The Impact of Medicaid Expansion Under the Affordable Care Act on the Gap Between American Indians and Whites in Breast Cancer Management and Prognosis.

BACKGROUND: Breast cancer (BC) death rates in the USA have not significantly declined for American Indians (AIs) in comparison to Whites. Our objective was to determine whether Medicaid Expansion as part of the Affordable Care Act led to improved BC outcomes for AIs relative to Whites. PATIENTS AND METHODS: Using the National Cancer Database, we conducted a retrospective cohort study. Included were BC patients who were AI and White; 40 to 64 years of age; diagnosed in 2009 to 2016; lived in states that expanded Medicaid in January 2014, and states that did not expand Medicaid. Our outcomes were stage at diagnosis, insurance status, timely treatment, and 3-year mortality. RESULTS: There were 359,484 newly diagnosed BC patients, 99.49% White, 0.51% AI. Uninsured rates declined more in the expansion states than in the nonexpansion states (OR = 0.44, 95% CI: 0.15-0.97, P < 0.001). Lower rates of Stage I BC diagnosis was found in AIs compared to Whites (46.58% vs. 55.33%, P < .001); these differential rates did not change after Medicaid expansion. Rates of definitive treatment initiation within 30 days of diagnosis declined after Medicaid expansion (P < .001); there was a smaller decline in the expansion states (OR 1.118, 95% CI: 1.09, 1.15, P < .001). Three year mortality was not different between expansion and nonexpansion states post Medicaid expansion. CONCLUSIONS: In newly diagnosed BCs, uninsured rates declined more in the states that expanded Medicaid in January 2014. Timely treatment post Medicaid expansion declined less in states that expanded Medicaid. There was no differential benefit of Medicaid expansion in the 2 races.

Social Risk and Dialysis Facility Performance in the First Year of the ESRD Treatment Choices Model.

Importance: The End-Stage Renal Disease Treatment Choices (ETC) model randomly selected 30% of US dialysis facilities to receive financial incentives based on their use of home dialysis, kidney transplant waitlisting, or transplant receipt. Facilities that disproportionately serve populations with high social risk have a lower use of home dialysis and kidney transplant raising concerns that these sites may fare poorly in the payment model. Objective: To examine first-year ETC model performance scores and financial penalties across dialysis facilities, stratified by their incident patients' social risk. Design, Setting, and Participants: A cross-sectional study of 2191 US dialysis facilities that participated in the ETC model from January 1 through December 31, 2021. Exposure: Composition of incident patient population, characterized by the proportion of patients who were non-Hispanic Black, Hispanic, living in a highly disadvantaged neighborhood, uninsured, or covered by Medicaid at dialysis initiation. A facility-level composite social risk score assessed whether each facility was in the highest quintile of having 0, 1, or at least 2 of these characteristics. Main Outcomes and Measures: Use of home dialysis, waitlisting, or transplant; model performance score; and financial penalization. Results: Using data from 125 984 incident patients (median age, 65 years [IQR, 54-74]; 41.8% female; 28.6% Black; 11.7% Hispanic), 1071 dialysis facilities (48.9%) had no social risk features, and 491 (22.4%) had 2 or more. In the first year of the ETC model, compared with those with no social risk features, dialysis facilities with 2 or more had lower mean performance scores (3.4 vs 3.6, P = .002) and lower use of home dialysis (14.1% vs 16.0%, P < .001). These facilities had higher receipt of financial penalties (18.5% vs 11.5%, P < .001), more frequently had the highest payment cut of 5% (2.4% vs 0.7%; P = .003), and were less likely to achieve the highest bonus of 4% (0% vs 2.7%; P < .001). Compared with all other facilities, those in the highest quintile of treating uninsured patients or those covered by Medicaid experienced more financial penalties (17.4% vs 12.9%, P = .01) as did those in the highest quintile in the proportion of patients who were Black (18.5% vs 12.6%, P = .001). Conclusions: In the first year of the Centers for Medicare & Medicaid Services' ETC model, dialysis facilities serving higher proportions of patients with social risk features had lower performance scores and experienced markedly higher receipt of financial penalties.

