Changes in Health Care Access by Race, Income, and Medicaid Expansion During the COVID-19 Pandemic.

BACKGROUND: The intersecting crises of the COVID-19 pandemic, job losses, and concomitant loss of employer-sponsored health insurance may have disproportionately affected health care access within minorized and lower-socioeconomic status communities. OBJECTIVE: To describe changes in access to care during the COVID-19 pandemic, stratified by race/ethnicity, household income, and state Medicaid expansion status. RESEARCH DESIGN: We used interrupted time series and difference-in-differences regression models, controlling for respondent characteristics and preexisting trends. SUBJECTS: Data were extracted for all adults aged 18-64 surveyed in the 2015-2020 Behavioral Risk Factor Surveillance System (N=1,731,699) from all 50 states and the District of Columbia. MEASURES: Our outcomes included indicators for whether respondents had any health insurance coverage or avoided seeking care because of cost within the prior year. The primary exposure was the onset of the COVID-19 pandemic in the United States in March 2020. RESULTS: The pandemic was associated with a 1.2 percentage point (pp) decline in uninsurance for Medicaid expansion states (95% CI, -1.8, -0.6); these reductions were concentrated among respondents who were Black, multiracial, or low income. The rates of uninsurance were generally stable in nonexpansion states. The rates of avoided care because of cost fell by 3.5 pp in Medicaid expansion states (95% CI, -3.9, -3.1), and by 3.6 pp (95% CI, 4.3-2.9) in nonexpansion states. These declines were concentrated among respondents who were Hispanic, Other Race, or low income. CONCLUSIONS: Our findings reinforce the value of Medicaid expansion as one tool to improve access to health insurance and care for marginalized and vulnerable populations.

Social risk adjustment in the hospital readmission reduction program: Pitfalls of peer grouping, measurement challenges, and potential solutions.

OBJECTIVE: To examine the limitations of peer grouping and associated challenges measuring social risk in Medicare's Hospital Readmission Reduction Program (HRRP). Under peer grouping, hospitals are divided into quintiles based on the proportion of a hospital's Medicare inpatients with Medicaid ("dual share"). This approach was implemented to address concerns that the HRRP unfairly penalized hospitals that disproportionately serve disadvantaged patients. DATA: Public data on hospitals in the HRRP. DESIGN: We examined the relationship between hospital dual share and readmission rates within peer groups; changes in hospitals' peer group assignments, readmission rates, and penalties; and the relationship between state Medicaid eligibility rules and peer groups. DATA COLLECTION: Public data on hospital characteristics and readmission rates for 3119 hospitals from 2019 to 2020. PRINCIPAL FINDINGS: The proportion of dual inpatients among hospitals of the same peer group varied by as much as 69 percentage points (ppt). Within peer groups, a one ppt increase in dual share was associated with a 0.01 ppt increase in the difference from the median readmission rate (p < 0.001). From 2019 to 2020, 8.8% of hospitals switched peer groups. Compared to hospitals that did not switch, those moving to a lower peer group had a higher mean penalty in 2020 (0.096 ppt; p = 0.006); those moving to a higher group had a lower mean penalty (-0.06 ppt; p = 0.079). However, changes in penalties did not correspond to changes in readmission rates. Hospitals in states with higher Medicaid income eligibility limits were more likely to be in higher peer groups. CONCLUSIONS: Peer grouping is limited in the extent to which it accounts for differences in hospitals' patient populations, and it may not fully insulate hospitals from penalties linked to changes in patient mix. These problems arise from the construction of peer groups and the measure of social risk used to define them.

Quantifying treatment preferences and their association with financial toxicity in women with breast cancer.

