What Explains Inequalities in Telehealth Utilization Among North Carolina Medicaid Beneficiaries?

Background: Increased availability of telehealth can improve access to health care. However, there is evidence of persistent disparities in telehealth usage, as well as among people from minoritized racial and ethnic groups and rural residents. The objective of our work was to explore the degree to which disparities in telehealth use for behavioral health (BH) and musculoskeletal (MSK) related services during the COVID-19 pandemic are explained by observed beneficiary- and area-level characteristics. Methods: Using North Carolina Medicaid claims data of Medicaid beneficiaries with BH or MSK conditions, we apply nonlinear regression-based decomposition analysis-based models developed by Kitagawa, Oaxaca, and Blinder to determine which observed variables are associated with racial, ethnic, and rural inequalities in telehealth usage. Results: In the BH cohort, we found statistically significant differences in telehealth usage by race in the adult population, and by race, Hispanic ethnicity, and rurality in the pediatric population. In the MSK cohort, we found significant inequities by Hispanic ethnicity and rurality among adults, and by race and rurality among children. Inequalities in telehealth use between groups were small, ranging from 0.7 percentage points between urban and rural adults with MSK conditions to 3.8 percentage points between white adults and people of color among those with BH conditions. Overall, we found that racial and ethnic inequalities in telehealth use are not well explained by the observed variables in our data. Rural disparities in telehealth use are better explained by observed variables, particularly area-level broadband internet use. Conclusions: For inequalities between rural and urban residents, our analysis provides observational evidence that infrastructure such as broadband internet access is an important driver of differences in telehealth use. For racial and ethnic inequalities, the pathways may be more complex and difficult to measure, particularly when relying on administrative data sources in place of more detailed data on individual-level socioeconomic factors.

Addressing Housing-Related Social Needs Through Medicaid: Lessons From North Carolina's Healthy Opportunities Pilots Program.

North Carolina Medicaid's Healthy Opportunities Pilots program is the country's first comprehensive program to evaluate the impact of paying community-based organizations to provide eligible Medicaid enrollees with an array of evidence-based services to address four domains of health-related social needs, one of which is housing. Using a mixed-methods approach, we mapped the distribution of severe housing problems and then examined the design and implementation of Healthy Opportunities Pilots housing services in the three program regions. Four cross-cutting implementation and policy themes emerged: accounting for variation in housing resources and needs to address housing insecurity, defining and pricing housing services in Medicaid, engaging diverse stakeholders across sectors to facilitate successful implementation, and developing sustainable financial models for delivery. The lessons learned and actionable insights can help inform the efforts of stakeholders elsewhere, particularly other state Medicaid programs, to design and implement cross-sectoral programs that address housing-related social needs by leveraging multiple policy-based resources. These lessons can also be useful for federal policy makers developing guidance on addressing housing-related needs in Medicaid.

Describing Perspectives of Telehealth and the Impact on Equity in Access to Health Care from Community and Provider Perspectives: A Multimethod Analysis.

Introduction: The rapid adoption of telehealth as a result of the COVID-19 pandemic provided the opportunity to examine perceptions of health care access and use of telehealth for delivery of effective and equitable care in low-income and historically marginalized communities. Methods: Focusing on communities with high social vulnerability, a multimethod analysis of combined perspectives, collected February through August 2022 from 112 health care providers, obtained from surveys and interviews, and 23 community members via 3 focus groups on access to care and telehealth. Qualitative data were analyzed using the Health Equity and Implementation Framework to identify barriers, facilitators, and recommendations for the implementation of telehealth using a health equity lens. Results: Participants perceived that telehealth helped maintain access to health care during the pandemic by addressing barriers including provider shortages, transportation concerns, and scheduling conflicts. Additional benefits suggested were improved care quality and coordination attributed to convenient avenues for care delivery and communication among providers and patients. However, many barriers to telehealth were reported and considered to limit equitable access to care. These included restrictive or changing policies regarding allowable services provided via telehealth, and availability of technology and broadband services to enable telehealth visits. Recommendations provided insight into care delivery innovation opportunities and potential policy changes to address equitable access to care. Conclusion: Integration of telehealth into models of care delivery could improve access to health care services and promote communication among providers and patients to improve care quality. Our findings have implications that are critical for future policy reforms and telehealth research.

Evaluating Telehealth Uptake Among North Carolina Medicaid Beneficiaries With Musculoskeletal Conditions: Insights From the COVID-19 Pandemic.