Trends in Emergency Department Visits Among People Younger Than Age 65 by Insurance Status: United States, 2010-2021.

Purpose-This report describes trends in emergency department visits among people younger than age 65 from 2010 through 2021, by health insurance status and selected demographic and hospital characteristics. Methods-Estimates in this report are based on data collected in the 2010-2021 National Hospital Ambulatory Medical Care Survey. Data were weighted to produce annual national estimates. Patient and hospital characteristics are presented by primary expected source of payment. Results-Private insurance and Medicaid were the most common primary expected sources of payment at emergency department visits by people younger than age 65 from 2010 through 2013. Medicaid was the most common primary expected source of payment from 2014 through 2021. Among children younger than age 18 years, the most common primary expected source of payment was Medicaid across the entire period. The percentage of visits by children with no insurance decreased from 7.4% in 2010 to 3.0% in 2021. Among adults, the percentage of visits with Medicaid increased from 25.5% in 2010 to 38.9% in 2021, and the percentage of visits by those with no insurance decreased from 24.6% to 11.1% during this period. Among Black non-Hispanic and Hispanic people, Medicaid was the most frequent primary expected source of payment during the entire period. Among White non-Hispanic people, private insurance was the most frequent primary expected source of payment through 2015, while private insurance and Medicaid were the most frequent primary expected sources of payment from 2016 through 2021.

Sociodemographic Factors in Pituitary Adenomas.

Pituitary adenomas have been increasingly detected in recent years, especially in the older population. Black patients have a higher incidence than other racial groups. In patients with functioning tumors, presentation and comorbidities are influenced by age and sex, whereas the impact of ethnoracial background is unclear. Active surveillance recommendation and surgery refusal disproportionally affect Black and older patients. The likelihood of surgery at high-volume centers is lower for patients of Black or Hispanic background, uninsured or with lower socioeconomic status. Multicentric studies are necessary to delineate the influence of sociodemographic factors according to the adenoma type and to address the causes of health care disparities.

Disparities in refusal of surgery for gynecologic cancer.

OBJECTIVE: To identify sociodemographic and clinical factors associated with refusal of gynecologic cancer surgery and to estimate its effect on overall survival. METHODS: The National Cancer Database was surveyed for patients with uterine, cervical or ovarian/fallopian tube/primary peritoneal cancer treated between 2004 and 2017. Univariate and multivariate logistic regression were used to assess associations between clinico-demographic variables and refusal of surgery. Overall survival was estimated using the Kaplan-Meier method. Trends in refusal over time were evaluated using joinpoint regression. RESULTS: Of 788,164 women included in our analysis, 5875 (0.75%) patients refused surgery recommended by their treating oncologist. Patients who refused surgery were older at diagnosis (72.4 vs 60.3 years, p < 0.001) and more likely Black (OR 1.77 95% CI 1.62-1.92). Refusal of surgery was associated with uninsured status (OR 2.94 95% CI 2.49-3.46), Medicaid coverage (OR 2.79 95% CI 2.46-3.18), low regional high school graduation (OR 1.18 95% CI 1.05-1.33) and treatment at a community hospital (OR 1.59 95% CI 1.42-1.78). Patients who refused surgery had lower median overall survival (1.0 vs 14.0 years, p < 0.01) and this difference persisted across disease sites. Between 2008 and 2017, there was a significant increase in refusal of surgery annually (annual percent change +1.41%, p < 0.05). CONCLUSIONS: Multiple social determinants of health are independently associated with refusal of surgery for gynecologic cancer. Given that patients who refuse surgery are more likely from vulnerable, underserved populations and have inferior survival, refusal of surgery should be considered a surgical healthcare disparity and tackled as such.

Association of Gaps in Health Insurance Coverage With Unmet Needs for Vision Care Among Adults in Ohio.

