SOCIAL AND ECONOMIC PREDICTORS FOR THE COURSE AND PROGNOSIS OF THE SEVERE MENTAL DISORDERS- THE SEP-MD DATA LINKAGE STUDY

尽管对包括精神分裂症在内的严重精神疾病(SMI)的研究已有30多年的历史，但围绕哪些因素最能有力地预测这些疾病的进程和结果，仍存在核心的挑战性问题。与普通人群相比，患有SMI的人的预期寿命减少了11到17岁，住院精神病住院的可能性增加，就业水平更低。与患有SMI的英国白人服务用户相比，患有SMI的少数族裔群体可能会经历更大的不平等-强制入院和社会排斥的比率更高。以前的国际工作表明，SMI的过程可能会随着环境的变化而表现出强烈的差异，然而，关于社会/环境因素是否可能改变SMI的过程进行的研究有限，研究的结论来自于受影响的人失去跟踪、样本量太小以及参与的少数族裔背景太少，以便能够得出可靠的结论。随着时间的推移，跟踪患有SMI的人的传统研究是耗时、昂贵的，并且在后勤方面具有挑战性，因为随着时间的推移追踪人是困难的。该项目将通过将英国人口普查数据与欧洲最大的二级精神卫生保健提供者之一的电子临床记录联系起来，解决这些重要问题。这是一种创新的数据链接，因为英国人口普查每十年进行一次，收集有关重要社会指标的详细信息(例如，与家庭贫困、社会隔离、移民状况、就业和长期失业有关)，而健康记录中通常不会有这些详细信息。临床记录将来自一家主要的英国精神健康信托基金-南伦敦和莫斯利信托基金，该基金为伦敦一个种族多元化、地理定义明确的城市地区提供近乎垄断的二级精神卫生保健，覆盖约120万人。通过这一联系，我们将创建一个至少在8年内跟踪调查的19,800名严重精神疾病患者的队列，我们将能够评估家庭贫困、社会隔离、种族和移民状况等社会因素以及诊断、处方和疾病严重程度等临床因素与我们的主要结果-死亡率、住院(强制性和自愿)和长期失业-的关联。我们将致力于评估人们居住的地方的特征(例如，生活在社会分散的社区或更贫穷的地区的影响)以及个人层面的特征(例如，社会孤立、生活在贫困中、烟草使用、处方、诊断和疾病严重程度)，以及这些特征与SMI患者的死亡风险之间的关系。这种联系还将使我们能够评估社会和临床因素与住院精神疾病入院(包括根据英国《精神健康法》强制拘留)的关联。最后，这种联系将使我们能够评估临床和社会因素，预测长期失业，定义为失业一年以上和/或从未就业，在患有SMI的样本中。我们的分析将评估所有这些关联与种族和移民状况的相互作用。通过我们的研究，我们还将考虑患有严重精神疾病的人是否经历了极端的健康不平等。我们已经与我们的非学术合作伙伴Black Thrive和Synergi协作中心一起开发了研究问题，并打算将研究结果直接提供给公共政策、服务开发和当前关于严重精神疾病患者所经历的不平等的研究和论述。

Despite more than thirty years of studies into the severe mental illnesses (SMI), including schizophrenia; central challenging questions remain around which factors most strongly predict course and outcomes of these conditions. People with SMI experience an 11 to 17 year reduction in life expectancy, an increased possibility of in-patient psychiatric admissions, and lower levels of employment, compared to the general population. Ethnic minority groups with SMI may experience even greater inequalities- with higher rates of compulsory admissions and social exclusion, compared to White British service users with SMI. Previous international work has suggested that the course of SMI may show strong variation with the environment, yet there has only been limited research conducted on whether social/ environmental factors potentially modify the course of SMI, with conclusions from studies affected by people being lost to follow up, sample sizes being too small, and with too few people of an ethnic minority background taking part, in order to enable robust conclusions. Traditional studies which follow people with SMI over time are time-intensive, expensive to run and logistically challenging to conduct, as tracing people over time is difficult. This project will address these important issues by linking UK Census data with the electronic clinical records from one of the largest secondary mental healthcare providers in Europe. This is an innovative data linkage as UK census is conducted every ten years and collects detailed information around important social indicators (for example, relating to household poverty, social isolation, migration status, employment and long-term worklessness) which are not usually available in good detail in health records. The clinical records will come from a major UK Mental Health Trust- South London & Maudsley Trust, which provides near-monopoly secondary mental healthcare to an ethnically-diverse, geographically defined urban area in London, with a catchment of approximately 1.2 million people.Through the linkage we will create a cohort of 19,800 people with severe mental illnesses followed over a minimum of eight years and we will be able to assess the association of social factors such as household poverty, social isolation, ethnicity and migration status, alongside clinical factors such as diagnosis, prescriptions and severity of illness with our main outcomes- mortality, in-patient admissions (compulsory and voluntary) and long-term worklessness. We will aim to assess the characteristics of where people live (for example the effect of living in socially fragmented neighbourhoods or more deprived areas) alongside person-level level characteristics (e.g. being socially isolated, living in poverty, tobacco use, prescriptions, diagnosis and illness severity) and how these are associated with mortality risks in people with SMI. The linkage will also enable us to assess the association of social and clinical factors with in-patient psychiatric admissions (including compulsory detentions under the UK Mental Health Act). Finally the linkage will allow us to assess clinical and social factors predicting long-term worklessness, defined as being unemployed for more than a year and/ or never holding employment, in a sample of people with SMI. Our analyses will assess the interplay of all of these associations with ethnicity and migration status. Through our study we will also consider whether people with severe mental illnesses who are multiply disadvantaged- i.e.disadvantaged across a range of indicators, experience extreme health inequalities. We have developed the research questions with our non-Academic partners, Black Thrive and the Synergi Collaborative Centre, and will intend for the findings to directly inform public policy, service development and current research and discourses regarding the inequalities experienced by people living with severe mental illnesses.