作者
Anuj B. Mehta,Jennifer Taylor,G.L. Day,Trevor Lane,Ivor S. Douglas
摘要
Rationale: Disparities in patient selection for advanced therapeutics in health care have been identified in multiple studies, but it is unclear if disparities exist in patient selection for extracorporeal membrane oxygenation (ECMO), a rapidly expanding critical care resource. Objectives: To determine if disparities exist in patient selection for ECMO based on sex, primary insurance, and median income of the patient’s neighborhood. Methods: In a retrospective cohort study using the Nationwide Readmissions Database 2016–2019, we identified patients treated with mechanical ventilation (MV) and/or ECMO with billing codes. Patient sex, insurance, and income level for patients receiving ECMO were compared with the patients treated with MV only, and hierarchical logistic regression with the hospital as a random intercept was used to determine odds of receiving ECMO based on patient demographics. Results: We identified 2,170,752 MV hospitalizations with 18,725 cases of ECMO. Among patients treated with ECMO, 36.1% were female compared with 44.5% of patients treated with> MV only (adjusted odds ratio [aOR] for ECMO, 0.73; 95% confidence interval [CI], 0.70–0.75). Of patients treated with ECMO, 38.1% had private insurance compared with 17.4% of patients treated with MV only. Patients with Medicaid were less likely to receive ECMO than patients with private insurance (aOR, 0.55; 95% CI, 0.52–0.57). Patients treated with ECMO were more likely to live in the highest-income neighborhoods compared with patients treated with MV only (25.1% vs. 17.3%). Patients living in the lowest-income neighborhoods were less likely to receive ECMO than those living in the highest-income neighborhoods (aOR, 0.63; 95% CI, 0.60–0.67). Conclusions: Significant disparities exist in patient selection for ECMO. Female patients, patients with Medicaid, and patients living in the lowest-income neighborhoods are less likely to be treated with ECMO. Despite possible unmeasured confounding, these findings were robust to multiple sensitivity analyses. On the basis of previous work describing disparities in other areas of health care, we speculate that limited access in some neighborhoods, restrictive/biased interhospital transfer practices, differences in patient preferences, and implicit provider bias may contribute to the observed differences. Future studies with more granular data are needed to identify and modify drivers of observed disparities.