Background: Mental health rehabilitation services provide specialist treatment to people with particularly severe and complex problems. In 2018, the Care Quality Commission reported that over half the 4,400 mental health inpatient rehabilitation beds in England were provided by the independent sector. They raised concerns that the length of stay and cost of independent sector care was double that of the NHS and that their services tended to be provided much further from people's homes. However, there has been no research comparing the two sectors and we therefore do not know if these concerns are justified. The ACER Study (Assessing the Clinical and cost-Effectiveness of inpatient mental health Rehabilitation services provided by the NHS and independent sector) is a national programme of research in England, funded from 2021 to 2026, that aims to investigate differences in inpatient mental health rehabilitation provided by the NHS and independent sector in terms of: patient characteristics; service quality; patient, carer and staff experiences; clinical and cost effectiveness.
Methods: ACER comprises a:1) detailed survey of NHS and independent sector inpatient mental health rehabilitation services across England; 2) qualitative investigation of patient, family, staff and commissioners' experiences of the two sectors; 3) cohort study comparing clinical outcomes in the two sectors over 18 months; 4) comprehensive national comparison of inpatient service use in the two sectors, using instrumental variable analysis of routinely collected healthcare data over 18 months; 5) health economic evaluation of the relative cost-effectiveness of the two sectors. In Components 3 and 4, our primary outcome is 'successful rehabilitation' defined as a) being discharged from the inpatient rehabilitation unit without readmission and b) inpatient service use over the 18 months.
Discussion: The ACER study will deliver the first empirical comparison of the clinical and cost-effectiveness of NHS and independent sector inpatient mental health rehabilitation services.
Trial Registration: ISRCTN17381762 retrospectively registered.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10848497 | PMC |
| http://dx.doi.org/10.1186/s12888-024-05524-6 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
External delay and dispersion correction of automatically sampled arterial blood with dual flow rates.
Biomed Phys Eng Express
January 2025
Brain Health Imaging Centre, Centre for Addiction and Mental Health, B68-250 College St, Toronto, Ontario, M5T 1R8, CANADA.
Objective: Arterial sampling for PET imaging often involves continuously measuring the radiotracer activity concentration in blood using an automatic blood sampling system (ABSS). We proposed and validated an external delay and dispersion correction procedure needed when a change in flow rate occurs during data acquisition. We also measured the external dispersion constant of [11C]CURB, [18F]FDG, [18F]FEPPA, and [18F]SynVesT-1.
View Article and Find Full Text PDFMapping the regional and remote specialised mental health workforce: Commentary on the AIHW data for 2022-2023.
Australas Psychiatry
January 2025
Consortium of Australian-Academic Psychiatrists for Independent Policy and Research Analysis (CAPIPRA), Canberra, ACT, Australia.
Objective: The Australian Institute of Health and Welfare publishes statistical indicator reports on the specialised mental health workforce. These include data for 2022-2023 on psychiatrists, mental health nurses, mental health occupational therapists, psychologists and mental health social workers. We provide a brief commentary on these reports, reflecting upon the implications of such changes for psychiatric practice and patient care.
View Article and Find Full Text PDFParental Mental Health and Child Maltreatment in the COVID-19 Pandemic: Importance of Sampling in a Quantitative Statistical Study.
J Med Internet Res
January 2025
Clinical Psychology and Psychotherapy, Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany.
Background: Results on parental burden during the COVID-19 pandemic are predominantly available from nonrepresentative samples. Although sample selection can significantly influence results, the effects of sampling strategies have been largely underexplored.
Objective: This study aimed to investigate how sampling strategy may impact study results.
Effectiveness of Digital Mental Health Interventions in the Workplace: Umbrella Review of Systematic Reviews.
JMIR Ment Health
January 2025
Inspire, Belfast, United Kingdom.
Background: There is potential for digital mental health interventions to provide affordable, efficient, and scalable support to individuals. Digital interventions, including cognitive behavioral therapy, stress management, and mindfulness programs, have shown promise when applied in workplace settings.
Objective: The aim of this study is to conduct an umbrella review of systematic reviews in order to critically evaluate, synthesize, and summarize evidence of various digital mental health interventions available within a workplace setting.
The Use of AI in Mental Health Services to Support Decision-Making: Scoping Review.
J Med Internet Res
January 2025
School of Business, Innovation and Sustainability, Halmstad University, Halmstad, Sweden.
Background: Recent advancements in artificial intelligence (AI) have changed the care processes in mental health, particularly in decision-making support for health care professionals and individuals with mental health problems. AI systems provide support in several domains of mental health, including early detection, diagnostics, treatment, and self-care. The use of AI systems in care flows faces several challenges in relation to decision-making support, stemming from technology, end-user, and organizational perspectives with the AI disruption of care processes.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!