Importance: Access to vision care is vital to diagnose and treat vision impairment and diseases. Previous studies found that currently uninsured adults have limited access to vision care. It is unclear whether a recent history (past 12 months) of gaps in insurance coverage likewise adversely affects access to vision care. Objective: To determine whether gaps in insurance coverage within the past 12 months are associated with higher risk of unmet needs for vision care among adults in Ohio. Design, Setting, and Participants: This cross-sectional study analyzed data for adults in Ohio from the 2021 Ohio Medicaid Assessment Survey (OMAS), which is conducted via web, telephone, and mail. Participants were residents 19 years or older who reported needing vision care or eyeglasses within the past 12 months. Exposures: Insurance coverage over the past 12 months, classified as continuous private, continuous public, gap in coverage, or year-round uninsured. Main Outcomes and Measure: Self-reported unmet need for vision care over the past 12 months. Results: Based on a sample of 19 036 participants, we calculated that 4% of adults experienced recent coverage gaps (weighted total in the population, 180 259 of 4 518 841) while another 4% were year-round uninsured (187 552 adults). Unmet needs for vision care were reported by 13% (590 015 adults). On multivariable logistic regression, adults with gaps in coverage were at a higher risk of unmet vision care needs compared with adults who had continuous private coverage (odds ratio [OR], 2.9; 95% CI, 2.1-3.9; P < .001) or continuous public coverage (OR, 1.7; 95% CI, 1.3-2.4; P = .001). Conclusions and Relevance: This study found that gaps in health insurance coverage were associated with increased risk of unmet vision care needs among adults in Ohio compared with continuous private or public coverage. Policies that protect the continuity of health insurance coverage may help reduce the rate of unmet needs for vision care.

The association of health insurance and race with treatment and survival in patients with metastatic colorectal cancer.

BACKGROUND: Black patients and underinsured patients with colorectal cancer (CRC) present with more advanced disease and experience worse outcomes. The study aim was to evaluate the interaction of health insurance status and race with treatment and survival in metastatic CRC. MATERIALS AND METHODS: Patients diagnosed with metastatic CRC within NCDB from 2006-2016 were included. Primary outcomes included receipt of chemotherapy and 3-year all-cause mortality. Multivariable logistic regression and Cox-regression (MVR) including a two-way interaction term of race and insurance were performed to evaluate the differential association of race and insurance with receipt of chemotherapy and mortality, respectively. RESULTS: 128,031 patients were identified; 70.6% White, 14.4% Black, 5.7% Hispanic, and 9.3% Other race. Chemotherapy use was higher among White compared to Black patients. 3-year mortality rate was higher for Blacks and lower for Hispanics, in comparison with White patients. By MVR, Black patients were less likely to receive chemotherapy. When stratified by insurance status, Black patients with private and Medicare insurance were less likely to receive chemotherapy than White patients. All-cause mortality was higher in Black patients and lower in Hispanic patients, and these differences persisted after controlling for insurance and receipt of chemotherapy. CONCLUSION: Black patients and uninsured or under-insured patients with metastatic CRC are less likely to receive chemotherapy and have increased mortality. The effect of health insurance among Blacks and Whites differs, however, and improving insurance alone does not appear to fully mitigate racial disparities in treatment and outcomes.

Relationship between insurance status and interhospital transfers among cancer patients in the United States.

