Disparities in Adult Patient Selection for Extracorporeal Membrane Oxygenation in the United States: A Population-Level Study

Insurance-based Disparities in Outcomes and Extracorporeal Membrane Oxygenation Utilization for Hospitalized COVID-19 Patients

BACKGROUND

The objective of this study was to examine insurance-based disparities in mortality, nonhome discharges, and extracorporeal membrane oxygenation utilization in patients hospitalized with COVID-19.

METHODS

Using a national database of U.S. academic medical centers and their affiliated hospitals, the risk-adjusted association between mortality, nonhome discharge, and extracorporeal membrane oxygenation utilization and (1) the type of insurance coverage (private insurance, Medicare, dual enrollment in Medicare and Medicaid, and no insurance) and (2) the weekly hospital COVID-19 burden (0 to 5.0%; 5.1 to 10%, 10.1 to 20%, 20.1 to 30%, and 30.1% and greater) was evaluated. Modeling was expanded to include an interaction between payer status and the weekly hospital COVID-19 burden to examine whether the lack of private insurance was associated with increases in disparities as the COVID-19 burden increased.

RESULTS

Among 760,846 patients hospitalized with COVID-19, 214,992 had private insurance, 318,624 had Medicare, 96,192 were dually enrolled in Medicare and Medicaid, 107,548 had Medicaid, and 23,560 had no insurance. Overall, 76,250 died, 211,702 had nonhome discharges, 75,703 were mechanically ventilated, and 2,642 underwent extracorporeal membrane oxygenation. The adjusted odds of death were higher in patients with Medicare (adjusted odds ratio, 1.28 [95% CI, 1.21 to 1.35]; P < 0.0005), dually enrolled (adjusted odds ratio, 1.39 [95% CI, 1.30 to 1.50]; P < 0.0005), Medicaid (adjusted odds ratio, 1.28 [95% CI, 1.20 to 1.36]; P < 0.0005), and no insurance (adjusted odds ratio, 1.43 [95% CI, 1.26 to 1.62]; P < 0.0005) compared to patients with private insurance. Patients with Medicare (adjusted odds ratio, 0.47; [95% CI, 0.39 to 0.58]; P < 0.0005), dually enrolled (adjusted odds ratio, 0.32 [95% CI, 0.24 to 0.43]; P < 0.0005), Medicaid (adjusted odds ratio, 0.70 [95% CI, 0.62 to 0.79]; P < 0.0005), and no insurance (adjusted odds ratio, 0.40 [95% CI, 0.29 to 0.56]; P < 0.001) were less likely to be placed on extracorporeal membrane oxygenation than patients with private insurance. Mortality, nonhome discharges, and extracorporeal membrane oxygenation utilization did not change significantly more in patients with private insurance compared to patients without private insurance as the COVID-19 burden increased.

CONCLUSIONS

Among patients with COVID-19, insurance-based disparities in mortality, nonhome discharges, and extracorporeal membrane oxygenation utilization were substantial, but these disparities did not increase as the hospital COVID-19 burden increased.

EDITOR’S PERSPECTIVE

Machine Learning Identifies Higher Survival Profile In Extracorporeal Cardiopulmonary Resuscitation

OBJECTIVES

Extracorporeal cardiopulmonary resuscitation (ECPR) has been shown to improve neurologically favorable survival in patients with refractory out-of-hospital cardiac arrest (OHCA) caused by shockable rhythms. Further refinement of patient selection is needed to focus this resource-intensive therapy on those patients likely to benefit. This study sought to create a selection model using machine learning (ML) tools for refractory cardiac arrest patients undergoing ECPR.

DESIGN

Retrospective cohort study.

SETTING

Cardiac ICU in a Quaternary Care Center.

PATIENTS

Adults 18-75 years old with refractory OHCA caused by a shockable rhythm.

METHODS

Three hundred seventy-six consecutive patients with refractory OHCA and a shockable presenting rhythm were analyzed, of which 301 underwent ECPR and cannulation for venoarterial extracorporeal membrane oxygenation. Clinical variables that were widely available at the time of cannulation were analyzed and ranked on their ability to predict neurologically favorable survival.

INTERVENTIONS

ML was used to train supervised models and predict favorable neurologic outcomes of ECPR. The best-performing models were internally validated using a holdout test set.