BACKGROUND: The shift from in-person to virtual visits, known as telehealth (TH), during the COVID-19 pandemic was a significant change for North Carolina (NC) Medicaid beneficiaries seeking treatment for musculoskeletal (MSK) conditions, as remote care for these conditions was previously unavailable. We used this policy change to investigate factors associated with TH uptake and whether TH availability mitigated disparities in access to care or affected emergency department (ED) visits among these beneficiaries. RESEARCH DESIGN: Using 2019-2021 NC Medicaid claims, we identified beneficiaries receiving treatment for MSK conditions before COVID-19 (March 2019-February 2020) and analyzed uptake of newly available TH during COVID-19 (April 2020-March 2021). We used descriptive analysis and Poisson generalized estimating equations to quantify TH uptake, factors associated with TH uptake, and the association with ED visits during COVID-19. RESULTS: Black and Hispanic beneficiaries were less likely to use TH compared with White and non-Hispanic counterparts (10%, P <0.001 and 20%, P =0.03, respectively). Adults eligible for Tailored Plans, specialized NC Medicaid plans for those with significant behavioral health needs or intellectual/developmental disabilities, were less likely to use TH [adjusted risk ratio (ARR):0.83, 95% CI (0.78, 0.87)]; youth eligible for Tailored Plans were more likely to use TH [ARR:1.28, 95% CI (1.16, 1.42)]. Lower county-level internet access was associated with lower TH use [ARR: 0.85, 95% CI (0.82, 0.99)]. No statistical difference in ED utilization was observed between TH users and non-users. CONCLUSIONS: TH has the potential to deliver convenient care to beneficiaries with MSK conditions who can access it. Further research and policy changes should explore and address underlying factors driving disparities and improve equitable access to care for this population.

Telehealth Utilization Among Adult Medicaid Beneficiaries in North Carolina with Behavioral Health Conditions During the COVID-19 Pandemic.

OBJECTIVE: We examined factors associated with telehealth utilization during COVID-19 among adult Medicaid beneficiaries with behavioral health conditions. DATA SOURCES AND STUDY SETTING: NC Medicaid 2019-2021 beneficiary and claims data. STUDY DESIGN: This retrospective cohort study examined and compared behavioral health service use pre-COVID-19 (03/01/2019 to 02/28/2020) and during COVID-19 (04/01/2020 to 03/31/2021). Telehealth users included those with at least one behavioral health visit via telehealth during COVID-19. Descriptive statistics were calculated for overall sample and by telehealth status. Multilevel modified Poisson generalized estimating equation examined associations between telehealth use and patient- and area-level characteristics. DATA COLLECTION/EXTRACTION METHODS: We identified individuals ages ≥ 21-64, diagnosed with a behavioral health condition, and had at least one behavioral-health specific visit before COVID-19. PRINCIPAL FINDINGS: Almost two-thirds of the cohort received behavioral health services during COVID-19, with half of these beneficiaries using telehealth. Non-telehealth users had steeper declines in service use from pre- to during COVID-19 compared to telehealth users. Beneficiaries identifying as Black, multiracial or other were significantly less likely to use telehealth (ARR = 0.86; 95% CI: (0.83, 0.89)); (ARR = 0.92; 95% CI: (0.87, 0.96)) compared to White beneficiaries. Those eligible for Medicaid through the blind/disabled programs and who qualified for a state-specific specialized behavioral health plan were more likely to use telehealth (17% and 20%, respectively). CONCLUSIONS: During the pandemic, telehealth facilitated continuity of care for beneficiaries with behavioral health conditions. Future research should aim to investigate how to reduce the digital divide and ensure equitable access to telehealth.

Health Care Use and Spending Among Need-Based Subgroups of Medicare Beneficiaries With Full Medicaid Benefits.

