Variations in standardized hospital mortality rates for six common medical diagnoses - Implications for profiling hospital quality
Variations in standardized hospital mortality rates for six common medical diagnoses - Implications for profiling hospital quality
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DOI：
10.1097/00005650-199807000-00003
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发表时间：
1998-07-01
期刊：
影响因子：
3
通讯作者：
Harper, DL
中科院分区：
文献类型：
--
作者：
Rosenthal, GE;Shah, A;Harper, DL
目标.作者确定了六种常见医学诊断的标准化医院死亡率是否不同。这项回顾性队列研究纳入了1991年至1993年从大都市地区30家医院出院的89，851名18岁及以上患者，主要诊断为急性心肌梗死、充血性心力衰竭、肺炎、中风、阻塞性肺病或胃肠道出血。对于每家医院，使用基于从患者住院记录中提取的临床数据元素的经验证的风险调整模型确定标准化死亡率比（观察/预测死亡率）。根据标准化死亡率，医院也被分为五个等级。标准化死亡率之间的相关性和五分位数排名之间的一致性被确定为每对诊断。个体诊断的医院标准化死亡率之间的相关性一般较弱。对于15对可能的诊断，皮尔逊系数范围从-0.10到0.43;只有6个是0.30或更大。医院五分位数排名之间的一致性也普遍较低，加权Kappa值范围为-0.12至0.42。15个kappa值中有3个小于0（即一致性低于偶然性），只有4个超过0.20，即“公平”一致性的阈值。虽然模拟分析发现随机变化和相对较低的医院数量解释了诊断标准化死亡率的一些差异，但很大一部分差异仍然无法解释。标准化医院死亡率因六种可能由类似医生管理的诊断而异。虽然通过限制对大容量医院的分析可以减少变异性，但研究结果表明，对于许多医院来说，诊断特异性死亡率可能是衡量医院质量的不一致指标，即使数据是多年汇总的。
OBJECTIVES. The authors determined whether standardized hospital mortality rates varied for six common medical diagnoses.METHODS. The retrospective cohort study included 89,851 patients aged 18 years and older discharged from 30 hospitals in a large metropolitan area in 1991 to 1993 with a principal diagnosis of acute myocardial infarction, congestive heart failure, pneumonia, stroke, obstructive lung disease, or gastrointestinal hemorrhage. For each hospital, standardized mortality ratios (observed/predicted mortality) were determined using validated risk-adjustment models that were based on clinical data elements abstracted from patients' hospital records. Hospitals also were categorized into quintiles on the basis of standardized mortality ratios. Correlations between standardized mortality ratios and agreement between quintile rankings were determined for each pair of diagnoses.RESULTS. Correlations between hospital-standardized mortality ratios for individual diagnoses were generally weak. For the 15 possible pairs of diagnoses, Pearson coefficients ranged from -0.10 to 0.43; only six were 0.30 or greater. Agreement between hospital quintile rankings was also generally low, with weighted kappa values ranging from -0.12 to 0.42. Three of 15 kappa values were less than 0 (ie, agreement lower than chance), and only four exceeded 0.20, the threshold for "fair" agreement. Although simulated analyses found that random variation and relatively low hospital volumes accounted for some of the difference in standardized mortality ratios for diagnoses, a large proportion of the difference remained unexplained.CONCLUSIONS. Standardized hospital mortality rates varied for six diagnoses that likely are managed by similar practitioners. Although variability may be decreased by restricting analyses to hospitals with large volumes, the findings indicate that for many hospitals, diagnosis-specific mortality rates may be an inconsistent measure of hospital quality, even when data are aggregated for multiple years.