Glover G R, Robin E, Emami J, Arabscheibani G R
PRiSM Unit, Institute of Psychiatry, London, UK.
Soc Psychiatry Psychiatr Epidemiol. 1998 Feb;33(2):89-96. doi: 10.1007/s001270050027.
The study aimed to develop a mental illness needs index to help local managers, district purchasers and national policy makers in allocating resources. Formulae were developed by regression analysis using 1991 census data to predict the period prevalence of acute psychiatric admission from electoral wards. Census variables used were chosen on the basis of an established association with mental illness rates. Data from one English Health Service region were analysed for patterns common to wards at hospital catchment area level and patterns common to district health authorities at regional level. The North East Thames region was chosen as the setting for the study, with 7096 patients being admitted during 1991. In most, but not all, catchment areas reasonable prediction of the pattern of admission prevalence was possible using the variables chosen. However, different population characteristics predicted admission prevalence in rural and urban areas. Prediction methods based on one or two variables are thus unlikely to work in both settings. A Mental Illness Needs Index (MINI) based on social isolation, poverty, unemployment, permanent sickness and temporary and insecure housing predicted differences in admission prevalence between wards at catchment area level better than Jarman's Underprivileged Area (UPA) score [1] and between districts at regional level better than the UPA score and comparably to the York Psychiatric Index [2] (adjusted r2 at regional level (MINI 0.82, UPA 0.53, York index 0.70). District admission prevalence rates vary by a factor of three between rural and inner city areas; this difference may not fully reflect the variation in the cost of providing care. It did not prove possible to incorporate factors related to bed availability in the models used; reasons for this are discussed. Data covering other aspects of mental health care in addition to hospital admission are needed for more satisfactory modelling.
该研究旨在制定一个精神疾病需求指数，以帮助地方管理人员、地区采购者和国家政策制定者进行资源分配。通过回归分析，利用1991年人口普查数据制定公式，以预测选区急性精神科住院的期间患病率。所使用的人口普查变量是根据与精神疾病发病率的既定关联来选择的。对来自一个英国卫生服务地区的数据进行了分析，以找出医院集水区层面各病房共有的模式以及地区层面各地区卫生当局共有的模式。选择泰晤士河北部地区作为研究地点，1991年期间有7096名患者入院。在大多数（但不是所有）集水区，使用所选变量可以合理预测住院患病率模式。然而，不同的人口特征预测了农村和城市地区的住院患病率。因此，基于一两个变量的预测方法在这两种情况下都不太可能有效。基于社会隔离、贫困、失业、长期疾病以及临时和不安全住房的精神疾病需求指数（MINI）在预测集水区层面各病房之间的住院患病率差异方面，比贾曼的贫困地区（UPA）得分[1]表现更好；在预测地区层面各地区之间的差异方面，比UPA得分表现更好，与约克精神病指数[2]相当（地区层面调整后的r2（MINI为0.82，UPA为0.53，约克指数为0.70）。农村和市中心地区之间的地区住院患病率相差三倍；这种差异可能无法完全反映提供护理的成本差异。在所使用的模型中，纳入与床位可用性相关的因素被证明是不可能的；对此进行了讨论。为了进行更令人满意的建模，除了住院情况外，还需要涵盖精神卫生保健其他方面的数据。
