] [Accepted: 05/02/2020] [Indexed: 10/24/2022]
Abstract
PURPOSE People with severe mental illnesses (SMI) have an increased risk of cardiovascular disease (CVD). Research in the general population suggests that social support may protect against increased CVD morbidity and mortality; however, this may not apply to those with SMI. We aimed to explore the association between perceived social support and attendance at primary care nurse CVD risk reduction clinic appointments and CVD risk-reducing behaviours in an SMI population with elevated CVD risk factors. METHODS We used longitudinal and cross-sectional data from a randomised controlled trial on 326 adults with SMI recruited via 76 general practices in England. Multilevel regression analysis estimated the effect of perceived social support on attendance at CVD risk reduction clinic appointments over 6 months, and adherence to CVD medication, physical activity, diet, smoking and alcohol use at baseline, adjusted by age, sex, ethnicity, deprivation, psychiatric diagnosis and employment. RESULTS Perceived social support predicted greater appointment attendance in unadjusted (IRR = 1.005; 1.000-1.010; p = 0.05) but not adjusted analysis (IRR = 1.003; 0.998-1.009; p = 0.25). Perceived social support was associated with greater adherence to medication; for each 1% increase in social support, there was a 4.2% increase in medication adherence (OR = 1.042; 1.015-1.070; p = 0.002). No association was found between greater perceived social support and greater physical activity, lower sedentary behaviour, healthier diet, lower alcohol use or being a non-smoker. CONCLUSIONS Social support may be an important facilitator for CVD medication adherence and is potentially important for primary care appointment attendance; however, alternative strategies might be needed to help people with SMI engage in physical activity, healthier diets and to reduce their smoking and alcohol use.
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Osborn D, Burton A, Walters K, Atkins L, Barnes T, Blackburn R, Craig T, Gilbert H, Gray B, Hardoon S, Heinkel S, Holt R, Hunter R, Johnston C, King M, Leibowitz J, Marston L, Michie S, Morris R, Morris S, Nazareth I, Omar R, Petersen I, Peveler R, Pinfold V, Stevenson F, Zomer E. Primary care management of cardiovascular risk for people with severe mental illnesses: the Primrose research programme including cluster RCT. PROGRAMME GRANTS FOR APPLIED RESEARCH 2019. [DOI: 10.3310/pgfar07020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background
Effective interventions are needed to prevent cardiovascular disease (CVD) in people with severe mental illnesses (SMI) because their risk of CVD is higher than that of the general population.
Objectives
(1) Develop and validate risk models for predicting CVD events in people with SMI and evaluate their cost-effectiveness, (2) develop an intervention to reduce levels of cholesterol and CVD risk in SMI and (3) test the clinical effectiveness and cost-effectiveness of this new intervention in primary care.
Design
Mixed methods with patient and public involvement throughout. The mixed methods were (1) a prospective cohort and risk score validation study and cost-effectiveness modelling, (2) development work (focus groups, updated systematic review of interventions, primary care database studies investigating statin prescribing and effectiveness) and (3) cluster randomised controlled trial (RCT) assessing the clinical effectiveness and cost-effectiveness of a new practitioner-led intervention, and fidelity assessment of audio-recorded appointments.
Setting
General practices across England.
Participants
All studies included adults with SMI (schizophrenia, bipolar disorder or other non-organic psychosis). The RCT included adults with SMI and two or more CVD risk factors.
Interventions
The intervention consisted of 8–12 appointments with a practice nurse/health-care assistant over 6 months, involving collaborative behavioural approaches to CVD risk factors. The intervention was compared with routine practice with a general practitioner (GP).
Main outcome measures
The primary outcome for the risk score work was CVD events, in the cost-effectiveness modelling it was quality-adjusted life-years (QALYs) and in the RCT it was level of total cholesterol.
Data sources
Databases studies used The Health Improvement Network (THIN). Intervention development work included focus groups and systematic reviews. The RCT collected patient self-reported and routine NHS GP data. Intervention appointments were audio-recorded.
