California safety-net hospitals likely to be penalized by ACA value, readmission, and meaningful-use programs

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

Importance

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.

Objective

To estimate potential changes in hospital performance after HEA and examine hospital patient mix, structural, and geographic characteristics associated with receipt of increased payments.

Design, Setting, and Participants

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.

Exposures

Hospital Value-Based Purchasing program HEA.

Main Outcomes and Measures

Reclassification of HVBP bonus or penalty status and changes in payment adjustments across hospital characteristics.

Results

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.

Conclusions and Relevance

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 Finances During the First Two Years of the COVID-19 Pandemic: Evidence From Washington State Hospitals

The COVID-19 pandemic created a broad array of challenges for hospitals. These challenges included restrictions on admissions and procedures, patient surges, rising costs of labor and supplies, and a disparate impact on already disadvantaged populations. Many of these intersecting challenges put pressure on hospitals' finances. There was concern that financial pressure would be particularly acute for hospitals serving vulnerable populations, including safety-net (SN) hospitals and critical access hospitals (CAHs). Using data from hospitals in Washington State, we examined changes in operating margins for SN hospitals, CAHs, and other acute care hospitals in 2020 and 2021. We found that the operating margins for all three categories of hospitals fell from 2019 to 2020, with SNs and CAHs sustaining the largest declines. During 2021, operating margins improved for all three hospital categories but SN operating margins still remained negative. Both changes in revenue and changes in expenses contributed to observed changes in operating margins. Our study is one of the first to describe how the financial effects of COVID-19 differed for SNs, CAHs, and other acute care hospitals over the first two years of the pandemic. Our results highlight the continuing financial vulnerability of SNs and demonstrate how the factors that contribute to profitability can shift over time.

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.

Hospital Performance Under Alternative Readmission Measures Incorporating Observation Stays

OBJECTIVE

To determine the extent to which counting observation stays changes hospital performance on 30-day readmission measures.

METHODS

This was a retrospective study of inpatient admissions and observation stays among fee-for-service Medicare enrollees in 2017. We generated 3 specifications of 30-day risk-standardized readmissions measures: the hospital-wide readmission (HWR) measure utilized by the Centers for Medicare and Medicaid Services, which captures inpatient readmissions within 30 days of inpatient discharge; an expanded HWR measure, which captures any unplanned hospitalization (inpatient admission or observation stay) within 30 days of inpatient discharge; an all-hospitalization readmission (AHR) measure, which captures any unplanned hospitalization following any hospital discharge (observation stays are included in both the numerator and denominator of the measure). Estimated excess readmissions for hospitals were compared across the 3 measures. High performers were defined as those with a lower-than-expected number of readmissions whereas low performers had higher-than-expected or excess readmissions. Multivariable logistic regression identified hospital characteristics associated with worse performance under the measures that included observation stays.

RESULTS

Our sample had 2586 hospitals with 5,749,779 hospitalizations. Observation stays ranged from 0% to 41.7% of total hospitalizations. Mean (SD) readmission rates were 16.6% (5.4) for the HWR, 18.5% (5.7) for the expanded HWR, and 17.9% (5.7) in the all-hospitalization readmission measure. Approximately 1 in 7 hospitals (14.9%) would switch from being classified as a high performer to a low performer or vice-versa if observation stays were fully included in the calculation of readmission rates. Safety-net hospitals and those with a higher propensity to use observation would perform significantly worse.

CONCLUSIONS

Fully incorporating observation stays in readmission measures would substantially change performance in value-based programs for safety-net hospitals and hospitals with high rates of observation stays.

A Comparison of Clinical and Cost Outcomes After Pancreatectomies at a Safety-net Hospital using a National Registry

BACKGROUND

Our institution (UFHJ) meets the criteria of both a large, specialized medical center (LSCMC) and a safety-net hospital (AEH). Our aim is to compare pancreatectomy outcomes at UFHJ against other LSCMCs, AEHs, and against institutions that meet criteria for both LSCMC and AEH. In addition, we sought to evaluate differences between LSCMCs and AEHs.

MATERIALS AND METHODS

Pancreatectomies for pancreatic cancer were queried from the Vizient Clinical Data Base (2018 to 2020). Clinical and cost outcomes were compared between UFHJ and LSCMCs, AEHs, and a combined group, respectively. Indices >1 indicated the observed value was greater than the expected national benchmark value.