MEASUREMENTS AND MAIN RESULTS

Neurologically favorable survival occurred in 119 of 301 patients (40%) receiving ECPR. Rhythm at the time of cannulation, intermittent or sustained return of spontaneous circulation, arrest to extracorporeal membrane oxygenation perfusion time, and lactic acid levels were the most predictive of the 11 variables analyzed. All variables were integrated into a training model that yielded an in-sample area under the receiver-operating characteristic curve (AUC) of 0.89 and a misclassification rate of 0.19. Out-of-sample validation of the model yielded an AUC of 0.80 and a misclassification rate of 0.23, demonstrating acceptable prediction ability.

CONCLUSIONS

ML can develop a tiered risk model to guide ECPR patient selection with tailored arrest profiles.

Machine learning based predictive modeling of readmissions following extracorporeal membrane oxygenation hospitalizations

Background

Despite increasing utilization and survival benefit over the last decade, extracorporeal membrane oxygenation (ECMO) remains resource-intensive with significant complications and rehospitalization risk. We thus utilized machine learning (ML) to develop prediction models for 90-day nonelective readmission following ECMO.

Methods

All adult patients receiving ECMO who survived index hospitalization were tabulated from the 2016-2020 Nationwide Readmissions Database. Extreme Gradient Boosting (XGBoost) models were developed to identify features associated with readmission following ECMO. Area under the receiver operating characteristic (AUROC), mean Average Precision (mAP), and the Brier score were calculated to estimate model performance relative to logistic regression (LR). Shapley Additive Explanation summary (SHAP) plots evaluated the relative impact of each factor on the model. An additional sensitivity analysis solely included patient comorbidities and indication for ECMO as potential model covariates.

Results

Of ∼22,947 patients, 4495 (19.6 %) were readmitted nonelectively within 90 days. The XGBoost model exhibited superior discrimination (AUROC 0.64 vs 0.49), classification accuracy (mAP 0.30 vs 0.20) and calibration (Brier score 0.154 vs 0.165, all P < 0.001) in predicting readmission compared to LR. SHAP plots identified duration of index hospitalization, undergoing heart/lung transplantation, and Medicare insurance to be associated with increased odds of readmission. Upon sub-analysis, XGBoost demonstrated superior disclination compared to LR (AUROC 0.61 vs 0.60, P < 0.05). Chronic liver disease and frailty were linked with increased odds of nonelective readmission.

Conclusions

ML outperformed LR in predicting readmission following ECMO. Future work is needed to identify other factors linked with readmission and further optimize post-ECMO care among this cohort.

Race-Conscious Research Using Extracorporeal Life Support Organization Registry Data: A Narrative Review

Race-conscious research identifies health disparities with 1) rigorous and responsible data collection, 2) intentionality and considered analyses, and 3) interpretation of results that advance health equity. Individual registries must overcome specific challenges to promote race-conscious research, and this paper describes ways to achieve this with a focus on the international Extracorporeal Life Support Organization (ELSO) registry. This article reviews ELSO registry publications that studied race with outcomes to consider whether research outputs align with race-conscious concepts and describe the direction of associations reported. Studies were identified via secondary analysis of a comprehensive scoping review on ECMO disparities. Of 32 multicenter publications, two (6%) studied race as the primary objective. Statistical analyses, confounder adjustment, and inclusive, antibiased language were inconsistently used. Only two (6%) papers explicitly discussed mechanistic drivers of inequity such as structural racism, and five (16%) discussed race variable limitations or acknowledged unmeasured confounders. Extracorporeal Life Support Organization registry publications demonstrated more adverse ECMO outcomes for underrepresented/minoritized populations than non-ELSO studies. With the objective to promote race-conscious ELSO registry research outputs, we provide a comprehensive understanding of race variable limitations, suggest reasoned retrospective analytic approaches, offer ways to interpret results that advance health equity, and recommend practice modifications for data collection.

Hospital Policy Variation in Addressing Decisions to Withhold and Withdraw Life-Sustaining Treatment

BACKGROUND

Sociodemographic disparities in physician decisions to withhold and withdraw life-sustaining treatment exist. Little is known about the content of hospital policies that guide physicians involved in these decisions.

RESEARCH QUESTION

What is the prevalence of US hospitals with policies that address withholding and withdrawing life-sustaining treatment; how do these policies approach ethically controversial scenarios; and how do these policies address sociodemographic disparities in decisions to withhold and withdraw life-sustaining treatment?

STUDY DESIGN AND METHODS

This national cross-sectional survey assessed the content of hospital policies addressing decisions to withhold or withdraw life-sustaining treatment. We distributed the survey electronically to American Society for Bioethics and Humanities members between July and August 2023 and descriptively analyzed responses.

