Non-safety Net Hospitals Research Articles

Comparison of nursing staffing ratio in selected safety net and non-safety net hospitals in the United States

Objective: This study investigated the differential association between nurse staffing in safety-net hospitals (SNHs) and non-SNHs.Methods: This retrospective cross-sectional study utilized multilevel mixed-effects linear regression models and included data from 1,228 hospitals.Results: The results showed that SNHs in the top quartile of disproportionate share hospital (DSH) payments had lower nurse staffing ratios (β = -0.86; p-value < .001), indicating a lower nurse-to-patient ratio, compared to non-SNHs. This association persisted even after adjusting for the county and hospital factors.Conclusions: These findings suggest that nurse staffing in SNHs may be impacted by the financial challenges associated with providing uncompensated care to vulnerable populations. Understanding the differences in nurse staffing between SNHs and non-SNHs can provide insights for improving quality of care. Further research is required to explore the impact of nurse staffing on patient outcomes in SNHs.

Health Equity Adjustment and Hospital Performance in the Medicare Value-Based Purchasing Program

Medicare's Hospital Value-Based Purchasing (HVBP) program will provide a health equity adjustment (HEA) to hospitals that have greater proportions of patients dually eligible for Medicare and Medicaid and that offer high-quality care beginning in fiscal year 2026. However, which hospitals will benefit most from this policy change and to what extent are unknown. To estimate potential changes in hospital performance after HEA and examine hospital patient mix, structural, and geographic characteristics associated with receipt of increased payments. This cross-sectional study analyzed all 2676 hospitals participating in the HVBP program in fiscal year 2021. Publicly available data on program performance and hospital characteristics were linked to Medicare claims data on all inpatient stays for dual-eligible beneficiaries at each hospital to calculate HEA points and HVBP payment adjustments. Hospital Value-Based Purchasing program HEA. Reclassification of HVBP bonus or penalty status and changes in payment adjustments across hospital characteristics. Of 2676 hospitals participating in the HVBP program in fiscal year 2021, 1470 (54.9%) received bonuses and 1206 (45.1%) received penalties. After HEA, 102 hospitals (6.9%) were reclassified from bonus to penalty status, whereas 119 (9.9%) were reclassified from penalty to bonus status. At the hospital level, mean (SD) HVBP payment adjustments decreased by $4534 ($90 033) after HEA, ranging from a maximum reduction of $1 014 276 to a maximum increase of $1 523 765. At the aggregate level, net-positive changes in payment adjustments were largest among safety net hospitals ($28 971 708) and those caring for a higher proportion of Black patients ($15 468 445). The likelihood of experiencing increases in payment adjustments was significantly higher among safety net compared with non-safety net hospitals (574 of 683 [84.0%] vs 709 of 1993 [35.6%]; adjusted rate ratio [ARR], 2.04 [95% CI, 1.89-2.20]) and high-proportion Black hospitals compared with non-high-proportion Black hospitals (396 of 523 [75.7%] vs 887 of 2153 [41.2%]; ARR, 1.40 [95% CI, 1.29-1.51]). Rural hospitals (374 of 612 [61.1%] vs 909 of 2064 [44.0%]; ARR, 1.44 [95% CI, 1.30-1.58]), as well as those located in the South (598 of 1040 [57.5%] vs 192 of 439 [43.7%]; ARR, 1.25 [95% CI, 1.10-1.42]) and in Medicaid expansion states (801 of 1651 [48.5%] vs 482 of 1025 [47.0%]; ARR, 1.16 [95% CI, 1.06-1.28]), were also more likely to experience increased payment adjustments after HEA compared with their urban, Northeastern, and Medicaid nonexpansion state counterparts, respectively. Medicare's implementation of HEA in the HVBP program will significantly reclassify hospital performance and redistribute program payments, with safety net and high-proportion Black hospitals benefiting most from this policy change. These findings suggest that HEA is an important strategy to ensure that value-based payment programs are more equitable.

Hospital safety-net status and postdischarge outcomes: The impact of socioeconomic status and Medicare post-acute care types.

