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OBJECTIVE:US hospitals that care for vulnerable populations, “safety-net hospitals” (SNHs), are more likely to incur penalties under the Hospital Readmissions Reduction Program, which penalizes hospitals with higher-than-expected readmissions. Understanding whether SNHs face unique barriers to reducing readmissions or whether they underuse readmission-prevention strategies is important. DESIGN:We surveyed leadership at 1600 US acute care hospitals, of whom 980 participated, between June 2013 and January 2014. Responses on 28 questions on readmission-related barriers and strategies were compared between SNHs and non-SNHs, adjusting for nonresponse and sampling strategy. We further compared responses between high-performing SNHs and low-performing SNHs. RESULTS:We achieved a 62% response rate. SNHs were more likely to report patient-related barriers, including lack of transportation, homelessness, and language barriers compared with non-SNHs (P-values<0.001). Despite reporting more barriers, SNHs were less likely to use e-tools to share discharge summaries (70.1% vs. 73.7%, P<0.04) or verbally communicate (31.5% vs. 39.8%, P<0.001) with outpatient providers, track readmissions by race/ethnicity (23.9% vs. 28.6%, P<0.001), or enroll patients in postdischarge programs (13.3% vs. 17.2%, P<0.001). SNHs were also less likely to use discharge coordinators, pharmacists, and postdischarge programs. When we examined the use of strategies within SNHs, we found trends to suggest that high-performing SNHs were more likely to use several readmission strategies. CONCLUSIONS:Despite reporting more barriers to reducing readmissions, SNHs were less likely to use readmission-reduction strategies. This combination of higher barriers and lower use of strategies may explain why SNHs have higher rates of readmissions and penalties under the Hospital Readmissions Reduction Program.

Background The aim of this study was to identify the range of ways that safety net hospitals (SNHs) have been empirically operationalized in the literature and determine the extent to which patterns could be identified in the use of empirical definitions of SNHs. Methods We conducted a PRISMA guided systematic review of studies published between 2009 and 2018 and analyzed 22 articles that met the inclusion criteria of hospital-level analyses with a clear SNH definition. Results Eleven unique SNH definitions were identified, and there were no obvious patterns in the use of a definition category (Medicaid caseload, DSH payment status, uncompensated care, facility characteristics, patient care mix) by the journal type where the article appeared, dataset used, or the year of publication. Conclusions Overall, there is broad variability in the conceptualization of, and variables used to define, SNHs. Our work advances the field toward the development of standards in measuring, operationalizing, and conceptualizing SNHs across research and policy questions.

The COVID-19 crisis has led to spiking unemployment rates with disproportionate impacts on low-income families. School and child-care center closures have also meant lost free and reduced-price school meals. Food prices have increased sharply, leading to reduced purchasing power for families with limited income. The Families First Coronavirus Response Act and the Coronavirus Aid, Relief, and Economic Security Act constituted a robust response, including expansions to unemployment insurance (expansions in eligibility and a $600 per week supplement), a onetime payment of $1,200 per adult and $500 per dependent, an increase in SNAP payments, and the launch of the Pandemic EBT program to replace lost school meals. Despite these efforts, real-time data show significant distress—notably, food insecurity rates have increased almost three times over the pre-COVID-19 rates and food pantry use has also spiked. In this paper, we explore why there is so much unmet need despite a robust policy response. We provide evidence for three explanations: (1) timing—relief came with a substantial delay, due to overwhelmed unemployment insurance (UI) systems and the need to implement new programs; (2) magnitude—payments outside UI are modest; and (3) coverage gaps—access is lower for some groups, and other groups are statutorily excluded.