Results
Two CVD risk score models were developed and validated in 38,824 people with SMI in THIN: the Primrose lipid model requiring cholesterol levels, and the Primrose body mass index (BMI) model with no blood test. These models performed better than published Cox Framingham models. In health economic modelling, the Primrose BMI model was most cost-effective when used as an algorithm to drive statin prescriptions. Focus groups identified barriers to, and facilitators of, reducing CVD risk in SMI including patient engagement and motivation, staff confidence, involving supportive others, goal-setting and continuity of care. Findings were synthesised with evidence from updated systematic reviews to create the Primrose intervention and training programme. THIN cohort studies in 16,854 people with SMI demonstrated that statins effectively reduced levels of cholesterol, with similar effect sizes to those in general population studies over 12–24 months (mean decrease 1.2 mmol/l). Cluster RCT: 76 GP practices were randomised to the Primrose intervention (n = 38) or treatment as usual (TAU) (n = 38). The primary outcome (level of cholesterol) was analysed for 137 out of 155 participants in Primrose and 152 out of 172 in TAU. There was no difference in levels of cholesterol at 12 months [5.4 mmol/l Primrose vs. 5.5 mmol/l TAU; coefficient 0.03; 95% confidence interval (CI) –0.22 to 0.29], nor in secondary outcomes related to cardiometabolic parameters, well-being or medication adherence. Mean cholesterol levels decreased over 12 months in both arms (–0.22 mmol/l Primrose vs. –0.39 mmol/l TAU). There was a significant reduction in the cost of inpatient mental health attendances (–£799, 95% CI –£1480 to –£117) and total health-care costs (–£895, 95% CI –£1631 to –£160; p = 0.012) in the intervention group, but no significant difference in QALYs (–0.011, 95% CI –0.034 to 0.011). A total of 69% of patients attended two or more Primrose appointments. Audiotapes revealed moderate fidelity to intervention delivery (67.7%). Statin prescribing and adherence was rarely addressed.
Limitations
RCT participants and practices may not represent all UK practices. CVD care in the TAU arm may have been enhanced by trial procedures involving CVD risk screening and feedback.
Conclusions
SMI-specific CVD risk scores better predict new CVD if used to guide statin prescribing in SMI. Statins are effective in reducing levels of cholesterol in people with SMI in UK clinical practice. This primary care RCT evaluated an evidence-based practitioner-led intervention that was well attended by patients and intervention components were delivered. No superiority was shown for the new intervention over TAU for level of cholesterol, but cholesterol levels decreased over 12 months in both arms and the intervention showed fewer inpatient admissions. There was no difference in cholesterol levels between the intervention and TAU arms, which might reflect better than standard general practice care in TAU, heterogeneity in intervention delivery or suboptimal emphasis on statins.
Future work
The new risk score should be updated, deployed and tested in different settings and compared with the latest versions of CVD risk scores in different countries. Future research on CVD risk interventions should emphasise statin prescriptions more. The mechanism behind lower costs with the Primrose intervention needs exploring, including SMI-related training and offering frequent support to people with SMI in primary care.
Trial registration
Current Controlled Trials ISRCTN13762819.
Funding
This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 7, No. 2. See the NIHR Journals Library website for further project information. Professor David Osborn is supported by the University College London Hospital NIHR Biomedical Research Centre and he was also in part supported by the NIHR Collaboration for Leadership in Applied Health Research and Care (CLAHRC) North Thames at Barts Health NHS Trust.
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Affiliation(s)
- David Osborn
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
- Camden and Islington NHS Foundation Trust, St Pancras Hospital, London, UK
| | - Alexandra Burton
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
| | - Kate Walters
- Department of Primary Care and Population Health, University College London, London, UK
| | - Lou Atkins
- Centre for Behaviour Change, Department of Clinical, Educational and Health Psychology, Division of Psychology and Language Sciences, Faculty of Brain Sciences, University College London, London, UK
| | - Thomas Barnes
- Faculty of Medicine, Department of Medicine, Imperial College London, London, UK
| | - Ruth Blackburn
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
| | - Thomas Craig
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Hazel Gilbert
- Department of Primary Care and Population Health, University College London, London, UK
| | - Ben Gray
- The McPin Foundation, London, UK
| | - Sarah Hardoon
- Department of Primary Care and Population Health, University College London, London, UK