BACKGROUND: The relationship between insurance status and interhospital transfers has not been adequately researched among cancer patients. Hence this study aimed for understanding this relationship using a nationally representative database. METHODS: A retrospective analysis was conducted using National Inpatient Sample (NIS) data collected during 2010-2016 and included all cancer hospitalization between 18 and 64 years of age. Interhospital transfers were compared based on insurance status (Medicare, Medicaid, private, and uninsured). Weighted multivariable logistic regressions were used to calculate the odds of interhospital transfers based on insurance status, after adjusting for many covariates. RESULTS: There were 3,580,908 weighted cancer hospitalizations, of which 72,353 (2.02%) had interhospital transfers. Uninsured patients had significantly higher rates of interhospital transfers, compared to those with Medicare (P = 0.005) and private insurance (P < 0.001). Privately insured patients had significantly lower rates of interhospital transfers, compared to those with Medicare (P < 0.001) and Medicaid (P < 0.001). Logistic regression analyses showed that the odds of having interhospital transfers were significantly higher among uninsured (adjusted odds ratio [aOR], 1.57, 95% CI: 1.45-1.69), Medicare (aOR, 1.38, 95% CI: 1.32-1.45) and Medicaid (aOR, 1.23, 95% CI: 1.16-1.30) patients when compared to those with private insurance coverages. CONCLUSION: Among cancer patients, uninsured and Medicare and Medicaid beneficiaries were more likely to experience interhospital transfers. In addition to medical reasons, factors such as affordability and socioeconomic status are influencing interhospital transfer decisions, indicating existing healthcare disparities. Further studies should focus on identifying the causal associations between factors explored in this study as well as additional unexplored factors.

Phenotype Discovery and Geographic Disparities of Late-Stage Breast Cancer Diagnosis across U.S. Counties: A Machine Learning Approach.

BACKGROUND: Disparities in the stage at diagnosis for breast cancer have been independently associated with various contextual characteristics. Understanding which combinations of these characteristics indicate highest risk, and where they are located, is critical to targeting interventions and improving outcomes for patients with breast cancer. METHODS: The study included women diagnosed with invasive breast cancer between 2009 and 2018 from 680 U.S. counties participating in the Surveillance, Epidemiology, and End Results program. We used a machine learning approach called Classification and Regression Tree (CART) to identify county "phenotypes," combinations of characteristics that predict the percentage of patients with breast cancer presenting with late-stage disease. We then mapped the phenotypes and compared their geographic distributions. These findings were further validated using an alternate machine learning approach called random forest. RESULTS: We discovered seven phenotypes of late-stage breast cancer. Common to most phenotypes associated with high risk of late-stage diagnosis were high uninsured rate, low mammography use, high area deprivation, rurality, and high poverty. Geographically, these phenotypes were most prevalent in southern and western states, while phenotypes associated with lower percentages of late-stage diagnosis were most prevalent in the northeastern states and select metropolitan areas. CONCLUSIONS: The use of machine learning methods of CART and random forest together with geographic methods offers a promising avenue for future disparities research. IMPACT: Local interventions to reduce late-stage breast cancer diagnosis, such as community education and outreach programs, can use machine learning and geographic modeling approaches to tailor strategies for early detection and resource allocation.

Underinsurance Among Children in the United States.

OBJECTIVES: We describe the change in the percentage of children lacking continuous and adequate health insurance (underinsurance) from 2016 to 2019. We also examine the relationships between child health complexity and insurance type with underinsurance. METHODS: Secondary analysis of US children in the National Survey of Children's Health combined 2016-2019 dataset who had continuous and adequate health insurance. We calculated differences in point estimates, with 95% confidence intervals (CIs), to describe changes in our outcomes over the study period. We used multivariable logistic regression adjusted for sociodemographic characteristics and examined relationships between child health complexity and insurance type with underinsurance. RESULTS: From 2016 to 2019, the proportion of US children experiencing underinsurance rose from 30.6% to 34.0% (+3.4%; 95% CI, +1.9% to +4.9%), an additional 2.4 million children. This trend was driven by rising insurance inadequacy (24.8% to 27.9% [+3.1%; 95% CI, +1.7% to +4.5%]), which was mainly experienced as unreasonable out-of-pocket medical expenses. Although the estimate of children lacking continuous insurance coverage rose from 8.1% to 8.7% (+0.6%), it was not significant at the 95% CI (-0.5% to +1.7%). We observed significant growth in underinsurance among White and multiracial children, children living in households with income ≥200% of the federal poverty limit, and those with private health insurance. Increased child health complexity and private insurance were significantly associated with experiencing underinsurance (adjusted odds ratio, 1.9 and 3.5, respectively). CONCLUSIONS: Underinsurance is increasing among US children because of rising inadequacy. Reforms to the child health insurance system are necessary to curb this problem.