RESULTS

Among 93 respondents from hospitals or hospital systems representing all 50 US states, Puerto Rico, and Washington, DC, 92% had policies addressing decisions to withhold or withdraw life-sustaining treatment. Hospitals varied in their stated guidance, permitting life-sustaining treatment to be withheld or withdrawn in cases of patient or surrogate request (82%), physiologic futility (81%), and potentially inappropriate treatment (64%). Of the 8% of hospitals with policies that addressed patient sociodemographic disparities in decisions to withhold or withdraw life-sustaining treatment, these policies provided opposing recommendations to either exclude sociodemographic factors in decision-making or actively acknowledge and incorporate these factors in decision-making. Only 3% of hospitals had policies that recommended collecting and maintaining information about patients for whom life-sustaining treatment was withheld or withdrawn that could be used to identify disparities in decision-making.

INTERPRETATION

Although most surveyed US hospital policies addressed withholding or withdrawing life-sustaining treatment, these policies varied widely in criteria and processes. Surveyed policies also rarely addressed sociodemographic disparities in these decisions.

Regional access to a centralized extracorporeal membrane oxygenation (ECMO) service in Victoria, Australia

Introduction

Victoria, Australia provides a centralised state ECMO service, supported by ambulance retrieval. Equity of access to this service has not been previously described.

Objective

Describe the characteristics of ECMO recipients and quantify geographical and socioeconomic influence on access.

Design

Retrospective observational study with spatial mapping.

Participants and setting

Adult (≥18 years) ECMO recipients from July 2016-June 2022. Data from administrative Victorian Admissions Episodes Database analysed in conjunction with Australian Urban Research Infrastructure Network population data and choropleth mapping. Presumed ECMO modes were inferred from cardiopulmonary bypass and pre-hospital cardiac arrest codes. Spatial autoregressive models including Moran's test used for spatial lag testing.

Outcomes

Demographics and outcomes of ECMO recipients; ECMO incidence by patient residence (Statistical-Area Level 2, SA-2) and Index of Relative Socioeconomic Advantage and Disadvantage (IRSAD); and ECMO utilisation adjusted for patient factors and linear distance from the central ECMO referral site.

Results

631 adults received ECMO over 6 years, after exclusion of paediatric (n = 242), duplicate (n = 135), and interstate or incomplete (n = 72) records. Mean age was 51.8 years, and 68.8 % were male. Overall ECMO incidence was 3.00 ± 3.95 per 105 population. 135 (21.4 %) were presumed VA-ECMO, 59 (9.3 %) presumed ECPR, and 437 (69.3 %) presumed VV-ECMO. Spatial lag was non-significant after adjusting for patient characteristics. Distance from the central referral site (dy/dx = 0.19, 95% CI -0.41-0.04, p = 0.105) and IRSAD score (dy/dx = 0.17, 95% CI -0.19-0.53, p = 0.359) did not predict ECMO utilisation.

Conclusion

Victorian ECMO incidence rates were low. We did not find evidence of inequity of access to ECMO irrespective of regional area or socioeconomic status.

An Update on Management of Adult Patients with Acute Respiratory Distress Syndrome: An Official American Thoracic Society Clinical Practice Guideline

Background: This document updates previously published Clinical Practice Guidelines for the management of patients with acute respiratory distress syndrome (ARDS), incorporating new evidence addressing the use of corticosteroids, venovenous extracorporeal membrane oxygenation, neuromuscular blocking agents, and positive end-expiratory pressure (PEEP). Methods: We summarized evidence addressing four "PICO questions" (patient, intervention, comparison, and outcome). A multidisciplinary panel with expertise in ARDS used the Grading of Recommendations, Assessment, Development, and Evaluation framework to develop clinical recommendations. Results: We suggest the use of: 1) corticosteroids for patients with ARDS (conditional recommendation, moderate certainty of evidence), 2) venovenous extracorporeal membrane oxygenation in selected patients with severe ARDS (conditional recommendation, low certainty of evidence), 3) neuromuscular blockers in patients with early severe ARDS (conditional recommendation, low certainty of evidence), and 4) higher PEEP without lung recruitment maneuvers as opposed to lower PEEP in patients with moderate to severe ARDS (conditional recommendation, low to moderate certainty), and 5) we recommend against using prolonged lung recruitment maneuvers in patients with moderate to severe ARDS (strong recommendation, moderate certainty). Conclusions: We provide updated evidence-based recommendations for the management of ARDS. Individual patient and illness characteristics should be factored into clinical decision making and implementation of these recommendations while additional evidence is generated from much-needed clinical trials.