Importance: Beneficiaries dual eligible for Medicare and Medicaid account for a disproportionate share of expenditures due to their complex care needs. Lack of coordination between payment programs creates misaligned incentives, resulting in higher costs, fragmented care, and poor health outcomes. Objective: To inform the design of integrated programs by describing the health care use and spending for need-based subgroups in North Carolina's full benefit, dual-eligible population. Design, Setting, and Participants: This cross-sectional study using Medicare and North Carolina Medicaid 100% claims data (2014-2017) linked at the individual level included Medicare beneficiaries with full North Carolina Medicaid benefits. Data were analyzed between 2021 and 2022. Exposure: Need-based subgroups: community well, home- and community-based services (HCBS) users, nursing home (NH) residents, and intensive behavioral health (BH) users. Measures: Medicare and Medicaid utilization and spending per person-year (PPY). Results: The cohort (n = 333 240) comprised subgroups of community well (64.1%, n = 213 667), HCBS users (15.0%, n = 50 095), BH users (15.2%, n = 50 509), and NH residents (7.5%, n = 24 927). Overall, 61.1% reported female sex. The most common racial identities included Asian (1.8%), Black (36.1%), and White (58.7%). Combined spending for Medicare and Medicaid was $26 874 PPY, and the funding of care was split evenly between Medicare and Medicaid. Among need-based subgroups, combined spending was lowest among community well at $19 734 PPY with the lowest portion (38.5%) of spending contributed by Medicaid ($7605). Among NH residents, overall spending ($68 359) was highest, and the highest portion of spending contributed by Medicaid (70.1%). Key components of spending among HCBS users' combined total of $40 069 PPY were clinician services on carrier claims ($14 523) and outpatient facility services ($9012). Conclusions and relevance: Federal and state policy makers and administrators are developing strategies to integrate Medicare- and Medicaid-funded health care services to provide better care to the people enrolled in both programs. Substantial use of both Medicare- and Medicaid-funded services was found across all need-based subgroups, and the services contributing a high proportion of the total spending differed across subgroups. The diversity of health care use suggests a tailored approach to integration strategies with comprehensive set benefits that comprises Medicare and Medicaid services, including long-term services and supports, BH, palliative care, and social services.

Comparing health care use and costs among new Medicaid enrollees before and during the COVID-19 pandemic.

BACKGROUND AND OBJECTIVE: To characterize health care use and costs among new Medicaid enrollees before and during the COVID pandemic. Results can help Medicaid non-expansion states understand health care use and costs of new enrollees in a period of enrollment growth. RESEARCH DESIGN: Retrospective cross-sectional analysis of North Carolina Medicaid claims data (January 1, 2018 - August 31, 2020). We used modified Poisson and ordinary least squares regression analysis to estimate health care use and costs as a function of personal characteristics and enrollment during COVID. Using data on existing enrollees before and during COVID, we projected the extent to which changes in outcomes among new enrollees during COVID were pandemic-related. SUBJECTS: 340,782 new enrollees pre-COVID (January 2018 - December 2019) and 56,428 new enrollees during COVID (March 2020 - June 2020). MEASURES: We observed new enrollees for 60-days after enrollment to identify emergency department (ED) visits, nonemergent ED visits, primary care visits, potentially-avoidable hospitalizations, dental visits, and health care costs. RESULTS: New Medicaid enrollees during COVID were less likely to have an ED visit (-46 % [95 % CI: -48 %, -43 %]), nonemergent ED visit (-52 % [95 % CI: -56 %, -48 %]), potentially-avoidable hospitalization (-52 % [95 % CI: -60 %, -43 %]), primary care visit (-34 % [95 % CI: -36 %, -33 %]), or dental visit (-36 % [95 % CI: -41 %, -30 %]). They were also less likely to incur any health care costs (-29 % [95 % CI: -30 %, -28 %]), and their total costs were 8 % lower [95 % CI: -12 %, -4 %]. Depending on the outcome, COVID explained between 34 % and 100 % of these reductions. CONCLUSIONS: New Medicaid enrollees during COVID used significantly less care than new enrollees pre-COVID. Most of the reduction stems from pandemic-related changes in supply and demand, but the profile of new enrollees before versus during COVID also differed.

Association Of Unemployment With Medicaid Enrollment By Social Vulnerability In North Carolina During COVID-19.

The COVID-19 pandemic precipitated an unemployment crisis in the US that surpassed the Great Recession of 2007-09 within the first three months of the pandemic. This article builds on the limited early evidence of the relationship between the pandemic and health insurance coverage, using county-level unemployment and Medicaid enrollment data from North Carolina, a large state that did not expand Medicaid. We used linear and county fixed effects models to assess this relationship, accounting for county-level social vulnerability, physical and virtual access to Medicaid enrollment, and COVID-19 case burden. Using data from January 2018 through August 2020, we estimated that the passthrough rate-the share of unemployed people who gained Medicaid coverage-was approximately 15 percent statewide but higher in more socially vulnerable counties. This low passthrough rate during a period of increased unemployment resulting from the COVID-19 pandemic means that Medicaid was unable to completely fulfill its countercyclical role, in which it grows to meet greater need during periods of widespread economic hardship, because of North Carolina's stringent Medicaid eligibility criteria. Working toward greater adoption of Medicaid expansion may help ensure that the US is better prepared for the next crisis by ensuring access to health insurance coverage.