Insurance coverage change and survivorship care among young adult survivors of childhood cancer.

OBJECTIVE: To (1) characterize change in type of insurance coverage among childhood cancer survivors from diagnosis to survivorship and (2) examine whether insurance change is associated with cancer-related follow-up care utilization. DATA SOURCES: Participants in this study were derived from the Project Forward study, a population-based, observational study of childhood cancer survivors in Los Angeles County that used California Cancer Registry data to identify participants. STUDY DESIGN: Multivariable logistic regression models incorporating survey nonresponse weights estimated the change in the marginal predicted probabilities of insurance change and survivorship care, adjusting for demographic, socioeconomic, and clinical covariates and clustering by treating hospital. DATA COLLECTION/EXTRACTION METHODS: Study participants were diagnosed with cancer who were younger than age 20 years while living in Los Angeles County from 1996 to 2010 and were older than the age 18 years at the time of survey participation, from 2015 to 2017 (N = 1106). PRINCIPAL FINDINGS: Most participants were 18-26 years of age, male, diagnosed before 2004, Hispanic/Latino race/ethnicity, single, without children, highly educated, not employed full time, and lived with their parents at survey. Almost half (N = 529) of participants experienced insurance change from diagnosis to survivorship. Insurance change was associated with insurance coverage at diagnosis, as those who were uninsured were most likely to experience change and gain coverage during survivorship (by 51 percentage points [ppt], standard error [SE] of 0.05). Survivors who experienced any change had decreased probability of reporting a recent cancer-related follow-up care visit, a disparity that was magnified for those who lost insurance coverage (-5 ppt, SE 0.02 for those who gained coverage; -15 ppt, SE 0.04 for those who lost coverage). CONCLUSIONS: Insurance coverage change was associated with lower cancer-related follow-up care utilization. Indeed, survivors who experienced any insurance coverage change had decreased probability of having a cancer-related follow-up care visit, and this was magnified for those who lost their insurance coverage.

Insurance type is associated with appropriate use of surgical and adjuvant care for differentiated thyroid carcinoma.

BACKGROUND: We aimed to characterize the association between differentiated thyroid cancer (DTC) patient insurance status and appropriateness of therapy (AOT) regarding extent of thyroidectomy and radioactive iodine (RAI) treatment. METHODS: The National Cancer Database was queried for DTC patients diagnosed between 2010 and 2016. Adjusted odds ratios (AOR) for AOT, as defined by the American Thyroid Association guidelines, and hazard ratios (HR) for overall survival (OS) were calculated. A difference-in-differences (DD) analysis examined the association of Medicaid expansion with outcomes for low-income patients aged <65. RESULTS: A total of 224,500 patients were included. Medicaid and uninsured patients were at increased risk of undergoing inappropriate therapy, including inappropriate lobectomy (Medicaid 1.36, 95% confidence interval [CI]: 1.21-1.54; uninsured 1.30, 95% CI: 1.05-1.60), and under-treatment with RAI (Medicaid 1.20, 95% CI: 1.14-1.26; uninsured 1.44, 95% CI: 1.33-1.55). Inappropriate lobectomy (HR 2.0, 95% CI: 1.7-2.3, P < .001) and under-treatment with RAI (HR 2.3, 95% CI: 2.2-2.5, P < .001) were independently associated with decreased survival, while appropriate surgical resection (HR 0.3, 95% CI: 0.3-0.3, P < .001) was associated with improved odds of survival; the model controlled for all relevant clinico-pathologic variables. No difference in AOT was observed in Medicaid expansion versus non-expansion states with respect to surgery or adjuvant RAI therapy. CONCLUSION: Medicaid and uninsured patients are at significantly increased odds of receiving inappropriate treatment for DTC; both groups are at a survival disadvantage compared with Medicare and those privately insured.

A Retrospective Cohort Study on Health Insurance: Related Disparities in Trauma Patients After Penetrating Injuries: 2000-2014.

