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

Jacopo Lenzi () and Santa Pildava ()
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Jacopo Lenzi: Alma Mater Studiorum–University of Bologna
Santa Pildava: Centre for Disease Prevention and Control of Latvia

Stata Journal, 2019, vol. 19, issue 2, 477-496

Abstract: A major challenge of outcomes research is measuring hospital perfor-mance 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).

Keywords: risk adjustment; bootstrap; caterpillar plot; eclplot; funnel plot; generalized estimating equations; healthcare quality assessment; hospital profil- ing; mfpboot; mfpboot bif; multivariable modeling; outcomes research; qic; risk-standardized mortality rates; stability; xtgee (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:tsj:stataj:v:19:y:2019:i:2:p:477-496

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DOI: 10.1177/1536867X19854021

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