Associations Between Socioeconomic Status, Patient Risk, and Short-Term Intensive Care Outcomes. Issue 9 (29th April 2021)

• Record Type: Journal Article
• Authors: Mullany, Daniel V.; Pilcher, David V.; Dobson, Annette J.
• Is Part Of: Critical care medicine. Volume 49:Issue 9(2021)
• Page Start: e849
• Page End: e859
• Publication Date: 2021-04-29
• Subjects: epidemiology -- intensive care -- mortality -- risk adjustment -- socioeconomic status; Critical care medicine -- Periodicals; Soins intensifs -- Périodiques; 616.028
• DOI: 10.1097/CCM.0000000000005051
• Languages: English
• ISSNs: 0090-3493

Abstract

Abstract : Supplemental Digital Content is available in the text. Abstract : OBJECTIVES: To investigate the association of socioeconomic status as measured by the average socioeconomic status of the area where a person resides on short-term mortality in adults admitted to an ICU in Queensland, Australia. DESIGN: Secondary data analysis using de-identified data from the Australian and New Zealand Intensive Care Society Centre for Outcome and Resource Evaluation linked to the publicly available area-level Index of Relative Socioeconomic Advantage and Disadvantage from the Australian Bureau of Statistics. SETTING: Adult ICUs from 35 hospitals in Queensland, Australia, from 2006 to 2015. PATIENTS: A total of 218, 462 patient admissions. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The outcome measure was inhospital mortality. The main study variable was decile of Index of Relative Socioeconomic Advantage and Disadvantage. The overall crude inhospital mortality was 7.8%; 9% in the most disadvantaged decile and 6.9% in the most advantaged decile ( p < 0.001). Increasing socioeconomic disadvantage was associated with increasing severity of illness as measured by Acute Physiology and Chronic Health Evaluation III score, admission with a diagnosis of sepsis or trauma, cardiac, respiratory, renal, and hepatic comorbidities, and remote location. Increasing socioeconomic advantage was associated with elective surgical admission, hematological and oncology comorbidities, and admission to a private hospital (all p < 0.001). After excluding patients admitted after elective surgery, in the remaining 106, 843 patients, the inhospital mortality was 13.6%, 13.3% in the most disadvantaged, and 14.1% in the most advantaged. There was no trend in mortality across deciles of socioeconomic status after excluding elective surgery patients. In the logistic regression model adjusting for severity of illness and diagnosis, there was no statistically significant difference in the odds ratio of inhospital mortality for the most disadvantaged decile compared with other deciles. This suggests variables used for risk adjustment may lie on the causal pathway between socioeconomic status and outcome in ICU patients. CONCLUSIONS: Socioeconomic status as defined as Index of Relative Socioeconomic Advantage and Disadvantage of the area in which a patient lives was associated with ICU admission diagnosis, comorbidities, severity of illness, and crude inhospital mortality in this study. Socioeconomic status was not associated with inhospital mortality after excluding elective surgical patients or when adjusted for severity of illness and admission diagnosis. Commonly used measures for risk adjustment in intensive care improve understanding of the pathway between socioeconomic status and outcomes.