| | - Samira Heinkel
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
| | - Richard Holt
- Human Development and Health Academic Unit, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Rachael Hunter
- Department of Primary Care and Population Health, University College London, London, UK
| | - Claire Johnston
- School of Health and Education, Faculty of Professional and Social Sciences, Middlesex University, London, UK
| | - Michael King
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
- Camden and Islington NHS Foundation Trust, St Pancras Hospital, London, UK
| | - Judy Leibowitz
- Camden and Islington NHS Foundation Trust, St Pancras Hospital, London, UK
| | - Louise Marston
- Department of Primary Care and Population Health, University College London, London, UK
| | - Susan Michie
- Camden and Islington NHS Foundation Trust, St Pancras Hospital, London, UK
- Centre for Behaviour Change, Department of Clinical, Educational and Health Psychology, Division of Psychology and Language Sciences, Faculty of Brain Sciences, University College London, London, UK
| | - Richard Morris
- Department of Primary Care and Population Health, University College London, London, UK
| | - Steve Morris
- Department of Allied Health Research, University College London, London, UK
| | - Irwin Nazareth
- Department of Primary Care and Population Health, University College London, London, UK
| | - Rumana Omar
- Department of Statistical Science, University College London, London, UK
| | - Irene Petersen
- Department of Primary Care and Population Health, University College London, London, UK
| | - Robert Peveler
- Human Development and Health Academic Unit, Faculty of Medicine, University of Southampton, Southampton, UK
| | | | - Fiona Stevenson
- Department of Primary Care and Population Health, University College London, London, UK
| | - Ella Zomer
- Department of Primary Care and Population Health, University College London, London, UK
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11
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Houben N, Janssen EPCJ, Hendriks MRC, van der Kellen D, van Alphen BPJ, van Meijel B. Physical health status of older adults with severe mental illness: The PHiSMI-E cohort study. Int J Ment Health Nurs 2019; 28:457-467. [PMID: 30294958 DOI: 10.1111/inm.12547] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/03/2018] [Indexed: 12/26/2022]
Abstract
The objective was to use various somatic parameters as basis for investigating the physical health of older adults with severe mental illnesses (SMI). A cross-sectional study design is performed by using baseline data from the Physical Health in SMI-elderly (PHiSMI-E) study. Data were collected using the Nursing Monitoring of Somatic Status and Lifestyle - Mental Health instrument in adults aged over 60 with SMI in a large Dutch mental health institute. Ninety-nine elderly SMI patients were included. Somatic comorbidity (84.8%), use of somatic medication (77.7%) and polypharmacy (67.7%) were prevalent. Extrapyramidal symptoms were experienced by 51% of patients, mainly in the subgroup with psychotic disorders (75.6%). Unhealthy diet was reported in 16.2%, obesity in 27.3%, and physical inactivity in 57.6%. Fatigue (67.7%) and dry mouth (66.6%) were the commonest reported physical symptoms. Mean VAS score (scale 0-10) indicating participants' self-perceived physical health was 6.7 (SD ± 1.6). After division of the total patient group into tertiles based on the VAS scores, the lowest tertile was characterized by less physical activity, unhealthier diet, more use of medication, more fatigue, somnolence, and inner agitation. In conclusion, impaired physical health status was common in these older patients with SMI. Although they had more psychiatric and somatic comorbidity than adult SMI patients described in the literature, they had a healthier lifestyle. To reduce morbidity and premature mortality in these frail patients, it is essential that healthcare providers are aware of the high prevalence of somatic comorbidity and symptoms, and of their interactions with the psychiatric disorders. This study improves our understanding of differences in vulnerability factors of older patients with SMI. The (early) detection of somatic comorbidities may improve long-term health outcomes of these patients.
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Affiliation(s)
- Noortje Houben
- Department of Old Age Psychiatry, Mondriaan, Heerlen, The Netherlands.,Department of Advanced Nursing Practice, School for Nursing, Zuyd University, Heerlen, The Netherlands
| | - Eveline P C J Janssen
- Department of Old Age Psychiatry, Mondriaan, Heerlen, The Netherlands.,Department of Psychiatry and Neuropsychology, MHeNs School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Marike R C Hendriks
- Department of Advanced Nursing Practice, School for Nursing, Zuyd University, Heerlen, The Netherlands
| | - Digna van der Kellen
- Department of Mental Health, Indigo Rijnmond, Rotterdam, The Netherlands.,uTOPiGGZ, Training and Coaching, Spijkenisse, The Netherlands