RESULTS

The mean number of pancreatectomy cases performed per institution in the LSCMC group was 12.15, 11.73, and 14.31 in 2018, 2019, and 2020, respectively. At AEHs, 25.33, 24.56, and 26.37 mean cases per institution per year, respectively. In the combined group of both LSCMCs and AEHs, 8.10, 7.60, and 7.22 mean cases, respectively. At UFHJ, 17, 34, and 39 cases were performed each year, respectively. Length of stay index decreased below national benchmarks at UFHJ (1.08 to 0.82), LSCMCs (0.91 to 0.85), and AEHs (0.94 to 0.93), with an increasing case mix index at UFHJ (3.33 to 4.20) from 2018 to 2020. In contrast, length of stay index increased in the combined group (1.14 to 1.18) and overall was the lowest at LSCMCs (0.89). Mortality index declined at UFHJ (5.07 to 0.00) below national benchmarks compared with LSCMCs (1.23 to 1.29), AEHs (1.19 to 1.45), and the combined group (1.92 to 1.99), and was significantly different between all groups ( P <0.001). Thirty-day re-admissions were lower at UFHJ (6.25% to 10.26%) compared with LSCMCs (17.62% to 16.83%) and AEHs (18.93% to 15.51%), and significantly lower at AEHs compared with LSCMCs ( P <0.001). Notably, 30-day re-admissions were lower at AEHs compared with LSCMCs ( P <0.001) and declined over time and were the lowest in the combined group in 2020 (17.72% to 9.52%). Direct cost index at UFHJ declined (1.00 to 0.67) below the benchmark compared with LSCMCs (0.90 to 0.93), AEHs (1.02 to 1.04), and the combined group (1.02 to 1.10). When comparing LSCMCs and AEHs, there were no significant differences between direct cost percentages ( P =0.56); however, the direct cost index was significantly lower at LSCMCs.

CONCLUSION

Pancreatectomy outcomes at our institution have improved over time exceeding national benchmarks and often were significant to LSCMCs, AEHs, and a combined comparator group. In addition, AEHs were able to maintain good quality care when compared with LSCMCs. This study highlights the role that safety-net hospitals can provide high-quality care to a medically vulnerable patient population in the presence of high-case volume.

Effect of Hospital Safety Net Burden on Survival for Patients With Sinonasal Squamous Cell Carcinoma

OBJECTIVE

To examine factors associated with hospital safety net burden and its impact on survival for patients with sinonasal squamous cell carcinoma (SNSCC).

STUDY DESIGN

Retrospective database study.

SETTING

National Cancer Database from 2004 to 2016.

METHODS

SNSCC cases were identified in the National Cancer Database. Hospital safety net burden was defined by percentage of uninsured/Medicaid patients treated, namely ≤25% for low-burden hospitals, 26% to 75% for medium-burden hospitals, and >75% for high-burden hospitals (HBHs). Univariate and multivariate analyses were used to investigate patient demographics, clinical characteristics, and overall survival.

RESULTS

An overall 6556 SNSCC cases were identified, with 1807 (27.6%) patients treated at low-burden hospitals, 3314 (50.5%) at medium-burden hospitals, and 1435 (21.9%) at HBHs. On multivariate analysis, Black race (odds ratio [OR], 1.39; 95% CI, 1.028-1.868), maxillary sinus primary site (OR, 1.31; 95% CI, 1.036-1.643), treatment at an academic/research program (OR, 20.63; 95% CI, 8.868-47.980), and treatment at a higher-volume facility (P < .001) resulted in increased odds of being treated at HBHs. Patients with grade III/IV tumor (OR, 0.70; 95% CI, 0.513-0.949), higher income (P < .05), or treatment modalities other than surgery alone (P < .05) had lower odds. Survival analysis showed that hospital safety net burden status was not significantly associated with overall survival (log-rank P = .727).

CONCLUSION

In patients with SNSCC, certain clinicopathologic factors, including Black race, lower income, treatment at an academic/research program, and treatment at facilities in the West region, were associated with treatment at HBHs. Hospital safety net burden status was not associated with differences in overall survival.

LEVEL OF EVIDENCE: 4

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

OBJECTIVE

To examine the limitations of peer grouping and associated challenges measuring social risk in Medicare's Hospital Readmission Reduction Program (HRRP). Under peer grouping, hospitals are divided into quintiles based on the proportion of a hospital's Medicare inpatients with Medicaid ("dual share"). This approach was implemented to address concerns that the HRRP unfairly penalized hospitals that disproportionately serve disadvantaged patients.

DATA

Public data on hospitals in the HRRP.