BACKGROUND: The objective of the current study was to understand treatment preferences and their association with financial toxicity in Patient Advocate Foundation clients with breast cancer. METHODS: This choice-based conjoint analysis used data from a nationwide sample of women with breast cancer who received assistance from the Patient Advocate Foundation. Choice sets created from 13 attributes of 3 levels each elicited patient preferences and trade-offs. Latent class analysis segmented respondents into distinct preference archetypes. The Comprehensive Score for Financial Toxicity (COST) tool captured financial toxicity. Adjusted generalized linear models estimated COST score differences by preference archetype. RESULTS: Of 220 respondents (for a response rate of 10%), the median age was 58 years (interquartile range, 49-66 years); 28% of respondents were Black, indigenous, or people of color; and approximately 60% had household incomes <$40,000. The majority of respondents were diagnosed with early-stage cancer (91%), 38% had recurrent disease, and 61% were receiving treatment. Treatment choice was most affected by preferences related to affordability and impact on activities of daily living. Two distinct treatment preference archetypes emerged. The "cost-prioritizing group" (75% of respondents) was most concerned about affordability, impact on activities of daily living, and burdening care partners. The "functional independence-prioritizing group" (25% of respondents) was most concerned about their ability to work, physical side effects, and interference with life events. COST scores were found to be similar between the archetypes in adjusted models (cost-prioritizing group COST score, 12 [95% confidence interval, 9-14]; and functional independence-prioritizing COST score, 11 [95% confidence interval, 9-13]). CONCLUSIONS: Patients with breast cancer prioritized affordability or maintaining functional independence when making treatment decisions. Because of this variability, preference evaluation during treatment decision making could optimize patients' treatment experiences.

Treatment Decision Making and Financial Toxicity in Women With Metastatic Breast Cancer.

INTRODUCTION: Oncologists have increasingly been proponents of shared decision making (SDM) to enhance patient outcomes and reduce unnecessary health care spending. However, its effect on patient out-of-pocket costs is unknown. This study investigated the relationship between patient preferences for SDM and financial toxicity (FT) in patients with metastatic breast cancer (MBC). PATIENTS AND METHODS: This cross-sectional study utilized surveys of women aged ≥ 18 with MBC who received care at two academic hospitals in Alabama from 2017 to 2019. Patients self-reported their SDM preference (Control Preferences Scale) and FT (Comprehensive Score for Financial Toxicity [COST] tool; 11-item scale, with lower scores indicating worse FT). Effect sizes were calculated using the proportion of variance explained (R2) or Cramer's V. Differences in FT by SDM preference were estimated using mixed models clustered by site and treating medical oncologist. RESULTS: In 95 women with MBC, 44% preferred SDM, 29% preferred provider-driven decision making, and 27% preferred patient-driven decision making. Patients preferring SDM were more often college educated (53% vs. 39%; V = 0.12) with an income greater than $40,000/y (55% vs. 43%; V = 0.18). Overall median COST was 22 (interquartile range, 16-29). After adjusting for patient demographic and clinical characteristics, patients preferring patient-driven decision making trended toward worse FT (COST 17: 95% confidence interval, 12-22) compared to those preferring SDM (COST 19: 95% confidence interval, 15-23) and those preferring provider-driven decision making (COST 22: 95% confidence interval, 17-27). CONCLUSION: Patients preferring more patient-driven decision making reported worse FT, although differences did not reach statistical significance. Further research is needed to understand this relationship.

Oncologic Services Through Project Access and Other Safety Net Care Coordination Programs.

PURPOSE: Little is known about the provision of oncologic services by Project Access safety net care coordination programs. MATERIALS AND METHODS: Information on safety net care coordination program locations, health services, and patient eligibility was obtained via program Web sites and calls. For programs not offering oncologic care, program directors were interviewed to identify oncologic care barriers. RESULTS: Web sites of 29 safety net care coordination programs in 22 states were identified; 62% (n = 18) offered oncologic services. Programs were in 65% (n = 11) of states that did not expand Medicaid. Of those offering oncologic services, 83% (n = 15) offered free chemotherapy, and 93% (n = 27) of all programs offered oncologic imaging. Program director interviews revealed costs, longitudinal care, and multiple-physician buy-in as barriers limiting oncologic care. CONCLUSION: Third-party care coordination centers provide a novel and potentially unrecognized approach to increasing oncology service access. Further research should identify strategies to overcome the relative lack of oncologic care offerings.

Health Insurance Literacy and Financial Hardship in Women Living With Metastatic Breast Cancer.