| | - Bas P J van Alphen
- Department of Old Age Psychiatry, Mondriaan, Heerlen, The Netherlands.,Department of Clinical and Lifespan Psychology, Vrije universiteit Brussel (VUB), Brussels, Belgium.,Department of Medical and Clinical Psychology, School of Social and Behavioural Sciences, Tilburg University, Tilburg, The Netherlands
| | - Berno van Meijel
- Inholland University of Applied Sciences, Research Group Mental Health Nursing, Amsterdam, The Netherlands.,Department of Psychiatry, VU University Medical Center, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.,Parnassia Psychiatric Institute, The Hague, The Netherlands.,GGZ-VS, Academy for Masters in Advanced Nursing Practice, Utrecht, The Netherlands
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12
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Osborn D, Burton A, Hunter R, Marston L, Atkins L, Barnes T, Blackburn R, Craig T, Gilbert H, Heinkel S, Holt R, King M, Michie S, Morris R, Morris S, Nazareth I, Omar R, Petersen I, Peveler R, Pinfold V, Walters K. Clinical and cost-effectiveness of an intervention for reducing cholesterol and cardiovascular risk for people with severe mental illness in English primary care: a cluster randomised controlled trial. Lancet Psychiatry 2018; 5:145-154. [PMID: 29396118 DOI: 10.1016/s2215-0366(18)30007-5] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Revised: 12/13/2017] [Accepted: 12/14/2017] [Indexed: 12/15/2022]
Abstract
BACKGROUND People with severe mental illnesses, including psychosis, have an increased risk of cardiovascular disease. We aimed to evaluate the effects of a primary care intervention on decreasing total cholesterol concentrations and cardiovascular disease risk in people with severe mental illnesses. METHODS We did this cluster randomised trial in general practices across England, with general practices as the cluster unit. We randomly assigned general practices (1:1) with 40 or more patients with severe mental illnesses using a computer-generated random sequence with a block size of four. Researchers were masked to allocation, but patients and general practice staff were not. We included participants aged 30-75 years with severe mental illnesses (schizophrenia, bipolar disorder, or psychosis), who had raised cholesterol concentrations (5·0 mmol/L) or a total:HDL cholesterol ratio of 4·0 mmol/L or more and one or more modifiable cardiovascular disease risk factors. Eligible participants were recruited within each practice before randomisation. The Primrose intervention consisted of appointments (≤12) with a trained primary care professional involving manualised interventions for cardiovascular disease prevention (ie, adhering to statins, improving diet or physical activity levels, reducing alcohol, or quitting smoking). Treatment as usual involved feedback of screening results only. The primary outcome was total cholesterol at 12 months and the primary economic analysis outcome was health-care costs. We used intention-to-treat analysis. The trial is registered with Current Controlled Trials, number ISRCTN13762819. FINDINGS Between Dec 10, 2013, and Sept 30, 2015, we recruited general practices and between May 9, 2014, and Feb 10, 2016, we recruited participants and randomly assigned 76 general practices with 327 participants to the Primrose intervention (n=38 with 155 patients) or treatment as usual (n=38 with 172 patients). Total cholesterol concentration data were available at 12 months for 137 (88%) participants in the Primrose intervention group and 152 (88%) participants in the treatment-as-usual group. The mean total cholesterol concentration did not differ at 12 months between the two groups (5·4 mmol/L [SD 1·1] for Primrose vs 5·5 mmol/L [1·1] for treatment as usual; mean difference estimate 0·03, 95% CI -0·22 to 0·29; p=0·788). This result was unchanged by pre-agreed supportive analyses. Mean cholesterol decreased over 12 months (-0·22 mmol/L [1·1] for Primrose vs -0·36 mmol/L [1·1] for treatment as usual). Total health-care costs (£1286 [SE 178] in the Primrose intervention group vs £2182 [328] in the treatment-as-usual group; mean difference -£895, 95% CI -1631 to -160; p=0·012) and psychiatric inpatient costs (£157 [135] vs £956 [313]; -£799, -1480 to -117; p=0·018) were lower in the Primrose intervention group than the treatment-as-usual group. Six serious adverse events of hospital admission and one death occurred in the Primrose group (n=7) and 23, including three deaths, occurred in the treatment-as-usual group (n=18). INTERPRETATION Total cholesterol concentration at 12 months did not differ between the Primrose and treatment-as-usual groups, possibly because of the cluster design, good care in the treatment-as-usual group, short duration of the intervention, or suboptimal focus on statin prescribing. The association between the Primrose intervention and fewer psychiatric admissions, with potential cost-effectiveness, might be important. FUNDING National Institute of Health Research Programme Grants for Applied Research.