State variation in effects of state social distancing policies on COVID-19 cases.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) sickened over 20 million residents in the United States (US) by January 2021. Our objective was to describe state variation in the effect of initial social distancing policies and non-essential business (NEB) closure on infection rates early in 2020. METHODS: We used an interrupted time series study design to estimate the total effect of all state social distancing orders, including NEB closure, shelter-in-place, and stay-at-home orders, on cumulative COVID-19 cases for each state. Data included the daily number of COVID-19 cases and deaths for all 50 states and Washington, DC from the New York Times database (January 21 to May 7, 2020). We predicted cumulative daily cases and deaths using a generalized linear model with a negative binomial distribution and a log link for two models. RESULTS: Social distancing was associated with a 15.4% daily reduction (Relative Risk = 0.846; Confidence Interval [CI] = 0.832, 0.859) in COVID-19 cases. After 3 weeks, social distancing prevented nearly 33 million cases nationwide, with about half (16.5 million) of those prevented cases among residents of the Mid-Atlantic census division (New York, New Jersey, Pennsylvania). Eleven states prevented more than 10,000 cases per 100,000 residents within 3 weeks. CONCLUSIONS: The effect of social distancing on the infection rate of COVID-19 in the US varied substantially across states, and effects were largest in states with highest community spread.

Medicaid Coverage Disruptions Among Children Enrolled in North Carolina Medicaid From 2016 to 2018.

Importance: Brief disruptions in insurance coverage among eligible participants are associated with poorer health outcomes for children. Objective: To describe factors associated with coverage disruptions among children enrolled in North Carolina Medicaid from 2016 to 2018 and estimate the outcome of preventing such disruptions on medical expenditures. Design Setting and Participants: This was a retrospective cohort study using North Carolina Medicaid claims data. All enrolled individuals were aged 1 to 20 years on January 1, 2016, and with 30 days of prior continuous enrollment. Children were observed from January 1, 2016, until December 31, 2018. Analyses were conducted from June 2020 through December 2020. Main Outcomes and Measures: Risk of Medicaid coverage disruptions of 1 to less than 12 months was assessed. Among children who disenrolled from Medicaid for 30 or more days, the risk of reenrollment within 1 to 6 months and 7 to 11 months was assessed. An inverse probability of censoring weights method was then used to estimate the outcome of an intervention to reduce coverage disruptions through preventing disenrollment on per member per month (PMPM) cost. Results: The study population included 831 173 Medicaid beneficiaries aged 1 to 5 years (23%), 6 to 17 years (68%), and 18 to 20 years (9%); 35% were Black, 44% were White, and 14% were Hispanic/Latinx. Among those with a first disenrollment (n = 214 401, 26%), the risk of reenrollment within 6 months and 7 to 11 months was 19% and 7%, respectively. Risk of coverage disruption was higher for Black children (hazard ratio [HR], 1.21; 95% CI, 1.18-1.24), children of other races (Asian, American Indian, Hawaiian or Pacific Islander, multiple races, or unreported; HR, 1.37; 95% CI, 1.33-1.40), and Latinx children (HR, 1.65; 95% CI, 1.60-1.70) compared with White children. Risk of coverage disruption was also higher for children with higher medical complexity (HR, 1.15; 95% CI, 1.12-1.19). The risk of coverage disruption was lower for children living in counties with the highest unemployment rates (HR, 0.89; 95% CI, 0.85-0.94), and comparisons between county-level measures of child poverty and graduation rates showed little or no difference. The estimated PMPM cost for the full population under a scenario in which all medical costs were included was $125.73. Estimated PMPM cost for the full cohort in a counterfactual scenario in which disenrollment was prevented was slightly lower ($122.14). Across all subgroups, estimated PMPM costs were modestly lower ($2-$8) in the scenario in which disenrollment was prevented. Conclusions and Relevance: In this cohort study, the risk of Medicaid coverage disruption was high, with many eligible children in historically marginalized communities continuing to experience unstable enrollment. In addition to improving health outcomes, preventing coverage gaps through policies that decrease disenrollment may also reduce Medicaid costs.

Are Certain Health Centers Better Patient-Centered Medical Homes for People with Severe Mental Illness?

