2011
DOI: 10.1378/chest.10-3011
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The Influence of Race/Ethnicity and Socioeconomic Status on End-of-Life Care in the ICU

Abstract: A growing body of evidence demonstrates the existence of important racial and ethnic differences in health care. Although many studies report on disparities in health care for acute and chronic conditions, 1-5 relatively few address racial disparities in the ICU, and those report confl icting fi ndings. Some have reported that black patients receive fewer medical interventions, 6,7 have shorter lengths of stay, and use fewer resources. 7 In contrast, others have found increased resource utilization, including … Show more

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Cited by 171 publications
(144 citation statements)
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References 57 publications
(63 reference statements)
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“…Preferences for end-of-life care may differ among socioeconomic and ethnic groups, thus limiting the generalizability of our study findings. 20,21 In conclusion, we found the rate of METimplemented DNR orders in the United States to be similar to that of previous reports in other countries. MET events involving a change in code status are associated with increased utilization of MET and ICU resources, but a shorter hospital length of stay.…”
Section: Discussionsupporting
confidence: 89%
“…Preferences for end-of-life care may differ among socioeconomic and ethnic groups, thus limiting the generalizability of our study findings. 20,21 In conclusion, we found the rate of METimplemented DNR orders in the United States to be similar to that of previous reports in other countries. MET events involving a change in code status are associated with increased utilization of MET and ICU resources, but a shorter hospital length of stay.…”
Section: Discussionsupporting
confidence: 89%
“…Demographic variables for patients included age, sex, race, cause of death (cancer, trauma, or other), insurance status (insured vs underinsured), 26 and education. Family member characteristics collected from family surveys included age, sex, race, and relationship to the patient (spouse/partner vs other relationship).…”
Section: Predictors and Covariatesmentioning
confidence: 99%
“…For the purposes of these analyses, we assess insurance as insured (private insurance, Medicare) and underinsured (Medicaid, no insurance) based on a prior validation of this approach. 25 For associations found to be signifi cant, we conducted sensitivity analyses in which we examined results of regression models across the four uncollapsed insurance categories. Patient race, education, and underlying cause of death were determined from the death certifi cate.…”
Section: Covariatesmentioning
confidence: 99%