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Affiliation(s)
- David Osborn
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK; Camden and Islington National Health Service Foundation Trust, St Pancras Hospital, London, UK.
| | - Alexandra Burton
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
| | - Rachael Hunter
- Department of Primary Care and Population Health, University College London, London, UK
| | - Louise Marston
- Department of Primary Care and Population Health, University College London, London, UK
| | - Lou Atkins
- Centre for Behaviour Change, Department of Clinical, Educational, and Health Psychology, Division of Psychology and Language Sciences, Faculty of Brain Sciences, University College London, London, UK
| | - Thomas Barnes
- Department of Medicine, Faculty of Medicine, Imperial College London, London, UK
| | - Ruth Blackburn
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
| | - Thomas Craig
- Institute of Psychiatry, Psychology & Neuroscience, Kings College London, London, UK
| | - Hazel Gilbert
- Department of Primary Care and Population Health, University College London, London, UK
| | - Samira Heinkel
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
| | - Richard Holt
- Human Development and Health Academic Unit, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Michael King
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK; Camden and Islington National Health Service Foundation Trust, St Pancras Hospital, London, UK
| | - Susan Michie
- Centre for Behaviour Change, Department of Clinical, Educational, and Health Psychology, Division of Psychology and Language Sciences, Faculty of Brain Sciences, University College London, London, UK; Camden and Islington National Health Service Foundation Trust, St Pancras Hospital, London, UK
| | - Richard Morris
- Department of Allied Health Research, University College London, London, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Steve Morris
- Department of Allied Health Research, University College London, London, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Irwin Nazareth
- Department of Primary Care and Population Health, University College London, London, UK
| | - Rumana Omar
- Department of Statistical Science, University College London, London, UK
| | - Irene Petersen
- Department of Primary Care and Population Health, University College London, London, UK
| | - Robert Peveler
- Human Development and Health Academic Unit, Faculty of Medicine, University of Southampton, Southampton, UK
| | | | - Kate Walters
- Department of Primary Care and Population Health, University College London, London, UK
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13
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Mangurian C, Niu GC, Schillinger D, Newcomer JW, Dilley J, Handley MA. Utilization of the Behavior Change Wheel framework to develop a model to improve cardiometabolic screening for people with severe mental illness. Implement Sci 2017; 12:134. [PMID: 29137666 PMCID: PMC5686815 DOI: 10.1186/s13012-017-0663-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2017] [Accepted: 11/01/2017] [Indexed: 12/21/2022] Open
Abstract
Background Individuals with severe mental illness (e.g., schizophrenia, bipolar disorder) die 10–25 years earlier than the general population, primarily from premature cardiovascular disease (CVD). Contributing factors are complex, but include systemic-related factors of poorly integrated primary care and mental health services. Although evidence-based models exist for integrating mental health care into primary care settings, the evidence base for integrating medical care into specialty mental health settings is limited. Such models are referred to as “reverse” integration. In this paper, we describe the application of an implementation science framework in designing a model to improve CVD outcomes for individuals with severe mental illness (SMI) who receive services in a community mental health setting. Methods Using principles from the theory of planned behavior, focus groups were conducted to understand stakeholder perspectives of barriers to CVD risk factor screening and treatment identify potential target behaviors. We then applied results to the overarching Behavior Change Wheel framework, a systematic and theory-driven approach that incorporates the COM-B model (capability, opportunity, motivation, and behavior), to build an intervention to improve CVD risk factor screening and treatment for people with SMI. Results Following a stepped approach from the Behavior Change Wheel framework, a model to deliver primary preventive care for people that use community mental health settings as their de facto health home was developed. The CRANIUM (cardiometabolic risk assessment and treatment through a novel integration model for underserved populations with mental illness) model focuses on engaging community psychiatrists to expand their scope of practice to become responsible for CVD risk, with significant clinical decision support. Conclusion The CRANIUM model was designed by integrating behavioral change theory and implementation theory. CRANIUM is feasible to implement, is highly acceptable to, and targets provider behavior change, and is replicable and efficient for helping to integrate primary preventive care services in community mental health settings. CRANIUM can be scaled up to increase CVD preventive care delivery and ultimately improve health outcomes among people with SMI served within a public mental health care system.
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Affiliation(s)
- Christina Mangurian
- Department of Psychiatry, Weill Institute for Neurosciences, UCSF at Zuckerberg San Francisco General (ZSFG), 1001 Potrero Avenue, 7M8, San Francisco, CA, 94110, USA. .,UCSF Center for Vulnerable Populations at ZSFG, San Francisco, CA, USA.