To examine the impact of socioeconomic status (SES) and postacute care (PAC) locations on the association between hospital safety-net status and 30-day postdischarge outcomes (readmission, hospice use,or death). Medicare Current Beneficiary Survey (MCBS) participants during 2006-2011 who were Medicare Fee-for-Service beneficiaries aged 65.5 years or older were included. The associations between hospital safety-net status and 30-day post-discharge outcomes were evaluated by comparing the models with and without PAC and SES adjustments. Safety-net hospital status was defined as being in the top 20% of hospitals ranked by hospital-level percent of total Medicare patient days. SES was measured using individual-level SES (dual eligibility, income,and education) and the Area Deprivation Index (ADI). This study identified 13,173 index hospitalizations for 6,825 patients; 1,428 hospitalizations (11.8%) were in safety-net hospitals. The averageunadjusted 30-day hospital readmission rate was 22.6% in safety-net hospitals versus 18.8% in nonsafety-net hospitals. Regardless of whether patient SES status was controlled or not, safety-net hospitals had higher estimated probabilities of 30-day readmission (ranging from 0.217 to 0.222 vs. 0.184 to 0.189), and lower probabilities for having neitherreadmission nor hospice/death (0.750-0.763 vs. 0.780-0.785); for models additionally adjusted for PAC types, safety-net patients had lower rates of hospice use or death (0.019-0.027 vs. 0.030-0.031). The results suggested that safety-net hospitals had lower hospice/death rates but higher readmission rates relative to outcomes at nonsafety-net hospitals. Readmission rate differences were similar regardless of patients' SES status. However, the rate of hospice referral or death rate was related to SES, which suggested that the outcomes were affected by SES and PAC types.

Readmissions performance and penalty experience of safety-net hospitals under Medicare\u2019s Hospital Readmissions Reduction Program

BackgroundThe Hospital Readmissions Reduction Program (HRRP), established by the Centers for Medicare and Medicaid Services (CMS) in March 2010, introduced payment-reduction penalties on acute care hospitals with higher-than-expected readmission rates for acute myocardial infarction (AMI), heart failure, and pneumonia. There is concern that hospitals serving large numbers of low-income and uninsured patients (safety-net hospitals) are at greater risk of higher readmissions and penalties, often due to factors that are likely outside the hospital’s control. Using publicly reported data, we compared the readmissions performance and penalty experience among safety-net and non-safety-net hospitals.MethodsWe used nationwide hospital level data for 2009-2016 from the Centers for Medicare and Medicaid Services (CMS) Hospital Compare program, CMS Final Impact Rule, and the American Hospital Association Annual Survey. We identified as safety-net hospitals the top quartile of hospitals in terms of the proportion of patients receiving income-based public benefits. Using a quasi-experimental difference-in-differences approach based on the comparison of pre- vs. post-HRRP changes in (risk-adjusted) 30-day readmission rate in safety-net and non-safety-net hospitals, we estimated the change in readmissions rate associated with HRRP. We also compared the penalty frequency among safety-net and non-safety-net hospitals.ResultsOur study cohort included 1915 hospitals, of which 479 were safety-net hospitals. At baseline (2009), safety-net hospitals had a slightly higher readmission rate compared to non-safety net hospitals for all three conditions: AMI, 20.3% vs. 19.8% (p value< 0.001); heart failure, 25.2% vs. 24.2% (p-value< 0.001); pneumonia, 18.7% vs. 18.1% (p-value< 0.001). Beginning in 2012, readmission rates declined similarly in both hospital groups for all three cohorts. Based on difference-in-differences analysis, HRRP was associated with similar change in the readmissions rate in safety-net and non-safety-net hospitals for AMI and heart failure. For the pneumonia cohort, we found a larger reduction (0.23%; p < 0.001) in safety-net hospitals. The frequency of readmissions penalty was higher among safety-net hospitals. The proportion of hospitals penalized during all four post-HRRP years was 72% among safety-net and 59% among non-safety-net hospitals.ConclusionsOur results lend support to the concerns of disproportionately higher risk of performance-based penalty on safety-net hospitals.

Teleophthalmology and Inequities in Diabetic Eye Disease at Safety Net Hospitals.