Patient-centered medical homes based at federally-qualified health centers (FQHCs) can benefit patients with complex health needs, such as severe mental illness (SMI). However, little is known about FQHC characteristics associated with changes in health care expenditures and utilization for individuals with SMI. Using North Carolina Medicaid claims and FQHC data from the Uniform Data System, multivariate regression identified FQHC characteristics associated with total expenditures, medication adherence and emergency department utilization among adults with SMI, controlling for time-invariant differences by health center. Few of the FQHC-level factors affected the outcomes-not even offering on-site behavioral health services. Although the FQHCs in the analysis sample exhibited considerable variation in the provision of specialty behavioral services and in staffing configurations, it may be the case that the examination of average effects across a heterogeneous group of adults with SMI mask benefits of FQHCs to certain subgroups. These findings support the conclusion that there is no "one-size-fits-all" model that works best for this diverse patient population. Study results are relevant for practices embarking on expanded medical home services for people with SMI.

Coincidence analysis: a new method for causal inference in implementation science.

BACKGROUND: Implementation of multifaceted interventions typically involves many diverse elements working together in interrelated ways, including intervention components, implementation strategies, and features of local context. Given this real-world complexity, implementation researchers may be interested in a new mathematical, cross-case method called Coincidence Analysis (CNA) that has been designed explicitly to support causal inference, answer research questions about combinations of conditions that are minimally necessary or sufficient for an outcome, and identify the possible presence of multiple causal paths to an outcome. CNA can be applied as a standalone method or in conjunction with other approaches and can reveal new empirical findings related to implementation that might otherwise have gone undetected. METHODS: We applied CNA to a publicly available dataset from Sweden with county-level data on human papillomavirus (HPV) vaccination campaigns and vaccination uptake in 2012 and 2014 and then compared CNA results to the published regression findings. RESULTS: The original regression analysis found vaccination uptake was positively associated only with the availability of vaccines in schools. CNA produced different findings and uncovered an additional solution path: high vaccination rates were achieved by either (1) offering the vaccine in all schools or (2) a combination of offering the vaccine in some schools and media coverage. CONCLUSIONS: CNA offers a new comparative approach for researchers seeking to understand how implementation conditions work together and link to outcomes.

The Past Decade of Paying for Value : From the Affordable Care Act to COVID-19.

The Affordable Care Act played a major role in transitioning American health care away from fee-for-service payment. We explore the spread of payment reforms since the implementation of the ACA, both nationally and in North Carolina; the corresponding effects on health care costs and quality; and further steps needed to achieve greater transformation.

Correction to: Comparing Associations of State Reopening Strategies with COVID-19 Burden.

In the original version of this paper, an author was misidentified. The corrected author listing appears here, and has been updated in the online version.

Comparing Associations of State Reopening Strategies with COVID-19 Burden.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) infected over 5 million United States (US) residents resulting in more than 180,000 deaths by August 2020. To mitigate transmission, most states ordered shelter-in-place orders in March and reopening strategies varied. OBJECTIVE: To estimate excess COVID-19 cases and deaths after reopening compared with trends prior to reopening for two groups of states: (1) states with an evidence-based reopening strategy, defined as reopening indoor dining after implementing a statewide mask mandate, and (2) states reopening indoor dining rooms before implementing a statewide mask mandate. DESIGN: Interrupted time series quasi-experimental study design applied to publicly available secondary data. PARTICIPANTS: Fifty United States and the District of Columbia. INTERVENTIONS: Reopening indoor dining rooms before or after implementing a statewide mask mandate. MAIN MEASURES: Outcomes included daily cumulative COVID-19 cases and deaths for each state. KEY RESULTS: On average, the number of excess cases per 100,000 residents in states reopening without masks is ten times the number in states reopening with masks after 8 weeks (643.1 cases; 95% confidence interval (CI) = 406.9, 879.2 and 62.9 cases; CI = 12.6, 113.1, respectively). Excess cases after 6 weeks could have been reduced by 90% from 576,371 to 63,062 and excess deaths reduced by 80% from 22,851 to 4858 had states implemented mask mandates prior to reopening. Over 50,000 excess deaths were prevented within 6 weeks in 13 states that implemented mask mandates prior to reopening. CONCLUSIONS: Additional mitigation measures such as mask use counteract the potential growth in COVID-19 cases and deaths due to reopening businesses. This study contributes to the growing evidence that mask usage is essential for mitigating community transmission of COVID-19. States should delay further reopening until mask mandates are fully implemented, and enforcement by local businesses will be critical for preventing potential future closures.

