ScHARR, University of Sheffield, Sheffield S1 4DA, UK.
BMJ. 2012 Mar 1;344:e1001. doi: 10.1136/bmj.e1001.
To develop a transparent and reproducible measure for hospitals that can indicate when deaths in hospital or within 30 days of discharge are high relative to other hospitals, given the characteristics of the patients in that hospital, and to investigate those factors that have the greatest effect in changing the rank of a hospital, whether interactions exist between those factors, and the stability of the measure over time.
Retrospective cross sectional study of admissions to English hospitals.
Hospital episode statistics for England from 1 April 2005 to 30 September 2010, with linked mortality data from the Office for National Statistics.
36.5 million completed hospital admissions in 146 general and 72 specialist trusts.
Deaths within hospital or within 30 days of discharge from hospital.
The predictors that were used in the final model comprised admission diagnosis, age, sex, type of admission, and comorbidity. The percentage of people admitted who died in hospital or within 30 days of discharge was 4.2% for males and 4.5% for females. Emergency admissions comprised 75% of all admissions and 5.5% died, in contrast to 0.8% who died after an elective admission. The percentage who died with a Charlson comorbidity score of 0 was 2% in contrast with 15% who died with a score greater than 5. Given these variables, the relative standardised mortality rates of the hospitals were not noticeably changed by adjusting for the area level deprivation and number of previous emergency visits to hospital. There was little evidence that including interaction terms changed the relative values by any great amount. Using these predictors the summary hospital mortality index (SHMI) was derived. For 2007/8 the model had a C statistic of 0.911 and accounted for 81% of the variability of between hospital mortality. A random effects funnel plot was used to identify outlying hospitals. The outliers from the SHMI over the period 2005-10 have previously been identified using other mortality indicators.
The SHMI is a relatively simple tool that can be used in conjunction with other information to identify hospitals that may need further investigation.
开发一种针对医院的透明且可重现的衡量标准，该标准可根据医院患者的特征，在医院内或出院后 30 天内的死亡人数相对于其他医院的死亡人数进行衡量，并研究那些对医院排名影响最大的因素，以及这些因素之间是否存在相互作用，以及该衡量标准随时间的稳定性。
对 2005 年 4 月 1 日至 2010 年 9 月 30 日期间英格兰医院入院情况的回顾性横断面研究。
英格兰医院入院病例统计数据，与国家统计局的死亡数据相关联。
146 家综合医院和 72 家专科医院共 3650 万例完成的住院治疗。
住院期间或出院后 30 天内的死亡情况。
最终模型中使用的预测因子包括入院诊断、年龄、性别、入院类型和合并症。男性住院或出院后 30 天内死亡的比例为 4.2%，女性为 4.5%。急诊入院占所有入院的 75%，5.5%死亡，而择期入院的死亡率为 0.8%。Charlson 合并症评分为 0 的患者死亡率为 2%，而评分为>5 的患者死亡率为 15%。在考虑这些变量的情况下，通过调整地区贫困程度和以往急诊就诊次数，医院的相对标准化死亡率并没有明显改变。几乎没有证据表明，通过引入交互项，医院的相对值会有很大的变化。使用这些预测因子，得出了医院死亡率综合指数（SHMI）。2007/8 年，该模型的 C 统计量为 0.911，解释了医院间死亡率差异的 81%。使用随机效应漏斗图来识别异常医院。2005-10 年期间，SHMI 的异常值已经使用其他死亡率指标进行了识别。
SHMI 是一种相对简单的工具，可以与其他信息一起使用，以识别可能需要进一步调查的医院。
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