Söderlund N, Milne R, Gray A, Raftery J
Department of Public Health and Primary Care, University of Oxford.
J Public Health Med. 1995 Mar;17(1):25-32.
The aim of the study was to examine the relationship between hospital costs and casemix, and after adjustment for casemix differences, between cost and institutional size, number of specialties, occupancy and teaching status.
A retrospective analysis of all admissions to nine acute-care NHS hospitals in the Oxford region during the 1991-1992 financial year was undertaken. All episodes were assigned to a diagnosis-related group (DRG) and a cost weight assigned accordingly. Costs per finished consultant episode, before and after adjustment for casemix differences, were analysed at the hospital and specialty level.
Casemix differences were significant, and accounted for approximately 77 per cent of the difference in costs between providers. Costs per casemix-adjusted episode were not significantly associated with differences in hospital size, scope, occupancy levels or teaching status, but sample size was insufficient to investigate these relationships adequately. Specialty costs were poorly correlated with specialty casemix. This was probably due to poor apportionment of specialty costs in hospital accounting returns.
Casemix differences need to be taken into account when comparing providers for the purposes of contracting, as unadjusted unit costs may be misleading. Although the methods used may currently be applied to most NHS hospitals, widespread use would be greatly facilitated by the development of indigenous cost weights and better routine hospital data coding and collection.
本研究旨在探讨医院成本与病例组合之间的关系，以及在调整病例组合差异后，成本与机构规模、专科数量、床位占用率和教学状况之间的关系。
对牛津地区9家国民健康服务体系（NHS）急症医院1991 - 1992财政年度的所有入院病例进行回顾性分析。所有病例均被分配到一个诊断相关组（DRG），并据此分配成本权重。在医院和专科层面分析了调整病例组合差异前后每个完成的顾问病例的成本。
病例组合差异显著，约占提供者之间成本差异的77%。调整病例组合后的每个病例成本与医院规模、范围、床位占用水平或教学状况的差异无显著关联，但样本量不足以充分研究这些关系。专科成本与专科病例组合的相关性较差。这可能是由于医院会计报表中专科成本分摊不当所致。
在为合同目的比较提供者时，需要考虑病例组合差异，因为未经调整的单位成本可能会产生误导。尽管目前使用的方法可能适用于大多数NHS医院，但本地成本权重的开发以及更好的常规医院数据编码和收集将极大地促进其广泛应用。