PURPOSE: In patients with metastatic breast cancer (MBC), low health insurance literacy may be associated with adverse material conditions, psychological response, and coping behaviors because of financial hardship (FH). This study explored the relationship between health insurance literacy and FH in women with MBC. METHODS: This cross-sectional study used data collected from 84 women receiving MBC treatment at 2 southeastern cancer centers. Low health insurance literacy was defined as not knowing premium or deductible costs. FH was defined by lifestyle changes as a result of medical expenses, financial toxicity, and medical care modifications attributable to cost. Mean differences were calculated using Cramer's V. Associations between health insurance literacy and FH were estimated with adjusted linear models. RESULTS: Half of the surveyed patients had low health insurance literacy, 26% were underinsured, 45% had private insurance, 39% had Medicare, and 15% had Medicaid. Patients with low health insurance literacy more often reported borrowing money (19% v 4%; V = 0.35); an inability to pay for basic necessities like food, heat, or rent (10% v 4%; V = 0.18); and skipping a procedure (8% v 1%; V = 0.21), medical test (7% v 0%; V = 0.30), or treatment (4% v 0%; V = 0.20) compared with patients with high health insurance literacy. Median Comprehensive Score for Financial Toxicity was 23 (interquartile range, 17-29). In adjusted models, health insurance literacy was not associated with financial toxicity. CONCLUSION: Low health insurance literacy was common in women receiving MBC treatment. Additional research to increase health insurance literacy could lessen undesirable material FH and unnecessary behavioral FH associated with cancer-related care.

Differential Impact of Hospital and Community Factors on Medicare Readmission Penalties.

OBJECTIVE: To identify hospital/county characteristics and sources of regional heterogeneity associated with readmission penalties. DATA SOURCES/STUDY SETTING: Acute care hospitals under the Hospital Readmissions Reduction Program from fiscal years 2013 to 2018 were linked to data from the Annual Hospital Association, Centers for Medicare and Medicaid Services, Medicare claims, Hospital Compare, Nursing Home Compare, Area Resource File, Health Inequity Project, and Long-term Care Focus. The final sample contained 3,156 hospitals in 1,504 counties. DATA COLLECTION/EXTRACTION METHODS: Data sources were combined using Medicare hospital identifiers or Federal Information Processing Standard codes. STUDY DESIGN: A two-level hierarchical model with correlated random effects, also known as the Mundlak correction, was employed with hospitals nested within counties. PRINCIPAL FINDINGS: Over a third of the variation in readmission penalties was attributed to the county level. Patient sociodemographics and the surrounding access to and quality of care were significantly associated with penalties. Hospital measures of Medicare volume, percentage dual-eligible and Black patients, and patient experience were correlated with unobserved area-level factors that also impact penalties. CONCLUSIONS: As the readmission risk adjustment does not include any community-level characteristics or geographic controls, the resulting endogeneity bias has the potential to disparately penalize certain hospitals.

Health Expenditure Concentration and Characteristics of High-Cost Enrollees in CHIP.

Devising effective cost-containment strategies in public insurance programs requires understanding the distribution of health care spending and characteristics of high-cost enrollees. The aim was to characterize high-cost enrollees in a state's public insurance program and determine whether expenditure inequality changes over time, or with changes in cost-sharing policies or program eligibility. We use 1999-2011 claims and enrollment data from the Alabama Children's Health Insurance Program, ALL Kids. All children enrolled in ALL Kids were included in our study, including multiple years of enrollment (N = 1,031,600 enrollee-months). We examine the distribution of costs over time, whether this distribution changes after increases in cost sharing and expanded eligibility, patient characteristics that predict high-cost status, and examine health services used by high-cost children to identify what is preventable. The top 10% (1%) of enrollees account for about 65.5% (24.7%) of total program costs. Inpatient and outpatient costs are the largest components of costs incurred by high-cost utilizers. Non-urgent emergency department costs are a relatively small portion. Average expenditure increases over time, particularly after expanded eligibility, and the share of costs incurred by the top 10% and 1% increases slightly. Multivariable logistic regression results indicate that infants and older teens, Caucasian children, and those with chronic conditions are more likely to be high-cost utilizers. Increased cost sharing does not reduce cost concentration or average expenditure among high-cost utilizers. These findings suggest that identifying and targeting potentially preventable costs among high-cost utilizers are called for to help reduce costs in public insurance programs.