Race, Ethnicity, Health Insurance, and Mortality in Older Survivors of Critical Illness

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

Racial inequities and biopsychosocial indicators in older adults

Objective

to analyze the association of self-reported skin color/race with biopsychosocial indicators in older adults.

Method

cross-sectional study conducted with a total of 941 older adults from a health micro-region in Brazil. Data were collected at home with instruments validated for the country. Descriptive analysis and binary, multinomial and linear logistic regression (p<0.05) were performed.

Results

Most older adults were self-declared white color/race (63.8%). Black color/race was a protective factor for negative (OR=0.40) and regular (OR=0.44) self-rated health perception and for the indicative of depressive symptoms (OR=0.43); and it was associated with the highest social support score (β=3.60) and the lowest number of morbidities (β=-0.78).

Conclusion

regardless of sociodemographic and economic characteristics, older adults of black color/race had the best outcomes of biopsychosocial indicators.

Comparison of Clinical Characteristics and Outcomes of Younger and Elderly Patients with Severe COVID-19 in Korea: A Retrospective Multicenter Study

Old age is associated with disease severity and poor prognosis among coronavirus disease 2019 (COVID-19) cases; however, characteristics of elderly patients with severe COVID-19 are limited. We aimed to assess the clinical characteristics and outcomes of patients hospitalized with severe COVID-19 at tertiary care centers in South Korea. This retrospective multicenter study included patients with severe COVID-19 who were admitted at seven hospitals in South Korea from 2 February 2020 to 28 February 2021. The Cox regression analyses were performed to assess factors associated with the in-hospital mortality. Of 488 patients with severe COVID-19, 318 (65.2%) were elderly (≥65 years). The older patient group had more underlying diseases and a higher severity score than the younger patient group. The older patient group had a higher in-hospital mortality rate than the younger patient group (25.5% versus 4.7%, p-value < 0.001). The in-hospital mortality risk factors among patients with severe COVID-19 included age, acute physiology and chronic health evaluation II score, presence of diabetes and chronic obstructive lung disease, high white blood cell count, low neutrophil-lymphocyte ratio and platelet count, do-not-resuscitate order, and treatment with invasive mechanical ventilation. In addition to old age, disease severity and examination results must be considered in treatment decision-making.

Link between redemption of a medical food pantry voucher and reduced hospital readmissions

This study investigated the relationship between redeeming a voucher at hospital-based Medical Food Pantry (MFP) and hospital readmissions in Greenville, NC. Admitted patients at Vidant Medical Center identified as food insecure were given a voucher to the MFP. A retrospective chart review identified demographic information, type of insurance, voucher provision, and redemption dates, food bag type and number of subsequent hospital readmissions for all patients issued a voucher (n = 542) between June 21, 2018 and July 1, 2019. Negative binomial regression analysis assessed the relationship between readmissions and voucher redemption. Sixty percent of patients receiving a voucher were minority (African American) with an average age of 55. Nearly half (48 percent) had Medicare. Thirty-eight percent of those vouchers that were issued were redeemed, usually within five days. Regression results indicate that the number of readmissions was higher among women and non-whites in the sample relative to men and whites. Those patients who redeemed a food voucher had a seven percent lower likelihood of being readmitted (CI, 0.05–0.27). Food insecure patients who redeemed MFP vouchers had a comparatively lower likelihood of subsequent readmissions. These findings suggest that programs targeting modifiable social determinants of health like food insecurity could improve health outcomes and reduce utilization of the healthcare system.

Socioeconomic Factors and Intensive Care Unit-Related Cognitive Impairment

OBJECTIVE

We aimed to identify socioeconomic and clinical risk factors for post-intensive care unit (ICU)-related long-term cognitive impairment (LTCI).

SUMMARY BACKGROUND DATA

After delirium during ICU stay, LTCI has been increasingly recognized, but without attention to socioeconomic factors.

METHODS

We enrolled a prospective, multicenter cohort of ICU survivors with shock or respiratory failure from surgical and medical ICUs across 5 civilian and Veteran Affairs (VA) hospitals from 2010 to 2016. Our primary outcome was LTCI at 3- and 12 months post-hospital discharge defined by the Repeatable Battery for Assessment of Neuropsychological Symptoms (RBANS) global score. Covariates adjusted using multivariable linear regression included age, sex, race, AHRQ socioeconomic index, Charlson comorbidity, Framingham stroke risk, Sequential Organ Failure Assessment, duration of coma, delirium, hypoxemia, sepsis, education level, hospital type, insurance status, discharge disposition, and ICU drug exposures.