OBJECTIVE: Although the lack of health insurance has been linked to poor health outcomes in several diseases, this relationship is still understudied in trauma. There exist differences between the Puerto Rico health care system and that of the United States. We therefore aimed to assess mortality disparities related to insurance coverage at the Puerto Rico Trauma Hospital (PRTH). METHODS: A retrospective cohort study of patients who sustained penetrating injuries (presenting at the PRTH from 2000 to 2014) was performed. Individuals were classified by their insurance status. Study variables comprised demographics, clinical characteristics and outcomes. A logistic regression analysis was performed to identify the association between health insurance status and risk of dying. RESULTS: Patients with public health insurance experienced more complications than did individuals who had private health insurance (PrHI) or who were uninsured. This group had longer durations of mechanical ventilation and spent more time in the hospital than did patients who had PrHI or who were uninsured. However, uninsured patients with gunshot wounds were 54% (adjusted odds ratio = 1.54; 95% CI: 1.01, 2.36) more likely to die than were their counterparts who had PrHI. CONCLUSION: Our study suggests that having health insurance could reduce a given patient mortality risk in trauma settings. More studies with larger samples are warranted to confirm these findings. If these findings hold true, then providing equitable access to health services for the entire population could prevent patients suffering trauma from having premature, preventable deaths.

Association Between Medicaid Expansion and Suicide Mortality Among Nonelderly US Adults.

In 2014, the Affordable Care Act gave states the option to expand Medicaid coverage to nonelderly adults (persons aged 18-64 years) with incomes up to 138% of the federal poverty level. To our knowledge, the association of Medicaid expansion with suicide, a leading cause of death in the United States, has not been examined. We used 2005-2017 data from the National Violent Death Reporting System to analyze suicide mortality in 8 Medicaid expansion states and 7 nonexpansion states. Using a difference-in-differences approach, we examined the association between Medicaid expansion and the rate of suicide death (number of deaths per 100,000 population) among nonelderly adults. After adjustment for state-level confounders, Medicaid expansion states had 1.2 fewer suicide deaths (ß = -1.2, 95% confidence interval: -2.5, 0.1) per 100,000 population per year during the postexpansion period than would have been expected if they had followed the same trend in suicide rates as nonexpansion states. Medicaid expansion was associated with reductions in suicide rates among women, men, persons aged 30-44 years, non-Hispanic White individuals, and persons without a college degree. Medicaid expansion was not associated with a change in suicide rates among persons aged 18-29 or 45-64 years or among non-White or Hispanic individuals. Overall, Medicaid expansion was associated with reductions in rates of suicide death among nonelderly adults. Further research on inequities in Medicaid expansion benefits is needed.

Improving estimates of Medicaid's effect on poverty: Measures and counterfactuals.

OBJECTIVE: To re-evaluate the effect of Medicaid on poverty using a poverty measure that accounts for health insurance needs and benefits and an evaluation approach that reflects disparities in access to alternative coverage. DATA SOURCES: The Current Population Survey (CPS) for calendar year 2015. STUDY DESIGN: We estimate the effect of losing Medicaid on poverty, combining two previous approaches: (1) A propensity impact, which simulates a no-Medicaid counterfactual incorporating changes to health insurance and medical out-of-pocket spending, using the Supplemental Poverty Measure (SPM). This measure does not reflect a need for health care access nor how health benefits meet that need. (2) An accounting impact, which assumes that those losing Medicaid remain uninsured and does not incorporate any behavioral changes, using the health-inclusive poverty measure (HIPM). This measure includes a need for health insurance in the threshold and health insurance benefits in resources. DATA COLLECTION/EXTRACTION METHODS: Not applicable. PRINCIPAL FINDINGS: Using the propensity-matched approach, we attributed a 2.5 percentage point reduction in health-inclusive poverty among those younger than age 65 to the Medicaid program, between the 1.0-point SPM propensity-match impact and the 3.9-point HIPM accounting impact. Medicaid's antipoverty impact and HIPM-SPM differences are greater among those who would become uninsured. HIPM propensity-matched estimates reveal much larger impacts of Medicaid on poverty disparities linked to race/ethnicity and single parenthood than SPM-based propensity estimates. CONCLUSIONS: Both the poverty measure and the method used to estimate the counterfactual make substantial, policy-relevant differences to estimates of Medicaid's impact on poverty. A poverty measure that fails to incorporate health insurance needs and benefits substantially underestimates Medicaid's effect. Failing to consider adjustments in insurance coverage and out-of-pocket spending substantially overestimates Medicaid's effect and underestimates its reduction of disparities.