Introduction: Teleophthalmology has emerged as a convenient and cost-effective intervention to increase access to screening for diabetic retinopathy (DR), a disease that disproportionately affects socially disadvantaged communities. However, a few studies have directly compared the detection of eye disease by teleophthalmology between socially and geographically diverse communities. This study compared the rates and severity of diabetic eye disease, as detected by teleophthalmology, between safety net and non-Safety Net Hospitals (non-SNHs). Methods: Retrospective chart review of patients screened for DR at county Safety Net Hospitals (SNHs) and non-SNHs in 150 cities and 30 states. The rates of DR, macular edema, suspected cataract, suspected glaucoma, and suspected age-related macular degeneration were compared. Relative risk and severity of disease in the county SNH population were calculated. Images were graded by the same group of IRIS readers, who used at least one image per eye with a 45° field centered between the optic disc and the macula. Participants with ungradable screening images were excluded. Results: Ninety-four thousand three hundred twenty-nine participants were screened for eye disease from September 1, 2016 to August 31, 2017. Among the screened participants (54% female; mean [SD] age, 58.7 [12.9] years), overall disease detection was 31% in the county SNH population and 23.6% in the non-SNH population. Compared with the non-SNH population, the county SNH population was twice as likely to screen positive for three or more concurrent eye conditions (1.2% vs. 0.7%) and had increased prevalence of DR (20.2% vs. 16.2%), macular edema (4.9% vs. 3.4%), suspected glaucoma (9.1% vs. 4.3%), suspected cataract (9.6% vs. 4.8%), and proliferative DR (2.1% vs. 1.0%). Conclusions: Increased diabetic eye disease prevalence and severity among people seen at SNHs highlights the need for continued resources to screen, treat, and manage disease. Teleophthalmology continues to be an important tool in efforts to mitigate health inequities and address barriers faced by underserved communities.

Association of Hospital Safety Net Status With Outcomes and Resource Use for Extracorporeal Membrane Oxygenation in the United States.

Safety net hospitals (SNH) have been associated with inferior surgical outcomes and increased resource use. Utilization and outcomes for extracorporeal membrane oxygenation (ECMO), a rescue modality for patients with respiratory or cardiac failure, may vary by safety net status. We hypothesized SNH to be associated with inferior outcomes and costs of ECMO in a national cohort. The 2008-2017 National Inpatient Sample was queried for ECMO hospitalizations and safety net hospitals were identified. Multivariable regression was used to perform risk-adjusted comparisons of mortality, complications and resource utilization at safety net and non-safety net hospitals. Of 36,491 ECMO hospitalizations, 28.2% were at SNH. On adjusted comparison SNH was associated with increased odds of mortality (AOR: 1.23), tracheostomy use (AOR: 1.51), intracranial hemorrhage (AOR: 1.39), as well as infectious complications (AOR: 1.21, all P < .05), with NSNH as reference. SNH was also associated with increased hospitalization duration (β=+4.5 days) and hospitalization costs (β=+$32,880, all P < .01). We have found SNH to be associated with inferior survival, increased complications, and higher costs compared to NSNH. These disparate outcomes warrant further studies examining systemic and hospital-level factors that may impact outcomes and resource use of ECMO at SNH.

Are Improvements Still Needed to the Modified Hospital Readmissions Reduction Program: a Health and Retirement Study (2000-2014)?

To address concerns that the Hospital Readmissions Reduction Program (HRRP) unfairly penalized safety net hospitals treating patients with high social and functional risks, Medicare recently modified HRRP to compare hospitals with similar proportions of high-risk, dual-eligible patients ("peer group hospitals"). Whether the change fully accounts for patients' social and functional risks is unknown. Examine risk-standardized readmission rates (RSRRs) and hospital penalties after adding patient-level social and functional and community-level risk factors. Using 2000-2014 Medicare hospital discharge, Health and Retirement Study, and community-level data, latent factors for patient social and functional factors and community factors were identified. We estimated RSRRs for peer groups and by safety net status using four hierarchical logistic regression models: "base" (HRRP model); "patient" (base plus patient factors); "community" (base plus community factors); and "full" (all factors). The proportion of hospitals penalized was calculated by safety net status. 20,255 fee-for-service Medicare beneficiaries (65+) with eligible index hospitalizations MAIN MEASURES: RSRRs KEY RESULTS: Half of safety net hospitals are in peer group 5. Compared with other hospitals, peer group 5 hospitals (most dual-eligibles) treated sicker, more functionally limited patients from socially disadvantaged groups. RSRRs decreased by 0.7% for peer groups 2 and 4 and 1.3% for peer group 5 under the patient and full (versus base) models. Measured performance improved after adjusting for patient risk factors for hospitals in peer group 4 and 5 hospitals, but worsened for those in peer groups 1, 2, and 3. Under the patient (versus base) model, fewer safety net hospitals (48.7% versus 51.3%) but more non-safety net hospitals (50.0% versus 49.1%) were penalized. Patient-level risk adjustment decreased RSRRs for hospitals serving more at-risk patients and proportion of safety net hospitals penalized, while modestly increasing RSRRs and proportion of non-safety net hospitals penalized. Results suggest HRRP modifications may not fully account for hospital variation in patient-level risk.

