Tips for calculating and displaying risk-standardized hospital outcomes in Stata

被引：18
|
作者：
Lenzi, Jacopo [1 ]
Pildava, Santa [2 ]
机构：
[1] Alma Mater Studiorum Univ Bologna, Dept Biomed & Neuromotor Sci, Bologna, Italy
[2] Ctr Dis Prevent & Control Latvia, Res & Hlth Stat Dept, Riga, Latvia
来源：
STATA JOURNAL | 2019年 / 19卷 / 02期
关键词：
st0562; risk adjustment; bootstrap; caterpillar plot; eclplot; funnel plot; generalized estimating equations; healthcare quality assessment; hospital profiling; mfpboot; mfpboot_bif; multivariable modeling; outcomes research; qic; risk-standardized mortality rates; stability; xtgee; GENERALIZED ESTIMATING EQUATIONS; DESIGN;
D O I：
10.1177/1536867X19854021
中图分类号：
O1 [数学]; C [社会科学总论];
学科分类号：
03 ; 0303 ; 0701 ; 070101 ;
摘要：
A major challenge of outcomes research is measuring hospital performance using readily available administrative data. When the outcome measure is mortality or morbidity, rates are adjusted to account for preexisting conditions that may confound their assessment. However, the concept of risk-adjusted outcomes is frequently misunderstood. In this article, we try to clarify things, and we describe Stata tools for appropriately calculating and displaying risk-standardized outcome measures. We offer practical guidance and illustrate the application of these tools to an example based on real data (30-day mortality following acute myocardial infarction in Latvia).
引用
收藏
页码：477 / 496
页数：20
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