Weich Scott, McBride Orla, Twigg Liz, Duncan Craig, Keown Patrick, Crepaz-Keay David, Cyhlarova Eva, Parsons Helen, Scott Jan, Bhui Kamaldeep
School of Health and Related Research, University of Sheffield, Sheffield, UK.
School of Psychology, Ulster University, County Londonderry, Ulster, UK.
Lancet Psychiatry. 2017 Aug;4(8):619-626. doi: 10.1016/S2215-0366(17)30207-9. Epub 2017 Jun 21.
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.
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.
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.
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.
National Institute for Health Research Health Services and Delivery Research Programme.
在英格兰,强制收治到精神科住院床位的比例不断上升,令人担忧。研究不同地区和服务之间的差异可能是确定干预目标以扭转这一趋势的关键。我们利用全国患者层面的数据对英格兰强制收治的空间差异进行建模,并量化了患者、当地地区和服务环境特征对这种差异的影响程度。
本研究是对2010 - 2011年精神健康最低数据集(MHMDS)进行的横断面多层次分析。来自8个提供方信托的数据被排除,包括3个缺乏空间识别码的独立提供方信托。我们排除了仅依据《精神健康法》相关条款被拘留,仅涉及转送至或在注册安全场所进行评估,或仅进行短期(≤72小时)评估的患者,因为这些情况本身并不一定意味着该患者会被收治到精神科住院床位。MHMDS包含了关于有限数量患者特征(即年龄、性别和种族)的较为完整的数据;然而,由于大量数据缺失,我们的分析中无法纳入几个患者层面的变量。使用MLwiN软件应用多层次模型来估计强制收治的差异,首先从空模型(无条件模型)开始,该模型将强制收治的总方差在模型的每个层面进行划分。主要结局是与自愿入院或仅接受社区护理的患者相比,强制收治到精神科住院床位。
有1238188名患者的数据可用,涵盖64个国民保健服务提供方信托(93%)和31865个人口普查低级别超级输出区(LSOA;98%)。在调整患者特征后,强制收治差异的7.5%和5.6%分别出现在LSOA层面和提供方信托层面。黑人患者被强制收治的可能性几乎是白人患者的三倍(优势比[OR]2.94,95%置信区间2.90 - 2.98)。在调整混杂因素后,在更贫困地区(OR 1.22,1.18 - 1.27)和非白人居民较多的地区(OR 1.51,1.43 - 1.59),强制收治情况更为严重。
精神科住院床位的强制收治率在不同地区和服务之间存在显著差异,与患者、地区和服务特征无关。强制收治率似乎反映了当地因素,尤其是社会经济和种族人口构成。了解这些因素如何影响获得和使用精神卫生保健,对于制定减少强制收治的干预措施可能很重要。
国家卫生研究院卫生服务与交付研究项目。