RESULTS

Of 1040 patients, 71% experienced delirium, and 47% and 41% of survivors had RBANS scores >1 standard deviation below normal at 3- and 12 months, respectively. Adjusted analysis indicated that delirium, non-White race, lower education, and civilian hospitals (as opposed to VA), were associated with at least a half standard deviation lower RBANS scores at 3- and 12 months (P ≤ 0.03). Sex, AHRQ socioeconomic index, insurance status, and discharge disposition were not associated with RBANS scores.

CONCLUSIONS

Socioeconomic and clinical risk factors, such as race, education, hospital type, and delirium duration, were linked to worse PICS ICU-related, LTCI. Further efforts may focus on improved identification of higher-risk groups to promote survivorship through emerging improvements in cognitive rehabilitation.

Influence of Insurance Status and Demographic Factors on Outcomes Following Tracheostomy

OBJECTIVES/HYPOTHESIS

Little data exists regarding the relationship between socioeconomic and demographic factors and tracheostomy outcomes. The goal of this study was to determine associations between socioeconomic status (SES), demographic factors, and insurance status with hospital length of stay (LOS), intensive care unit (ICU) LOS, and mortality following tracheostomy.

STUDY DESIGN

Retrospective cohort study.

METHODS

A retrospective analysis of all patients who underwent tracheostomy at an urban tertiary-care academic hospital from 2016 to 2017 was performed. Patients were aggregated into low-, middle-, and high-income brackets. Other variables included age, sex, race, ethnicity, body mass index, and Charlson Comorbidity Index (CCI). Outcomes included hospital and ICU LOS, in-hospital mortality, and 30-day mortality following tracheostomy. Outcomes were compared using Kruskal-Wallis tests for continuous variables and χ² or Fisher exact tests for categorical variables. The α level was set to .05.

RESULTS

In total, 523 patients were included in the study. Patients from high-income areas were more likely to be male (P < .01), white (P < .01), and had lower body mass index (P = .04). On multiple regression analysis, Hispanic or Latino ethnicity was associated with an increased odds of 30-day mortality (odds ratio [OR]: 4.43, P = .020). CCI was also associated with increased odds of 30-day mortality (OR: 1.12, P = .039).

CONCLUSIONS

Lower SES was not associated with increased morbidity or mortality after tracheostomy. Although Hispanic patients tended to have a lower CCI score, they had increased 30-day mortality, suggesting there are factors specific to this population that may influence outcomes, and future targeted studies are warranted to study these relationships.

LEVEL OF EVIDENCE

4 Laryngoscope, 131:1463-1467, 2021.

Combining Nonclinical Determinants of Health and Clinical Data for Research and Evaluation: Rapid Review

Background

Nonclinical determinants of health are of increasing importance to health care delivery and health policy. Concurrent with growing interest in better addressing patients’ nonmedical issues is the exponential growth in availability of data sources that provide insight into these nonclinical determinants of health.

Objective

This review aimed to characterize the state of the existing literature on the use of nonclinical health indicators in conjunction with clinical data sources.

Methods

We conducted a rapid review of articles and relevant agency publications published in English. Eligible studies described the effect of, the methods for, or the need for combining nonclinical data with clinical data and were published in the United States between January 2010 and April 2018. Additional reports were obtained by manual searching. Records were screened for inclusion in 2 rounds by 4 trained reviewers with interrater reliability checks. From each article, we abstracted the measures, data sources, and level of measurement (individual or aggregate) for each nonclinical determinant of health reported.

Results

A total of 178 articles were included in the review. The articles collectively reported on 744 different nonclinical determinants of health measures. Measures related to socioeconomic status and material conditions were most prevalent (included in 90% of articles), followed by the closely related domain of social circumstances (included in 25% of articles), reflecting the widespread availability and use of standard demographic measures such as household income, marital status, education, race, and ethnicity in public health surveillance. Measures related to health-related behaviors (eg, smoking, diet, tobacco, and substance abuse), the built environment (eg, transportation, sidewalks, and buildings), natural environment (eg, air quality and pollution), and health services and conditions (eg, provider of care supply, utilization, and disease prevalence) were less common, whereas measures related to public policies were rare. When combining nonclinical and clinical data, a majority of studies associated aggregate, area-level nonclinical measures with individual-level clinical data by matching geographical location.

Conclusions

A variety of nonclinical determinants of health measures have been widely but unevenly used in conjunction with clinical data to support population health research.

Impacts of Financial Coverage on Long-Term Outcome of Intensive Care Unit Survivors in South Korea

PURPOSE

The objective of this study was to investigate whether financial coverage by the national insurance system for patients with lower economic conditions can improve their 1-year mortality after intensive care unit (ICU) discharge.

