Christensen Steffen, Jacobsen Jacob, Bartels Paul, Nørgaard Mette
Klinisk Epidemiologisk Afdeling, Arhus Sygehus, DK-8000 Arhus C.
Ugeskr Laeger. 2007 Aug 20;169(34):2767-72.
Hospital standardised mortality ratios (HSMR) are widely used in quality improvement campaigns. No data exist on whether HSMR can be computed based on Danish administrative registries. We therefore used data from Danish registries to compute HSMRs.
By linking hospital discharge registries with the Danish Civil Registration System, we identified 77 primary discharge diagnoses that accounted for 80% of all deaths within 30 days of admission. We calculated overall death rates stratified by the 77 primary discharge diagnoses, age, gender, and type of admission and used these to compute the expected number of deaths. HSMR for each hospital was calculated as the ratio of observed to expected number of deaths.
Pneumonia, non-specified was the diagnosis that accounted for most deaths within 30 days after admission. The crude mortality rate varied from 5.7% to 6.3%. HSMR varied little--from 95 and 98 in Hospitals B and D to 102 and 103 in Hospitals A and C, respectively.
We found that it was possible to use data from Danish administrative registries to compute HSMR and that HSMR varied little between hospitals with comparable case-mixes.
医院标准化死亡率（HSMR）在质量改进活动中被广泛应用。目前尚无关于能否基于丹麦行政登记数据计算HSMR的相关数据。因此，我们利用丹麦登记处的数据来计算HSMR。
通过将医院出院登记数据与丹麦民事登记系统相链接，我们确定了77种主要出院诊断，这些诊断占入院后30天内所有死亡病例的80%。我们计算了按77种主要出院诊断、年龄、性别和入院类型分层的总体死亡率，并以此计算预期死亡人数。每家医院的HSMR计算为观察到的死亡人数与预期死亡人数之比。
未明确的肺炎是入院后30天内导致死亡最多的诊断。粗死亡率在5.7%至6.3%之间变化。HSMR变化不大——B医院和D医院分别为95和98，A医院和C医院分别为102和103。
我们发现利用丹麦行政登记数据计算HSMR是可行的，并且在病例组合相当的医院之间HSMR变化不大。