DESIGN

We examined the relationship between hospital dual share and readmission rates within peer groups; changes in hospitals' peer group assignments, readmission rates, and penalties; and the relationship between state Medicaid eligibility rules and peer groups.

DATA COLLECTION

Public data on hospital characteristics and readmission rates for 3119 hospitals from 2019 to 2020.

PRINCIPAL FINDINGS

The proportion of dual inpatients among hospitals of the same peer group varied by as much as 69 percentage points (ppt). Within peer groups, a one ppt increase in dual share was associated with a 0.01 ppt increase in the difference from the median readmission rate (p < 0.001). From 2019 to 2020, 8.8% of hospitals switched peer groups. Compared to hospitals that did not switch, those moving to a lower peer group had a higher mean penalty in 2020 (0.096 ppt; p = 0.006); those moving to a higher group had a lower mean penalty (-0.06 ppt; p = 0.079). However, changes in penalties did not correspond to changes in readmission rates. Hospitals in states with higher Medicaid income eligibility limits were more likely to be in higher peer groups.

CONCLUSIONS

Peer grouping is limited in the extent to which it accounts for differences in hospitals' patient populations, and it may not fully insulate hospitals from penalties linked to changes in patient mix. These problems arise from the construction of peer groups and the measure of social risk used to define them.

Hospital value-based payment programs and disparity in the United States: A review of current evidence and future perspectives

Beginning in the early 2010s, an array of Value-Based Purchasing (VBP) programs has been developed in the United States (U.S.) to contain costs and improve health care quality. Despite documented successes in these efforts in some instances, there have been growing concerns about the programs' unintended consequences for health care disparities due to their built-in biases against health care organizations that serve a disproportionate share of disadvantaged patient populations. We explore the effects of three Medicare hospital VBP programs on health and health care disparities in the U.S. by reviewing their designs, implementation history, and evidence on health care disparities. The available empirical evidence thus far suggests varied impacts of hospital VBP programs on health care disparities. Most of the reviewed studies in this paper demonstrate that hospital VBP programs have the tendency to exacerbate health care disparities, while a few others found evidence of little or no worsening impacts on disparities. We discuss several policy options and recommendations which include various reform approaches and specific programs ranging from those addressing upstream structural barriers to health care access, to health care delivery strategies that target service utilization and health outcomes of vulnerable populations under the VBP programs. Future studies are needed to produce more explicit, conclusive, and consistent evidence on the impacts of hospital VBP programs on disparities.

Readmissions performance and penalty experience of safety-net hospitals under Medicare's Hospital Readmissions Reduction Program

BACKGROUND

The 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.

METHODS

We 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.

RESULTS

Our 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.

CONCLUSIONS

Our results lend support to the concerns of disproportionately higher risk of performance-based penalty on safety-net hospitals.

Assessing and Augmenting Predictive Models for Hospital Readmissions With Novel Variables in an Urban Safety-net Population

BACKGROUND

The performance of existing predictive models of readmissions, such as the LACE, LACE+, and Epic models, is not established in urban safety-net populations. We assessed previously validated predictive models of readmission performance in a socially complex, urban safety-net population, and if augmentation with additional variables such as the Area Deprivation Index, mental health diagnoses, and housing access improves prediction. Through the addition of new variables, we introduce the LACE-social determinants of health (SDH) model.

METHODS

This retrospective cohort study included adult admissions from July 1, 2016, to June 30, 2018, at a single urban safety-net health system, assessing the performance of the LACE, LACE+, and Epic models in predicting 30-day, unplanned rehospitalization. The LACE-SDH development is presented through logistic regression. Predictive model performance was compared using C-statistics.

RESULTS

A total of 16,540 patients met the inclusion criteria. Within the validation cohort (n=8314), the Epic model performed the best (C-statistic=0.71, P<0.05), compared with LACE-SDH (0.67), LACE (0.65), and LACE+ (0.61). The variables most associated with readmissions were (odds ratio, 95% confidence interval) against medical advice discharge (3.19, 2.28-4.45), mental health diagnosis (2.06, 1.72-2.47), and health care utilization (1.94, 1.47-2.55).

CONCLUSIONS

The Epic model performed the best in our sample but requires the use of the Epic Electronic Health Record. The LACE-SDH performed significantly better than the LACE and LACE+ models when applied to a safety-net population, demonstrating the importance of accounting for socioeconomic stressors, mental health, and health care utilization in assessing readmission risk in urban safety-net patients.