Although readmission rates are declining under Medicare's Hospital Readmissions Reduction Program (HRRP), concerns remain that the HRRP will harm quality at safety-net hospitals because they are penalized more often. Disparities between white and black patients might widen because more black patients receive care at safety-net hospitals. Disparities may be particularly worse for clinical conditions not targeted by the HRRP because hospitals might reallocate resources toward targeted conditions (acute myocardial infarction, pneumonia, and heart failure) at the expense of nontargeted conditions. To examine disparities in readmission rates between white and black patients discharged from safety-net or non-safety-net hospitals after the HRRP began, evaluating discharges for any clinical condition and the subsets of targeted and nontargeted conditions. Cohort study conducting quasi-experimental analyses of patient hospital discharges for any clinical condition among fee-for-service Medicare beneficiaries from 2007 to 2015 after controlling for patient and hospital characteristics. Changes in disparities were measured within safety-net and non-safety-net hospitals after the HRRP penalties were enforced and compared with prior trends. These analyses were then stratified by targeted and nontargeted conditions. Analyses were conducted from October 1, 2017, through August 31, 2018. Trends in 30-day readmission rates among white and black patients by quarter and differences in trends across periods. The study sample included 58 237 056 patient discharges (black patients, 9.8%; female, 57.7%; mean age [SD] age, 78.8 [7.9] years; nontargeted conditions, 50 372 806 [86.5%]). Within safety-net hospitals, disparities in readmission rates for all clinical conditions widened between black and white patients by 0.04 percentage point per quarter in the HRRP penalty period (95% CI, 0.01 to 0.07; P = .01). This widening was driven by nontargeted conditions (0.05 percentage point per quarter [95% CI, 0.01 to 0.08]; P = .006), whereas disparities for the HRRP-targeted conditions did not change (with an increase of 0.01 percentage point per quarter [95% CI, -0.07 to 0.10]; P = .74). Within non-safety-net hospitals, racial disparities remained stable in the HRRP penalty period across all conditions, whether the conditions were HRRP-targeted or nontargeted. Findings from this study suggest that disparities are widening within safety-net hospitals, specifically for non-HRRP-targeted conditions. Although increases in racial disparities for nontargeted conditions were modest, they represent 6 times more discharges in our cohort than targeted conditions.

Safety-net hospitals provide essential care to patients regardless of their insurance coverage, financial circumstances, or immigration status, and they often operate with thin margins. But the lack of a clear definition for safety-net hospitals presents challenges.

Introduction The underrepresentation of Black, Indigenous, and People of Color (BIPOC) individuals in healthcare research limits generalizability and contributes to healthcare inequities. Existing barriers and attitudes toward research participation must be addressed to increase the representation of safety net and other underserved populations. Methods We conducted semi‐structured qualitative interviews with patients at an urban safety net hospital, focusing on facilitators, barriers, motivators, and preferences for research participation. We conducted direct content analysis guided by an implementation framework and used rapid analysis methods to generate final themes. Results We completed 38 interviews and identified six major themes related to preferences for engagement in research participation: (1) wide variation in research recruitment preferences; (2) logistical complexity negatively impacts willingness to participate; (3) risk contributes to hesitation toward research participation; (4) personal/community benefit, interest in study topic, and compensation serve as motivators for research participation; (5) continued participation despite reported shortcomings of informed consent process; and (6) mistrust could be overcome by relationship or credibility of information sources. Conclusion Despite barriers to participation in research studies among safety‐net populations, there are also facilitators that can be implemented to increase knowledge and comprehension, ease of participation, and willingness to join research studies. Study teams should vary recruitment and participation methods to ensure equal access to research opportunities. Patient/Public Contribution Our analysis methods and study progress were presented to individuals within the Boston Medical Center healthcare system. Through this process community engagement specialists, clinical experts, research directors, and others with significant experience working with safety‐net populations supported data interpretation and provided recommendations for action following the dissemination of data.

Introduction Initial treatment for nonmetastatic breast cancer is resection or neoadjuvant systemic therapy, depending on tumor biology and patient factors. Delays in treatment have been shown to impact survival and quality of life. Little has been published on the performance of safety-net hospitals in delivering timely care for all patients. Methods We conducted a retrospective study of patients with invasive ductal or lobular breast cancer, diagnosed and treated between 2009 and 2019 at an academic, safety-net hospital. Time to treatment initiation was calculated for all patients. Consistent with a recently published Committee on Cancer timeliness metric, a treatment delay was defined as time from tissue diagnosis to treatment of greater than 60 days. Results A total of 799 eligible women with stage 1–3 breast cancer met study criteria. Median age was 60 years, 55.7% were non-white, 35.5% were non-English-speaking, 18.9% were Hispanic, and 49.4% were Medicaid/uninsured. Median time to treatment was 41 days (IQR 27–56 days), while 81.1% of patients initiated treatment within 60 days. The frequency of treatment delays did not vary by race, ethnicity, insurance, or language. Diagnosis year was inversely associated with the occurrence of a treatment delay (OR: 0.944, 95% CI 0.893–0.997, p value: 0.039). Conclusion At our institution, race, ethnicity, insurance, and language were not associated with treatment delay. Additional research is needed to determine how our safety-net hospital delivered timely care to all patients with breast cancer, as reducing delays in care may be one mechanism by which health systems can mitigate disparities in the treatment of breast cancer.