| | - Grace C Niu
- Department of Psychiatry, Weill Institute for Neurosciences, UCSF at Zuckerberg San Francisco General (ZSFG), 1001 Potrero Avenue, 7M8, San Francisco, CA, 94110, USA
| | - Dean Schillinger
- UCSF Center for Vulnerable Populations at ZSFG, San Francisco, CA, USA.,UCSF Department of Medicine, Division of General Internal Medicine at ZSFG, 1001 Potrero Avenue, 1320A, San Francisco, CA, 94110, USA
| | - John W Newcomer
- Department of Clinical Biomedical Sciences, Charles E. Schmidt College of Medicine, Florida Atlantic University, 777 Glades Road, BC-71 Rm 241, Boca Raton, FL, 33431, USA
| | - James Dilley
- Department of Psychiatry, Weill Institute for Neurosciences, UCSF at Zuckerberg San Francisco General (ZSFG), 1001 Potrero Avenue, 7M8, San Francisco, CA, 94110, USA
| | - Margaret A Handley
- UCSF Center for Vulnerable Populations at ZSFG, San Francisco, CA, USA.,UCSF Department of Medicine, Division of General Internal Medicine at ZSFG, 1001 Potrero Avenue, 1320A, San Francisco, CA, 94110, USA.,UCSF Department of Epidemiology and Biostatistics, 550 16th Street, San Francisco, CA, 64158, USA
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14
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Zomer E, Osborn D, Nazareth I, Blackburn R, Burton A, Hardoon S, Holt RIG, King M, Marston L, Morris S, Omar R, Petersen I, Walters K, Hunter RM. Effectiveness and cost-effectiveness of a cardiovascular risk prediction algorithm for people with severe mental illness (PRIMROSE). BMJ Open 2017; 7:e018181. [PMID: 28877952 PMCID: PMC5588956 DOI: 10.1136/bmjopen-2017-018181] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVES To determine the cost-effectiveness of two bespoke severe mental illness (SMI)-specific risk algorithms compared with standard risk algorithms for primary cardiovascular disease (CVD) prevention in those with SMI. SETTING Primary care setting in the UK. The analysis was from the National Health Service perspective. PARTICIPANTS 1000 individuals with SMI from The Health Improvement Network Database, aged 30-74 years and without existing CVD, populated the model. INTERVENTIONS Four cardiovascular risk algorithms were assessed: (1) general population lipid, (2) general population body mass index (BMI), (3) SMI-specific lipid and (4) SMI-specific BMI, compared against no algorithm. At baseline, each cardiovascular risk algorithm was applied and those considered high risk (> 10%) were assumed to be prescribed statin therapy while others received usual care. PRIMARY AND SECONDARY OUTCOME MEASURES Quality-adjusted life years (QALYs) and costs were accrued for each algorithm including no algorithm, and cost-effectiveness was calculated using the net monetary benefit (NMB) approach. Deterministic and probabilistic sensitivity analyses were performed to test assumptions made and uncertainty around parameter estimates. RESULTS The SMI-specific BMI algorithm had the highest NMB resulting in 15 additional QALYs and a cost saving of approximately £53 000 per 1000 patients with SMI over 10 years, followed by the general population lipid algorithm (13 additional QALYs and a cost saving of £46 000). CONCLUSIONS The general population lipid and SMI-specific BMI algorithms performed equally well. The ease and acceptability of use of an SMI-specific BMI algorithm (blood tests not required) makes it an attractive algorithm to implement in clinical settings.
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Affiliation(s)
- Ella Zomer
- Department of Epidemiology and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia
- Department of Primary Care and Population Health, Faculty of Population Health Sciences, University College London, London, UK
| | - David Osborn
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
- Camden and Islington National Health Service Foundation Trust, London, UK
| | - Irwin Nazareth
- Department of Primary Care and Population Health, Faculty of Population Health Sciences, University College London, London, UK
| | - Ruth Blackburn
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
| | - Alexandra Burton
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
| | - Sarah Hardoon
- Department of Primary Care and Population Health, Faculty of Population Health Sciences, University College London, London, UK
| | - Richard Ian Gregory Holt
- Human Development and Health Academic Unit, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Michael King
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
| | - Louise Marston
- Department of Primary Care and Population Health, Faculty of Population Health Sciences, University College London, London, UK
| | - Stephen Morris
- Department of Applied Health Research, Faculty of Population Health Sciences, University College London, London, UK
| | - Rumana Omar
- Department of Statistical Science, Faculty of Mathematical and Physical Sciences, University College London, London, UK
| | - Irene Petersen
- Department of Primary Care and Population Health, Faculty of Population Health Sciences, University College London, London, UK
| | - Kate Walters
- Department of Primary Care and Population Health, Faculty of Population Health Sciences, University College London, London, UK
| | - Rachael Maree Hunter
- Department of Primary Care and Population Health, Faculty of Population Health Sciences, University College London, London, UK
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