Hospital-Acquired Conditions: A Review of Classical and Novel Risk Factors Following Total Hip and Knee Arthroplasties

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In 2016, a total of 48,771 hospital-acquired conditions (HACs) were reported in U.S. hospitals. These incidents resulted in an excess cost of >$2 billion, which translates to roughly $41,000 per patient per HAC.

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In the settings of total hip arthroplasty (THA) and total knee arthroplasty (TKA), increased age, a body mass index of >35 kg/m2, male sex, diabetes mellitus, electrolyte disturbances, and a history of anemia increase the likelihood of surgical site infections.

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Institution-specific (surgical) risk factors such as increased tourniquet time, an operative time of >130 minutes, bilateral procedures, a femoral nerve block, and general anesthesia increase the risk of HACs in the settings of THA and TKA.

Does Eco-Certification Correlate with Improved Financial Performance? Evidence From a Longitudinal Study in the US Hospital Industry

Health care-based negative production externalities, such as greenhouse gas emissions, underscore the need for hospitals to implement sustainable practices. Eco-certification has been adopted by a number of providers in an attempt, for instance, to curb energy consumption. While these strategies have been evaluated with respect to cost savings, their implications pertaining to hospitals' financial viability remain unknown. We specify a fixed-effects model to estimate the correlation between Energy Star certification and 3 different hospitals' financial performance measures (net patient revenue, operating expenses, and operating margin) in the United States between 2000 and 2016. The Energy Star participation indicators' parameters imply that this type of eco-certification is associated with lower net patient revenue and lower operating expenses. However, the estimated negative relationship between eco-certification and operating margin suggests that the savings in operating expenses are not enough for a hospital to achieve higher margins. These findings may indicate that undertaking sustainable practices is partially related to intangible benefits such as community reputation and highlight the importance of government policies to financially support hospitals' investments in green practices.

Disparities in Laryngeal Cancer Treatment and Outcomes: An Analysis by Hospital Safety-Net Burden

OBJECTIVES/HYPOTHESIS

To analyze the impact of hospital safety-net burden on survival outcomes for laryngeal squamous cell carcinoma (LSCC) patients.

STUDY DESIGN

Retrospective cohort study.

METHODS

From 2004 to 2015, 59,733 LSCC patients treated with curative intent were identified using the National Cancer Database. Low (LBH) <25th, medium (MBH) 25th-75th, and high (HBH) >75th safety-net burden hospitals were defined by the percentage quartiles (%) of uninsured/Medicaid-insured patients treated. Social and clinicopathologic characteristics and overall survival (using Kaplan-Meier survival analysis) were evaluated. Crude and adjusted hazard ratios (HR) with 95% confidence intervals (CI) were computed using Cox regression modeling.

RESULTS

There were 324, 647, and 323 hospitals that met the criteria as LBH, MBH, and HBH, respectively. The median follow-up was 38.6 months. A total of 27,629 deaths were reported, with a median survival of 75.8 months (a 5-year survival rate of 56.6%). Median survival was 83.2, 77.8, and 69.3 months for patients from LBH, MBH, and HBH, respectively (P < .0001). The median % of uninsured/Medicaid-insured patients treated among LBH, MBH, and HBH were 3.6%, 14.0%, and 27.0%, respectively. Patients treated at HBH were significantly more likely to be young, Black, Hispanic, of low income, and present with more advanced disease compared to LBH and MBH. Survival was comparable for LBH and MBH (HR = 1.02; 95% CI = 0.97-1.07, P = .408) on multivariate analysis. HBH, compared to LBH patients, had inferior survival (HR = 1.07; 95% CI = 1.01-1.13, P = .023).

CONCLUSIONS

High burden safety-net hospitals receive disproportionately more patients with advanced-stage and low socioeconomic status, yielding inferior survival compared to low burden hospitals.

LEVEL OF EVIDENCE

3 (individual cohort study) Laryngoscope, 131:E1987-E1997, 2021.

Diverse perspectives on hospitalisation events among people with dementia: protocol for a multisite qualitative study

INTRODUCTION

People living with dementia (PLWD) are more likely to experience hospitalisation events (hospitalisation, rehospitalisation) than those without dementia. Many hospitalisation events, particularly rehospitalisation within 30 days of discharge, are thought to be avoidable. Yet our understanding of dementia-specific risk and protective factors surrounding avoidable hospitalisation is limited to specific intersetting transitions and predominantly clinician perspectives. Broader insights are needed to design accessible and effective solutions for reducing avoidable hospitalisations. We have designed the Stakeholders Understanding of Prevention Protection and Opportunities to Reduce HospiTalizations (SUPPORT) Study to address these gaps. The objectives of the SUPPORT Study are to elicit and examine family caregiver, community and hospital providers' perspectives on avoidable hospitalisation events among PLWD, and to identify opportunities for effective prevention.