Safety-net hospitals versus non-safety centers and clinical outcomes after trans-catheter aortic valve replacement.

To compare post-procedural outcomes of trans-catheter valve replacement (TAVR) among safety-net (SNH) and non-safety net hospitals (non-SNH). SNH treat a large population of un-insured and low income patients; prior studies report worse outcome at these centers. Results of TAVR at these centers is limited. Adults undergoing TAVR at hospitals in the US participating in the National In-patient sample (NIS) database from January 2014 to December 2015 were included. A 1:1 propensity-matched cohort of patients operated at SNH and non-SNH institutions was analyzed, on the basis of 16 demographic and clinical co-variates. Main outcome was all-cause post-procedural mortality. Secondary outcomes included stroke, acute kidney injury and length of post-operative stay. Between 2014 and 2015, 41,410 patients (mean age 80 ± 0.11 years, 46% female) underwent TAVR at 731 centers; 6,996 (16.80%) procedures were performed at SNH comprising 135/731 (18.4%) of all centers performing TAVR. SNH patients were more likely to be female (49% vs. 46%, p < .001); admitted emergently (31% vs. 21%; p < .001; at the lowest quartile for household income (25% % vs. 20%; p < .001) and from minorities (Blacks 5.9% vs. 3.9%; Hispanic 7.2% vs. 3.2%).Adjusted logistic regression was performed on 6,995 propensity-matched patient pairs. Post-procedural mortality [OR 0.99(0.98-1.007); p = .43], stroke [OR 1.009(0.99-1.02); p = .08], acute kidney injury [OR 0.99(0.96-1.01); p = .5] and overall length of stay (6.9 ± 0.1 vs. 7.1 ± 0.2 days; p = .57) were comparable in both cohorts. Post-procedural outcomes after TAVR at SNH are comparable to national outcomes and wider adoption of TAVR at SNH may not adversely influence outcomes.

Abstract 356: Hospital Safety Net Status and Clinical Outcomes After Trans-catheter Aortic Valve Replacement

Introduction: Safety-net hospitals (SNH) treat a large population of un-insured and low income patients; several prior studies report worse outcome at these centers. Trans-catheter valve replacement (TAVR) is emerging as first-line therapy for aortic stenosis irrespective of surgical risk scores. However, results of TAVR performed at these centers is limited. Objective: To determine whether post-procedural outcomes of TAVR are comparable at safety-net (SNH) and non-safety net hospitals (non-SNH). Methods: We conducted a retrospective, cohort study with propensity-matched analysis. Complex survey data from the Agency for Healthcare Quality and Research containing weighted sample of all hospital admissions nationwide was utilized for this study. Adults undergoing TAVR at US hospitals participating in the National In-patient sample (NIS) database from January 2014 - December 2015 were included. A 1:1 propensity-matched cohort of patients operated at safety-net hospitals (SNH) and non-SNH institutions was analyzed. Propensity-matching was performed on the basis of sixteen demographic and clinical confounding co-variates. Main outcome studied was all-cause post-procedural mortality. Secondary outcomes compared were stroke, acute kidney injury and length of post-operative stay. Results: Between 2014 - 2015, 41410 patients (mean age 80 +/- 0.11 years, 46% female) underwent TAVR at 731 centers nationwide; 6996 (16.80 %) procedures were performed at safety net centers. SNH comprised 135/731 (18.4%) of all centers performing TAVR. SNH patients were more likely to be female (49 % vs 46 %, p &lt;0.001); admitted emergently (31% vs 21%; p &lt;0.001) and at the lowest quartile for household income (25% % vs 20 %; p &lt;0.001). A large proportion of SNH patients were minorities (Blacks 5.9% vs 3.9%; Hispanic 7.2% vs 3.2%). Adjusted logistic regression was performed on 6995 propensity-matched patient pairs. Post-procedural mortality [OR 0.99 (0.98 - 1.007); p = 0.43], stroke [OR 1.009 (0.99-1.02); p = 0.08], and acute kidney injury [OR 0.99 (0.96 - 1.01); p = 0.5] were comparable in both cohorts. Overall length of stay was also similar (6.9 +/- 0.1 vs 7.1 +/- 0.2 days; p = 057). Conclusion: Post-procedural outcomes after TAVR at SNH are comparable to national outcomes. Our study provides preliminary evidence that wider adoption of TAVR may not adversely influence outcomes at SNH.