Health services utilization, out-of-pocket expenditure, and underinsurance among insured non-elderly cancer survivors in the United States, 2011-2015.

BACKGROUND: High out-of-pocket (OOP) expenditure and inadequate insurance coverage may adversely affect cancer survivors. We aimed to characterize the extent and correlates of healthcare utilization, OOP expenditures, and underinsurance among insured cancer survivors. METHODS: We used 2011-2015 Medical Expenditure Panel Survey data to identify a nationally representative sample of insured non-elderly adult (age 18-64 years) cancer survivors. We used negative binomial, two-part (logistic and Generalized Linear Model with log link and gamma distribution), and logistic regression models to quantify healthcare utilization, OOP expenditures, and underinsurance, respectively, and identified sociodemographic correlates for each outcome. RESULTS: We identified 2738 insured non-elderly cancer survivors. Adjusted average utilization of ambulatory, non-ambulatory, prescription medication, and dental services was 14.4, 0.51, 24.9, and 1.4 events per person per year, respectively. Higher ambulatory and dental services utilization were observed in older adults, females, non-Hispanic Whites, survivors with a college degree and high income, compared to their counterparts. Nearly all (97.7%) survivors had some OOP expenditures, with a mean adjusted OOP expenditure of $1552 per person per year. Adjusted mean OOP expenditures for ambulatory, non-ambulatory, prescription medication, dental, and other health services were $653, $161, $428, $194, and $83, respectively. Sociodemographic variations in service-specific OOP expenditures were generally consistent with respective utilization patterns. Overall, 8.8% of the survivors were underinsured. CONCLUSION: Many insured non-elderly cancer survivors allocate a substantial portion of their OOP expenditure for healthcare-related services and experience financial vulnerability, resulting in nearly 8.8% of the survivors being underinsured. Utilization of healthcare services varies across sociodemographic groups.

Dropping out of voluntary community-based health insurance in rural Uganda: Evidence from a cross-sectional study in rural south-western Uganda.

AIM: Community Based Health Insurance (CBHI) schemes have become central to health systems financing as avenues of achieving universal health coverage in developing countries. Yet, while emphasis in research and policy has mainly concentrated on enrolment, very little has been apportioned to high rates of dropping out after initial enrolment. The main aim of this study is to understand the factors behind CBHI dropping out through a cross-sectional quantitative research design to gain insights into curtailing the drop out of CBHI in Uganda. METHODS: The survey for the quantitative research component took place between August 2015 and March 2016 covering 464 households with under-5 children in south-western Uganda. To understand the factors associated with dropping out of CBHI, we employ a multivariate logistic regression on a subsample of 251 households who were either currently enrolled or had enrolled at one time and later dropped out. RESULTS: Overall, we find that 25.1 percent of the households that had ever enrolled in insurance reported dropping out. Household socioeconomic status (wealth) was one of the key factors that associated with dropping out. Larger household sizes and distance from the hospital were significantly associated with dropping out. More socially connected households were less likely to drop out revealing the influence of community social capital in keeping households insured. CONCLUSION: The findings have implications for addressing equity and inclusion concerns in community-based health insurance programmes such as one in south-western Uganda. Even when community based informal system aim for inclusion of the poorest, they are not enough and often the poorest of the poor slip into the cracks and remain uninsured or drop out. Moreover, policy interventions toward curtailing high dropout rates should be considered to ensure financial sustainability of CBHI schemes.