MATERIALS AND METHODS

This study, conducted in a single tertiary hospital, used a retrospective cohort design to investigate discharged ICU survivors between January 2012 and December 2016. ICU survivors were classified into two groups according to the National Health Insurance (NHI) system in Korea: medical aid program (MAP) group, including people who have difficulty paying their insurance premium or receive medical aid from the government due to a poor economic status; and NHI group consisting of people who receive government subsidy for approximately 2/3 of their medical expenses.

RESULTS

After propensity score (PS) matching, a total of 2495 ICU survivors (1859 in NHI group and 636 in MAP group) were included in the analysis. Stratified Cox regression analysis of PS-matched cohorts showed that 1-year mortality was 1.31-fold higher in MAP group than in NHI group (hazard ratio: 1.31, 95% confidence interval, 1.06 to 1.61; p=0.012). According to Kaplan-Meir estimation, MAP group also showed significantly poorer survival probability than NHI group after PS matching (p=0.011).

CONCLUSION

This study showed that 1-year mortality was higher in ICU survivors with low economic status, even if financial coverage was provided by the government. Our result suggests the necessity of a more nuanced and multifaceted approach to policy for ICU survivors with low economic status.

Health Insurance and Disparities in Mortality among Older Survivors of Critical Illness: A Population Study

OBJECTIVES

The 1.5 million Medicare beneficiaries who survive intensive care each year have a high post-hospitalization mortality rate. We aimed to determine whether mortality after critical illness is higher for Medicare beneficiaries with Medicaid compared with those with commercial insurance.

DESIGN

A retrospective cohort study from 2010 through 2014 with 1 year of follow-up using the New York Statewide Planning and Research Cooperative System database.

SETTING

A New York State population-based study of older (age ≥65 y) survivors of intensive care.

PARTICIPANTS

Adult Medicare beneficiaries age 65 years or older who were hospitalized with intensive care at a New York State hospital and survived to discharge.

INTERVENTION

None.

MEASUREMENT

Mortality in the first year after hospital discharge.

RESULTS

The study included 340 969 Medicare beneficiary survivors of intensive care with a mean (standard deviation) age of 77 (8) years; 20% died within 1 year. There were 152 869 (45%) with commercial insurance, 78 577 (23%) with Medicaid, and 109 523 (32%) with Medicare alone. Compared with those with commercial insurance, those with Medicare alone had a similar 1-year mortality rate (adjusted hazard ratio [aHR] = 1.01; 95% confidence interval [CI] = .99-1.04), and those with Medicaid had a 9% higher 1-year mortality rate (aHR = 1.09; 95% CI = 1.05-1.12). Among those discharged home, the 1-year mortality rate did not vary by insurance coverage, but among those discharged to skilled-care facilities (SCFs), the 1-year mortality rate was 16% higher for Medicaid recipients (aHR = 1.16; 95% CI = 1.12-1.21; P for interaction <.001).

CONCLUSIONS

Older adults with Medicaid insurance have a higher 1-year post-hospitalization mortality compared with those with commercial insurance, especially among those discharged to SCFs. Future studies should investigate care disparities at SCFs that may mediate these higher mortality rates. J Am Geriatr Soc 67:2497-2504, 2019.

Medical resource utilization patterns and mortality rates according to age among critically ill patients admitted to a medical intensive care unit

There is ongoing controversy about how to address the growing demand for intensive care for critically ill elderly patients. We investigated resource utilization patterns and mortality rates according to age among critically ill patients.We retrospectively analyzed the medical records of patients admitted to a medical intensive care unit (ICU) in a tertiary referral teaching hospital between July 2006 and June 2015. Patients were categorized into non-elderly (age <65 years, n = 4140), young-elderly (age 65-74 years, n = 2306), and old-elderly (age ≥75 years, n = 1508) groups.Among 7954 admissions, the mean age was 61.5 years, and 5061 (63.6%) were of male patients. The proportion of comorbidities increased with age (64.6% in the non-elderly vs 81.4% in the young-elderly vs 82.8% in the old-elderly, P < .001 and P for trend <.001), whereas the baseline Sequential Organ Failure Assessment (SOFA) score decreased with age (8.1 in the non-elderly vs 7.2 in the young-elderly vs 7.2 in the old-elderly, P < .001, R = -.092 and P for trend <.001). Utilization rates of mechanical ventilation (48.6% in the non-elderly vs 48.3% in the young-elderly vs 45.5% in the old-elderly, P = .11) and renal replacement therapy (27.5% in the non-elderly vs 25.5% in the young-elderly vs 24.8% in the old-elderly, P = .069) were comparable between the age groups. The 28-day ICU mortality rates were lower in the young-elderly and the old-elderly groups than in the non-elderly group (35.6% in the non-elderly vs 34.2% in the young-elderly, P = .011; and vs 32.6% in the old-elderly, P = .002).A substantial number of critically ill elderly patients used medical resources as non-elderly patients and showed favorable clinical outcomes. Our results support that underlying medical conditions rather than age per se need to be considered for determining intensive care.