Barriers and facilitators to implementing priority inpatient initiatives in the safety net setting

BackgroundSafety net hospitals, which serve vulnerable and underserved populations and often operate on smaller budgets than non-safety net hospitals, may experience unique implementation challenges. We sought to describe common barriers and facilitators that affect the implementation of improvement initiatives in a safety net hospital, and identify potentially transferable lessons to enhance implementation efforts in similar settings.MethodsWe interviewed leaders within five inpatient departments and asked them to identify the priority inpatient improvement initiative from the last year. We then conducted individual, semi-structured interviews with 25 stakeholders across the five settings. Interviewees included individuals serving in implementation oversight, champion, and frontline implementer roles. The Consolidated Framework for Implementation Research informed the discussion guide and a priori codes for directed content analysis.ResultsDespite pursuing diverse initiatives in different clinical departments, safety net hospital improvement stakeholders described common barriers and facilitators related to inner and outer setting dynamics, characteristics of individuals involved, and implementation processes. Implementation barriers included (1) limited staffing resources, (2) organizational recognition without financial investment, and (3) the use of implementation strategies that did not adequately address patients’ biopsychosocial complexities. Facilitators included (1) implementation approaches that combined passive and active communication styles, (2) knowledge of patient needs and competitive pressure to perform well against non-SNHs, (3) stakeholders’ personal commitment to reduce health inequities, and (4) the use of multidisciplinary task forces to drive implementation activities.ConclusionInner and outer setting dynamics, individual’s characteristics, and process factors served as implementation barriers and facilitators within the safety net. Future work should seek to leverage findings from this study toward efforts to enact positive change within safety net hospitals.

Prevalence and predictors of donor milk programs among U.S. advanced neonatal care facilities.

(1) Determine national prevalence and predictors of donor milk programs among levels 2-4 advanced neonatal care facilities; (2) describe characteristics of donor milk programs. We randomly selected 120 U.S. hospitals with levels 2-4 advanced neonatal care facilities among each of four U.S. regions and surveyed the medical directors from July 2017 to November 2017 regarding donor milk use. We weighted responses according to the number of birthing hospitals in each region. Response rate was 213/480 (44%). Twenty-eight percent of level 2 and 88% of levels 3 and 4 neonatal care facilities had donor milk programs. Donor milk programs occurred more often in the South vs. Northeast (aOR 3.7 [1.1, 12.5] and less often in safety-net hospitals (≥75% Medicaid patients) vs. nonsafety-net hospitals (aOR 0.3 [0.1, 0.8]). In 2017, the vast majority of levels 3 and 4 neonatal care facilities had donor milk programs but disparities existed according to the safety-net hospital status and region.

