Hospital segregation, critical care strain, and inpatient mortality during the COVID-19 pandemic in New York City.

BACKGROUND: Hospital segregation by race, ethnicity, and health insurance coverage is prevalent, with some hospitals providing a disproportionate share of undercompensated care. We assessed whether New York City (NYC) hospitals serving a higher proportion of Medicaid and uninsured patients pre-pandemic experienced greater critical care strain during the first wave of the COVID-19 pandemic, and whether this greater strain was associated with higher rates of in-hospital mortality. METHODS: In a retrospective analysis of all-payer NYC hospital discharge data, we examined changes in admissions, stratified by use of intensive care unit (ICU), from the baseline period in early 2020 to the first COVID-19 wave across hospital quartiles (265,329 admissions), and crude and risk-adjusted inpatient mortality rates, also stratified by ICU use, in the first COVID wave across hospital quartiles (23,032 inpatient deaths), based on the proportion of Medicaid or uninsured admissions from 2017-2019 (quartile 1 lowest to 4 highest). Logistic regressions were used to assess the cross-sectional association between ICU strain, defined as ICU volume in excess of the baseline average, and patient-level mortality. RESULTS: ICU admissions in the first COVID-19 wave were 84%, 97%, 108%, and 123% of the baseline levels by hospital quartile 1-4, respectively. The risk-adjusted mortality rates for ICU admissions were 36.4 (CI = 34.7,38.2), 43.6 (CI = 41.5,45.8), 45.9 (CI = 43.8,48.1), and 45.7 (CI = 43.6,48.0) per 100 admissions, and those for non-ICU admissions were 8.6 (CI = 8.3,9.0), 10.9 (CI = 10.6,11.3), 12.6 (CI = 12.1,13.0), and 12.1 (CI = 11.6,12.7) per 100 admissions by hospital quartile 1-4, respectively. Compared with the reference group of 100% or less of the baseline weekly average, ICU admissions on a day for which the ICU volume was 101-150%, 151-200%, and > 200% of the baseline weekly average had odds ratios of 1.17 (95% CI = 1.10, 1.26), 2.63 (95% CI = 2.31, 3.00), and 3.26 (95% CI = 2.82, 3.78) for inpatient mortality, and non-ICU admissions on a day for which the ICU volume was 101-150%, 151-200%, and > 200% of the baseline weekly average had odds ratios of 1.28 (95% CI = 1.22, 1.34), 2.60 (95% CI = 2.40, 2.82), and 3.44 (95% CI = 3.11, 3.63) for inpatient mortality. CONCLUSIONS: Our findings are consistent with hospital segregation as a potential driver of COVID-related mortality inequities and highlight the need to desegregate health care to address structural racism, advance health equity, and improve pandemic resiliency.

Medication Nonuse and Hospital Utilization: Medicaid Participants With Type 2 Diabetes in New York City.

INTRODUCTION: This study assesses the proportion of New York City Medicaid participants diagnosed with type 2 diabetes who did not have any claims for diabetes medication for an entire year and the association between nonuse of diabetes medication and subsequent hospitalizations. METHODS: The 2014‒2016 New York State Medicaid claims data were used for this cohort study. Two types of hospitalizations were examined: all-cause hospitalizations and preventable diabetes hospitalizations. A potential association between medication nonuse and the number of hospitalizations in the following year was assessed using the negative binomial regression model, adjusting for individual- and neighborhood-level factors. The study was conducted in 2019‒2020. RESULTS: Among the 117,183 individuals included in this study, 27.5% did not use any diabetes medication for an entire year. Compared with individuals using oral hypoglycemic medication only, the crude rate of all-cause hospitalizations among individuals who used no medication was approximately twice as high (37,111 vs 19,209 per 100,000 population), and the crude rate of preventable diabetes hospitalizations was almost 3 times as high (1,488 vs 537 per 100,000 population). Adjusting for individual- and neighborhood-level characteristics, medication nonuse was still associated with higher levels of all-cause hospitalizations (incidence rate ratio=1.26; 95% CI=1.21, 1.31) and preventable diabetes hospitalizations (incidence rate ratio=1.66; 95% CI=1.39, 1.99). CONCLUSIONS: Medication use and adherence are important for managing diabetes. However, almost 30% of New York City Medicaid participants with type 2 diabetes had no claims for diabetes medication for an entire year. Significantly higher hospitalization rates among this group warrant attention from providers and policy makers.

Disparities in Preventable Hospitalizations Among Public Housing Developments.

INTRODUCTION: This study assesses preventable hospitalization rates among New York City residents living in public housing developments compared with all New York City residents and residents in low-income areas. Additionally, preventable hospitalization rates by development (one or multiple buildings in close proximity and served by the same management office) were determined. METHODS: The 2010-2014 New York City hospital discharge data were geocoded and linked with New York City Housing Authority records using building-level identifiers. Preventable hospitalizations resulting from ambulatory care-sensitive conditions were identified for public housing residents, citywide, and residents of low-income areas. Age-adjusted overall and ambulatory care-sensitive, condition-specific preventable hospitalization rates (11 outcomes) were determined and compared across groups to assess potential disparities. Additionally, rates were ranked and compared among public housing developments by quartiles. The analysis was conducted in 2016 and 2017. RESULTS: The age-adjusted rate of preventable hospitalization was significantly higher among public housing residents than citywide (rate ratio [RR]=2.67, 95% CI=2.65, 2.69), with the greatest disparities in hospitalizations related to diabetes (RR=3.12, 95% CI=3.07, 3.18) and asthma (RR=4.14, 95% CI=4.07, 4.21). The preventable hospitalization rate was also higher among residents of public housing than low-income areas (RR=1.33, 95% CI=1.31, 1.35). There were large differences between developments ranked in the top and bottom quartiles of preventable hospitalization (RR=1.81, 95% CI=1.76, 1.85) with the largest difference related to chronic obstructive pulmonary disease (RR=3.38, 95% CI=3.08, 3.70). CONCLUSIONS: Preventable hospitalization rates are high among public housing residents, and vary significantly by development and condition. By providing geographically granular information, geocoded hospital discharge data can serve as a valuable tool for health assessment and engagement of the healthcare sector and other stakeholders in interventions that address health inequities.