Impact of Socioeconomic Status on 30-Day and 1-Year Mortalities after Intensive Care Unit Admission in South Korea: A Retrospective Cohort Study

Background

Socioeconomic status (SES) is closely associated with health outcomes, including mortality in critically ill patients admitted to intensive care unit (ICU). However, research regarding this issue is lacking, especially in countries where the National Health Insurance System is mainly responsible for health care. This study aimed to investigate how the SES of ICU patients in South Korea is associated with mortality.

Methods

This was a retrospective observational study of adult patients aged ≥20 years admitted to ICU. Associations between SES-related factors recorded at the time of ICU admission and 30-day and 1-year mortalities were analyzed using univariable and multivariable Cox regression analyses.

Results

A total of 6,008 patients were included. Of these, 394 (6.6%) died within 30 days of ICU admission, and 1,125 (18.7%) died within 1 year. Multivariable Cox regression analysis found no significant associations between 30-day mortality after ICU admission and SES factors (P>0.05). However, occupation was significantly associated with 1-year mortality after ICU admission.

Conclusions

Our study shows that 30-day mortality after ICU admission is not associated with SES in the National Health Insurance coverage setting. However, occupation was associated with 1-year mortality after ICU admission.

Using electronic health record data for environmental and place based population health research: a systematic review

PURPOSE

We conducted a systematic review of literature published on January 2000-May 2017 that spatially linked electronic health record (EHR) data with environmental information for population health research.

METHODS

We abstracted information on the environmental and health outcome variables and the methods and data sources used.

RESULTS

The automated search yielded 669 articles; 128 articles are included in the full review. The number of articles increased by publication year; the majority (80%) were from the United States, and the mean sample size was approximately 160,000. Most articles used cross-sectional (44%) or longitudinal (40%) designs. Common outcomes were health care utilization (32%), cardiometabolic conditions/obesity (23%), and asthma/respiratory conditions (10%). Common environmental variables were sociodemographic measures (42%), proximity to medical facilities (15%), and built environment and land use (13%). The most common spatial identifiers were administrative units (59%), such as census tracts. Residential addresses were also commonly used to assign point locations, or to calculate distances or buffer areas.

CONCLUSIONS

Future research should include more detailed descriptions of methods used to geocode addresses, focus on a broader array of health outcomes, and describe linkage methods. Studies should also explore using longitudinal residential address histories to evaluate associations between time-varying environmental variables and health outcomes.

End-of-Life Decision-Making for Patients With Geriatric Trauma Cared for in a Trauma Intensive Care Unit

BACKGROUND

The geriatric trauma population is growing and fraught with poor physiological response to injury and high mortality rates. Our primary hypothesis analyzed how prehospital and in-hospital characteristics affect decision-making regarding continued life support (CLS) versus withdrawal of care (WOC). Our secondary hypothesis analyzed adherence to end-of-life decisions regarding code status, living wills, and advanced directives.

MATERIALS AND METHODS

We performed a retrospective review of patients with geriatric trauma at a level I and level II trauma center from January 1, 2007, to December 31, 2014. Two hundred seventy-four patients met inclusion criteria with 144 patients undergoing CLS and 130 WOC.

RESULTS

A total of 13 269 patients with geriatric trauma were analyzed. Insurance type and injury severity score (ISS) were found to be significant predictors of WOC ( P = .013/.045). Withdrawal of care patients had shorter time to palliative consultation and those with geriatrics consultation were 16.1 times more likely to undergo CLS ( P = .026). Twenty-seven (33%) patients who underwent CLS and 31 (24%) patients who underwent WOC had a living will, advanced directive, or DNR order ( P = .93).

CONCLUSIONS

Of the many hypothesized predictors of WOC, ISS was the only tangible independent predictor of WOC. We observed an apparent disconnect between the patient's wishes via living wills or advanced directives "in a terminal condition" and fulfillment during EOL decision-making that speaks to the complex nature of EOL decisions and further supports the need for a multidisciplinary approach.