Travel distance is associated with improved survival in hepatocellular carcinoma

Background: An association between travel distance and survival measures has been been demonstrated across gastrointestinal malignancies but thus far has not been examined in patients newly diagnosed with hepatocellular carcinoma (HCC). We aimed to determine the association of travel distance with time to treatment (TTT) and overall survival (OS) in patients newly diagnosed with HCC. Methods: Newly diagnosed HCC patients who received treatment were identified in the Texas Cancer Registry from 2004 to 2015. We compared system- and patient-level factors among patients who traveled short (<12.5 miles), intermediate (12.5–49.9 miles), and long (≥50 miles) travel distances for initial treatment. Anova and Chi-square analyses were used to compare clinicopathologic variables, and Kaplan-Meier with log rank and cox regression models were used to compare survival. Results: 4,329 patients were identified: 2,136 (49.3%) short, 1,380 (31.9%) intermediate, and 813 (18.9%) long distance patients. Patients who traveled intermediate and long distances were more likely to be Non-Hispanic White (59% for intermediate and 60% for long vs 33% for short, p<0.001) and a higher proportion of privately insured patients (29% for intermediate and 24% for long vs 16% for short, p < 0.001). Short distance patients were more often Hispanic White (43% vs 24% for intermediate and 31% for long) or Non-Hispanic Black (18% vs 8% for intermediate and long, p < 0.001). Long distance travelers were more often initially treated at ACS accredited hospitals (95% vs 73% for short and 89% for intermediate, p < 0.001), non-safety net hospitals (53% vs 40% for short and 52% for intermediate, p < 0.001), academic centers (80% vs 57% for short and 73% for intermediate,p < 0.001), and high volume hospitals (85% vs 63% for short and 78% for intermediate, p < 0.001). Long distance travelers had smaller tumors, more localized disease, and were more likely to undergo ablation. Patients who traveled short distances were more likely to undergo surgical resection or transplantation. Long distance travelers had the shortest median TTT (4 weeks vs 5 weeks for short and intermediate, p = 0.003). Non-Hispanic Black and Hispanic White races were independently associated with decreased odds of intermediate (OR 0.27, 95%CI 0.2–0.4, and OR 0.40, 95%CI 0.3–0.5) and long (0.27, 95%CI 0.2–0.4, and OR 0.58, 95%CI 0.5–0.7) driving distance compared to short distance. Intermediate distance was associated with the highest median OS of 32 months vs 31 (long) and 22 months (short) (p < 0.001). Intermediate distance was independently associated with improved OS (HR 0.89, 95%CI 0.81–0.98) compared to short, but long distance was associated with similar survival. Conclusion: Racial/ethnic minority patients have decreased odds of traveling longer distances for HCC care. Intermediate travel distance (12.5–49.9 miles) is associated with decreased TTT and improved OS compared to other travel distances.

Multi-institution Evaluation of Adherence to Comprehensive Postoperative VTE Chemoprophylaxis.

The aims of this study were to: (1) measure the rate of failure to provide defect-free postoperative venous thromboembolism (VTE) chemoprophylaxis, (2) identify reasons for failure to provide defect-free VTE chemoprophylaxis, and (3) examine patient- and hospital-level factors associated with failure. Current VTE quality measures are inadequate. VTE outcome measures are invalidated for interhospital comparison by surveillance bias. VTE process measures (e.g., SCIP-VTE-2) do not comprehensively capture failures throughout patients' entire hospitalization. We examined adherence to a novel VTE chemoprophylaxis process measure in patients who underwent colectomies over 18 months at 36 hospitals in a statewide surgical collaborative. This measure assessed comprehensive VTE chemoprophylaxis during each patient's entire hospitalization, including reasons why chemoprophylaxis was not given. Associations of patient and hospital characteristics with measure failure were examined. The SCIP-VTE-2 hospital-level quality measure identified failures of VTE chemoprophylaxis in 0% to 3% of patients. Conversely, the novel measure unmasked failure to provide defect-free chemoprophylaxis in 18% (736/4086) of colectomies. Reasons for failure included medication not ordered (30.4%), patient refusal (30.3%), incorrect dosage/frequency (8.2%), and patient off-unit (3.4%). Patients were less likely to fail the chemoprophylaxis process measure if treated at nonsafety net hospitals (OR 0.62, 95% CI 0.39-0.99, P = 0.045) or Magnet designated hospitals (OR 0.45, 95% CI 0.29-0.71, P = 0.001). In contrast to SCIP-VTE-2, our novel quality measure unmasked VTE chemoprophylaxis failures in 18% of colectomies. Most failures were due to patient refusals or ordering errors. Hospitals should focus improvement efforts on ensuring patients receive VTE prophylaxis throughout their entire hospitalization.

How Have Hospital Pricing Practices for Surgical Episodes of Care Responded to Affordable CareAct-Related Medicaid Expansion?