Half of Rural Residents at High Risk of Serious Illness Due to COVID-19, Creating Stress on Rural Hospitals.

PURPOSE: During the COVID-19 epidemic, it is critical to understand how the need for hospital care in rural areas aligns with the capacity across states. METHODS: We analyzed data from the 2018 Behavioral Risk Factor Surveillance System to estimate the number of adults who have an elevated risk of serious illness if they are infected with coronavirus in metropolitan, micropolitan, and rural areas for each state. Study data included 430,949 survey responses representing over 255.2 million noninstitutionalized US adults. For data on hospital beds, aggregate survey data were linked to data from the 2017 Area Health Resource Files by state and metropolitan status. FINDINGS: About 50% of rural residents are at high risk for hospitalization and serious illness if they are infected with COVID-19, compared to 46.9% and 40.0% in micropolitan and metropolitan areas, respectively. In 19 states, more than 50% of rural populations are at high risk for serious illness if infected. Rural residents will generate an estimated 10% more hospitalizations for COVID-19 per capita than urban residents given equal infection rates. CONCLUSION: More than half of rural residents are at increased risk of hospitalization and death if infected with COVID-19. Experts expect COVID-19 burden to outpace hospital capacity across the country, and rural areas are no exception. Policy makers need to consider supply chain modifications, regulatory changes, and financial assistance policies to assist rural communities in caring for people affected by COVID-19.

North Carolina's Health Care Transformation to Value: Progress to Date and Further Steps Needed.

North Carolina has received national attention for its approach to health care payment and delivery reform. Importantly, payment reform alone is not enough to drive systematic changes in care delivery. We highlight the importance of progress in four complementary areas to achieve system-wide payment and care reform.

How Would Rural Hospitals Be Affected by Loss of the Affordable Care Act's Medicare Low-Volume Hospital Adjustment?

PURPOSE: The low-volume hospital (LVH) payment adjustment established in the Patient Protection and Affordable Care Act (ACA) of 2010 is scheduled to sunset on October 1, 2017. The purpose of this analysis was: (1) to estimate the effect of the ACA LVH adjustment on qualifying hospitals' profitability margins; and (2) to examine hospital and market characteristics of the hospitals that would be most adversely affected by the loss of the ACA LVH adjustment. METHODS: 2004-2015 data from the Hospital Cost Report Information System, Hospital Market Service Area File and Nielsen-Claritas Pop-Facts file were used to estimate difference-in-difference regression models with hospital-level random effects in order to determine whether the ACA LVH adjustment improved qualifying rural hospitals' profitability margins. Recycled predictions estimated the effect of losing the ACA LVH adjustment on profitability margins. Bivariate analyses explored associations between the predicted profitability margins and hospital and market characteristics. FINDINGS: The ACA LVH adjustment significantly improved Sole Community Hospitals' Medicare inpatient margins in the year they received the adjustment, and it had a large but statistically insignificant effect on the profitability margins of other rural hospitals. Hospitals that would be the most adversely affected by loss of the ACA LVH adjustment were more likely to be small, located in the South, and in high-poverty markets with higher proportions of black and uninsured individuals. CONCLUSIONS: Elimination of the ACA LVH adjustment would have differential effects on subgroups of hospitals, and those located in markets serving historically underserved populations would be the most adversely affected.

Colorectal cancer surgery outcomes for vulnerable patients in safety-net versus non-safety-net hospitals.

Extensive research documents disparities in health outcomes for vulnerable populations. Safety-net hospitals-those that serve a greater proportion of vulnerable patients with Medicaid or no insurance-may yield better outcomes for these vulnerable patients because of their expertise with this population. National Inpatient Sample data from 2005-2007 show that predicted rates of complications following colorectal cancer surgery are approximately 20% lower for vulnerable patients in safety-net than in non-safety-net hospitals (0.273 versus 0.340; 95% CI for the difference: -0.11, -0.001). Differences by safety-net status for Medicare and privately-insured patients were smaller and not statistically significant. The lower complication rates are not due to earlier discharge, as vulnerable patients had significantly longer stays at safety-net hospitals (1.79 days; 95% CI 0.13, 3.40). Additional research is needed to determine whether improvement in post-operative outcomes is due to the expertise of safety-net hospitals in caring for patients with Medicaid or no insurance.