Scott Weich1, Orla McBride2, Liz Twigg3, Craig Duncan3, Patrick Keown4, David Crepaz-Keay5, Eva Cyhlarova6, Helen Parsons7, Jan Scott4, Kamaldeep Bhui8. 1. School of Health and Related Research, University of Sheffield, Sheffield, UK. Electronic address: s.weich@sheffield.ac.uk. 2. School of Psychology, Ulster University, County Londonderry, Ulster, UK. 3. Department of Geography, University of Portsmouth, Buckingham Building, Portsmouth, UK. 4. Newcastle University, Academic Psychiatry Campus for Ageing & Vitality, Newcastle upon Tyne, UK. 5. Mental Health Foundation, London, UK. 6. London School of Economics and Political Science, London, UK. 7. Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK. 8. Centre for Psychiatry, Barts and The London School of Medicine & Dentistry, Queen Mary University of London, London, UK.
Abstract
BACKGROUND: The increasing rate of compulsory admission to psychiatric inpatient beds in England is worrying. Studying variation between places and services could be key to identifying targets for interventions to reverse this trend. We modelled spatial variation in compulsory admissions in England using national patient-level data and quantified the extent to which patient, local-area, and service-setting characteristics accounted for this variation. METHODS: This study is a cross-sectional, multilevel analysis of the 2010-11 Mental Health Minimum Data Set (MHMDS). Data from eight provider trusts were excluded, including three independent provider trusts that lacked spatial identification codes. We excluded patients detained under sections of the Mental Health Act concerned only with conveyance to, or assessment in, a registered Place of Safety, or for short-term (≤72 h) assessment only, as these do not in themselves necessarily mean that the person will be admitted to an inpatient mental health bed. MHMDS contained reasonably complete data for a limited number of patient characteristics, namely age, sex, and ethnicity; however, several patient-level variables could not be included in our analysis because of high levels of missing data. Multilevel models were applied with MLwiN to estimate variation in compulsory admission, starting with null (unconditional) models that partitioned total variance in compulsory admission between each level in the model. The primary outcome was compulsory admission to a psychiatric inpatient bed, compared with people admitted voluntarily or receiving only community-based care. FINDINGS: Data were available for 1 238 188 patients, covering 64 National Health Service provider trusts (93%) and 31 865 census lower super output areas (LSOAs; 98%). 7·5% and 5·6% of the variance in compulsory admission occurred at LSOA level and provider trust levels, respectively, after adjusting for patient characteristics. Black patients were almost three times more likely to be admitted compulsorily than were white patients (odds ratio [OR] 2·94, 95% CI 2·90-2·98). Compulsory admission was greater in more deprived areas (OR 1·22, 1·18-1·27) and in areas with more non-white residents (OR 1·51, 1·43-1·59), after adjusting for confounders. INTERPRETATION: Rates of compulsory admission to inpatient psychiatric beds vary significantly between local areas and services, independent of patient, area, and service characteristics. Compulsory admission rates seem to reflect local factors, especially socioeconomic and ethnic population composition. Understanding how these factors condition access to, and use of, mental health care is likely to be important for developing interventions to reduce compulsion. FUNDING: National Institute for Health Research Health Services and Delivery Research Programme.
BACKGROUND: The increasing rate of compulsory admission to psychiatric inpatient beds in England is worrying. Studying variation between places and services could be key to identifying targets for interventions to reverse this trend. We modelled spatial variation in compulsory admissions in England using national patient-level data and quantified the extent to which patient, local-area, and service-setting characteristics accounted for this variation. METHODS: This study is a cross-sectional, multilevel analysis of the 2010-11 Mental Health Minimum Data Set (MHMDS). Data from eight provider trusts were excluded, including three independent provider trusts that lacked spatial identification codes. We excluded patients detained under sections of the Mental Health Act concerned only with conveyance to, or assessment in, a registered Place of Safety, or for short-term (≤72 h) assessment only, as these do not in themselves necessarily mean that the person will be admitted to an inpatient mental health bed. MHMDS contained reasonably complete data for a limited number of patient characteristics, namely age, sex, and ethnicity; however, several patient-level variables could not be included in our analysis because of high levels of missing data. Multilevel models were applied with MLwiN to estimate variation in compulsory admission, starting with null (unconditional) models that partitioned total variance in compulsory admission between each level in the model. The primary outcome was compulsory admission to a psychiatric inpatient bed, compared with people admitted voluntarily or receiving only community-based care. FINDINGS: Data were available for 1 238 188 patients, covering 64 National Health Service provider trusts (93%) and 31 865 census lower super output areas (LSOAs; 98%). 7·5% and 5·6% of the variance in compulsory admission occurred at LSOA level and provider trust levels, respectively, after adjusting for patient characteristics. Black patients were almost three times more likely to be admitted compulsorily than were white patients (odds ratio [OR] 2·94, 95% CI 2·90-2·98). Compulsory admission was greater in more deprived areas (OR 1·22, 1·18-1·27) and in areas with more non-white residents (OR 1·51, 1·43-1·59), after adjusting for confounders. INTERPRETATION: Rates of compulsory admission to inpatient psychiatric beds vary significantly between local areas and services, independent of patient, area, and service characteristics. Compulsory admission rates seem to reflect local factors, especially socioeconomic and ethnic population composition. Understanding how these factors condition access to, and use of, mental health care is likely to be important for developing interventions to reduce compulsion. FUNDING: National Institute for Health Research Health Services and Delivery Research Programme.
Authors: Sönke Johann Peters; Mario Schmitz-Buhl; Olaf Karasch; Jürgen Zielasek; Euphrosyne Gouzoulis-Mayfrank Journal: BMC Psychiatry Date: 2022-07-14 Impact factor: 4.144
Authors: Kristoffer Halvorsrud; James Nazroo; Michaela Otis; Eva Brown Hajdukova; Kamaldeep Bhui Journal: BMC Med Date: 2018-12-12 Impact factor: 8.775
Authors: Scott Weich; Craig Duncan; Kamaldeep Bhui; Alastair Canaway; David Crepaz-Keay; Patrick Keown; Jason Madan; Orla McBride; Graham Moon; Helen Parsons; Swaran Singh; Liz Twigg Journal: BMJ Open Date: 2018-10-18 Impact factor: 2.692