PurposeAmong women with non-metastatic breast cancer, marked disparities in stage at presentation, receipt of guideline-concordant treatment and stage-specific survival have been shown in national cohorts based on race, ethnicity, insurance and language. Little is published on the performance of safety-net hospitals to achieve equitable care. We evaluate differences in treatment and survival by race, ethnicity, language and insurance status among women with non-metastatic invasive breast cancer at a single, urban academic safety-net hospital.MethodsWe conducted a retrospective study of patients with invasive ductal or lobular breast cancer, diagnosed and treated between 2009 and 2014 at an urban, academic safety-net hospital. Demographic, tumor and treatment characteristics were obtained. Stage at presentation, stage-specific overall survival, and receipt of guideline-concordant surgical and adjuvant therapies were analyzed. Chi-square analysis and ANOVA were used for statistical analysis. Unadjusted survival analysis was conducted by Kaplan–Meier method using log-rank test; adjusted 5 year survival analysis was completed stratified by early and late stage, using flexible parametric survival models incorporating age, race, primary language and insurance status.Results520 women with stage 1–3 invasive breast cancer were identified. Median age was 58.5 years, 56.1% were non-white, 31.7% were non-English-speaking, 16.4% were Hispanic, and 50.1% were Medicaid/uninsured patients. There were no statistically significant differences in stage at presentation between age group, race, ethnicity, language or insurance. The rate of breast conserving surgery (BCS) among stage 1–2 patients did not vary by race, insurance or language. Among patients indicated for adjuvant therapies, the rates of recommendation and completion of therapy did not vary by race, ethnicity, insurance or language. Unadjusted survival at 5 years was 93.7% for stage 1–2 and 73.5% for stage 3. Adjusting for age, race, insurance status and primary language, overall survival at 5 years was 93.8% (95% CI 86.3–97.2%) for stage 1–2 and 83.4% (95% CI 35.5–96.9%) for stage 3 disease. Independently, for patients with early- and late-stage disease, age, race, language and insurance were not associated with survival at 5-years.ConclusionAmong patients diagnosed and treated at an academic safety-net hospital, there were no differences in the stage at presentation or receipt of guideline-concordant treatment by race, ethnicity, insurance or language. Overall survival did not vary by race, insurance or language. Additional research is needed to assess how hospitals and healthcare systems mitigate breast cancer disparities.

PurposePublic safety net hospitals (SNH) serve a disparate patient population; however, little is known about long-term oncologic outcomes of patients receiving care at these facilities. This study is the first to examine overall survival (OS) and the initiation of treatment in breast cancer patients treated at a SNH.MethodsPatients presenting to a SNH with stage I-IV breast cancer from 2005 to 2017 were identified from the local tumor registry. The hospital has a weekly breast tumor board and a multidisciplinary approach to breast cancer care. Kaplan-Meier survival analysis was performed to identify patient, tumor, and treatment characteristics associated with OS. Factors with a p < 0.1 were included in the Cox proportional hazards model.Results2709 breast cancer patients were evaluated from 2005 to 2017. The patient demographics, tumor characteristics, and treatments received were analyzed. Five-year OS was 78.4% (93.9%, 87.4%, 70.9%, and 23.5% for stages I, II, III, and IV, respectively). On multivariable analysis, higher stage, age > 70 years, higher grade, and non-Hispanic ethnicity were associated with worse OS. Patients receiving surgery (HR = 0.33, p < 0.0001), chemotherapy (HR = 0.71, p = 0.006), and endocrine therapy (HR = 0.61, p < 0.0001) had better OS compared to those who did not receive these treatments.ConclusionDespite serving a vulnerable minority population that is largely poor, uninsured, and presenting with more advanced disease, OS at our SNH approaches national averages. This novel finding indicates that in the setting of multidisciplinary cancer care and with appropriate initiation of treatment, SNHs can overcome socioeconomic barriers to achieve equitable outcomes in breast cancer care.

As we enter a new stage of pandemic response and recovery — in which we must address issues of racial health inequities, frontline health care infrastructure, and community preparedness — what constitutes adequate support for the U.S. health care safety net?