ObjectiveTo determine how Medicaid expansion under the Affordable Care Act of 2010 (ACA) has affected hospital pricing practices for surgical episodes of care. MethodsGiven that safety net hospitals would be more vulnerable to decreasing reimbursement due to an increase in proportion of Medicaid patients, we utilized the Premier Healthcare Database to compare institutional charge-to-cost ratio (CCR) in safety net hospitals vs nonsafety net hospitals for 8 index urologic surgery procedures during the period from 2012 to 2015. The effect of Medicaid expansion on CCR was assessed through difference-in-differences analysis. ResultsCCR among safety net hospitals increased from 4.06 to 4.30 following ACA-related Medicaid expansion. This did not significantly differ from the change among nonsafety net hospitals, which was from 4.00 to 4.38 (P = .086). The census division with the highest degree of Medicaid expansion experienced a smaller increase in CCR among safety net hospitals relative to nonsafety net (P < .0001). CCR increased by a greater degree in safety net hospitals compared to nonsafety net in the census division where Medicaid expansion was the least prevalent (P < .0001). ConclusionSafety net hospitals have not preferentially increased CCR in response to ACA-related Medicaid expansion. Census divisions where safety net hospitals did increase CCR more than their nonsafety net counterparts do not correspond to those where Medicaid expansion was most prevalent. This could indicate that, despite being more vulnerable to an increased proportion of more poorly reimbursing Medicaid patients, safety net hospitals have not reacted by increasing charges to private payers.

Comparing Risk Standardized Readmission Rates of Surgical Patients at Safety Net and Non-Safety Net Hospitals

Comparing Risk Standardized Readmission Rates of Surgical Patients at Safety Net and Non-Safety Net Hospitals

Hospital Characteristics Associated With Postdischarge Hospital Readmission, Observation, and Emergency Department Utilization.

Whether types of hospitals with high readmission rates also have high overall postdischarge acute care utilization (including emergency department and observation care) is unknown. Cross-sectional analysis. Nonfederal United States acute care hospitals. Using methodology established by the Centers for Medicare & Medicaid Services, we calculated each hospital's "excess days in acute care" for fee-for-service (FFS) Medicare beneficiaries aged over 65 years discharged after hospitalization for acute myocardial infarction, heart failure (HF), or pneumonia, representing the mean difference between predicted and expected total days of acute care utilization in the 30 days following hospital discharge, per 100 discharges. We assessed the multivariable association of 8 hospital characteristics with excess days in acute care and the proportion of hospitals with each characteristic that were statistical outliers (95% credible interval estimate does not include 0). We included 2184 hospitals for acute myocardial infarction [228 (10.4%) better than expected, 549 (25.1%) worse than expected], 3720 hospitals for HF [484 (13.0%) better and 840 (22.6%) worse], and 4195 hospitals for pneumonia [673 (16.0%) better, 1005 (24.0%) worse]. Results for all conditions were similar. Worse than expected outliers for pneumonia included: 18.8% of safety net hospitals versus 26.1% of nonsafety net hospitals; 16.7% of public hospitals versus 33.1% of for-profit hospitals; 19.5% of nonteaching hospitals versus 52.2% of major teaching hospitals; 7.9% of rural hospitals versus 42.1% of large urban hospitals; 5.9% of hospitals with 24-<50 beds versus 58% of hospitals with >500 beds; and 29.0% of hospitals with nurse-to-bed ratios >1.0-1.5 versus 21.7% of hospitals with ratios >2.0. Including emergency department and observation stays in measures of postdischarge utilization produces similar results as measuring only readmissions in that major teaching, urban and for-profit hospitals still perform disproportionately poorly versus nonteaching or public hospitals. However, it enables identification of more outliers and a more granular assessment of the association of hospital factors and outcomes.

How Safe Is the Safety Net? Comparison of Ivor-Lewis Esophagectomy at a Safety-Net Hospital Using the NSQIP Database

Recent data suggest that surgical outcomes at hospitals caring for low-income, vulnerable populations are suboptimal compared with outcomes from nonsafety-net hospitals. Therefore, the purpose of our study was to compare outcomes for patients who underwent an Ivor-Lewis esophagectomy at a safety-net hospital with the National Surgical Quality Improvement Program (NSQIP) database. We retrospectively reviewed the medical records of consecutive patients who underwent an Ivor-Lewis esophagectomy, between September 2013 and January 2017, at a single safety-net hospital. Patient characteristics and outcomes were compared with the 2013 to 2015 NSQIP database. Continuous variables were compared using Student's t-test, and categorical variables were analyzed using chi-square tests. Values of p < 0.05 were considered significant. We identified 78 patients from the safety-net hospital and 1,825 patients in the NSQIP database who underwent an Ivor-Lewis esophagectomy. Baseline characteristics were similar, except the safety-net hospital patients were more likely to have COPD (19.2% vs 8.1%; p=0.001) and be current smokers (42.3% vs 26.0%; p= 0.001); patients in the NSQIP group had a higher BMI (28 kg/m2 vs 26 kg/m2; p= 0.001). There were no differences between groups for mortality, readmission, discharge destination, or mean operative time. Safety-net hospital patients had significantly fewer complications (16.7% vs 33.3%; p=0.003), fewer reoperations (6.4% vs 14.5%; p= 0.046), and shorter hospital length of stay (10.3 vs 13.1 days; p= 0.001). Patients who underwent an Ivor-Lewis esophagectomy at a safety-net hospital had fewer complications and reoperations, and a shorter hospital length of stay compared with a national cohort. These findings illustrate the value of clinical pathways in optimizing the patient outcomes at safety-net hospitals and providing excellent care to their vulnerable patient population.

Medicare Payment Penalties and Safety Net Hospital Profitability: Minimal Impact on These Vulnerable Hospitals.

To examine relationships between penalties assessed by Medicare's Hospital Readmission Reduction Program and Value-Based Purchasing Program and hospital financial condition. Centers for Medicare and Medicaid Services, American Hospital Association, and Area Health Resource File data for 4,824 hospital-year observations. Bivariate and multivariate analysis of pooled cross-sectional data. Safety net hospitals have significantly higher HRRP/VBP penalties, but, unlike nonsafety net hospitals, increases in their penalty rate did not significantly affect their total margins. Safety net hospitals appear to rely on nonpatient care revenues to offset higher penalties for the years studied. While reassuring, these funding streams are volatile and may not be able to compensate for cumulative losses over time.

Trends in readmission rates for safety net hospitals and non-safety net hospitals in the era of the US Hospital Readmission Reduction Program: a retrospective time series analysis using Medicare administrative claims data from 2008 to 2015

ObjectiveTo compare trends in readmission rates among safety net and non-safety net hospitals under the US Hospital Readmission Reduction Program (HRRP).DesignA retrospective time series analysis using Medicare administrative claims data...

Improved Rates of Immediate Breast Reconstruction at Safety Net Hospitals

Substantial federal resources have been directed toward ensuring the delivery of high-quality care at safety net hospitals. Although disparities in receipt of breast reconstruction persist at the patient level, the extent to which hospital factors contribute to these differences remains unclear. The rates of immediate breast reconstruction across safety net and non-safety net hospitals were investigated. Women 21 years and older with breast cancer or increased risk of breast cancer undergoing immediate post-mastectomy reconstruction were identified in the Nationwide Inpatient Sample database. Safety net hospitals were defined as hospitals with the highest tertile of Medicaid disproportionate share hospital payment adjustments. Adjusted odds ratios of undergoing reconstruction were calculated. Thirty-one percent of patients (n = 10,910) at safety net hospitals underwent immediate reconstruction compared with 46 percent of patients (n = 14,619) at non-safety net hospitals (p < 0.001). Logistic regression revealed that women at non-safety net hospitals were significantly more likely to undergo reconstruction (OR, 1.89; 95 percent CI, 1.65 to 2.16). However, analysis by study year revealed that rates of reconstruction at safety net hospitals increased over time. After accounting for sociodemographic factors, women undergoing mastectomies at safety net hospitals remain less likely to undergo immediate breast reconstruction. However, the differences in rates of reconstruction between safety net and non-safety net hospitals have narrowed over time. The availability of immediate reconstruction lessens the psychological trauma of mastectomy, and it is critical to continue redirecting federal efforts toward this valuable component of breast cancer care. Risk, II.