METHODS AND ANALYSIS

We will conduct a multisite, descriptive qualitative study to interview around 100 family caregivers, community and hospital providers. We will identify and sample from regions and communities with higher socio-contextual disadvantage and hospital utilisation, and will aim to recruit individuals representing diverse racial/ethnic backgrounds. Interviews will follow a descriptive qualitative design in conjunction with constant comparison techniques to sample divergent situations and events. We will employ a range of analytical approaches to address specific research questions including thematic (inductive and deductive), comparative and dimensional analysis. Interviews will be conducted individually or in focus groups and follow a semistructured interview guide.

ETHICS AND DISSEMINATION

The study is approved by the University of Wisconsin-Madison Institutional Review Board. Informed consent procedures will incorporate steps to evaluate capacity to provide informed consent in the event that participants express concerns with thinking or memory or demonstrate challenges recalling study details during the consent process to ensure capacity to consent to participation. A series of publicly available reports, seminars and symposia will be undertaken in collaboration with collaborating organisation partners.

The impact of hospital safety-net status on inpatient outcomes for brain tumor craniotomy: a 10-year nationwide analysis

Background

Outcome disparities have been documented at safety-net hospitals (SNHs), which disproportionately serve vulnerable patient populations. Using a nationwide retrospective cohort, we assessed inpatient outcomes following brain tumor craniotomy at SNHs in the United States.

Methods

We identified all craniotomy procedures in the National Inpatient Sample from 2002–2011 for brain tumors: glioma, metastasis, meningioma, and vestibular schwannoma. Safety-net burden was calculated as the number of Medicaid plus uninsured admissions divided by total admissions. Hospitals in the top quartile of burden were defined as SNHs. The association between SNH status and in-hospital mortality, discharge disposition, complications, hospital-acquired conditions (HACs), length of stay (LOS), and costs were assessed. Multivariate regression adjusted for patient, hospital, and severity characteristics.

Results

304,719 admissions were analyzed. The most common subtype was glioma (43.8%). Of 1,206 unique hospitals, 242 were SNHs. SNH admissions were more likely to be non-white (P < .001), low income (P < .001), and have higher severity scores (P = .034). Mortality rates were higher at SNHs for metastasis admissions (odds ratio [OR] = 1.48, P = .025), and SNHs had higher complication rates for meningioma (OR = 1.34, P = .003) and all tumor types combined (OR = 1.17, P = .034). However, there were no differences at SNHs for discharge disposition or HACs. LOS and hospital costs were elevated at SNHs for all subtypes, culminating in a 10% and 9% increase in LOS and costs for the overall population, respectively (all P < .001).

Conclusions

SNHs demonstrated poorer inpatient outcomes for brain tumor craniotomy. Further analyses of the differences observed and potential interventions to ameliorate interhospital disparities are warranted.

Hospital Location and Socioeconomic Disadvantage of Emergency General Surgery Patients

BACKGROUND

Emergency general surgery (EGS) patients are more socioeconomically vulnerable than elective counterparts. We hypothesized that a hospital's neighborhood disadvantage is associated with vulnerability of its EGS patients.

MATERIALS AND METHODS

Area deprivation index (ADI), a neighborhood-level measure of disadvantage, and key characteristics of 724 hospitals in 14 states were linked to patient-level data in State Inpatient Databases. Hospital and EGS patient characteristics were compared across hospital ADI quartiles (least disadvantaged [ADI 1-25] "affluent," minimally disadvantaged [ADI 26-50] "min-da", moderately disadvantaged [ADI 51-75] "mod-da", and most disadvantaged [ADI 76-100] "impoverished") using chi² tests and multivariable regression.

RESULTS

Higher disadvantage hospitals are more often nonteaching (affluent = 38.9%, min-da = 53.5%, mod-da = 72.1%, and impoverished = 67.6%), nonaffiliated with medical schools (50%, 72.4%, 81.8%, and 78.8%), and in rural areas (3.3%, 9.2%, 31.2%, and 27.9%). EGS patients at higher disadvantage hospitals are more likely to be older (43.9%, 48.6%, 49.1%, and 46.6%), have >3 comorbidities (17.0%, 19.0%, 18.4%, and 19.3%), live in low-income areas (21.4%, 23.6%, 32.2%, and 42.5%), and experience complications (23.2%, 23.7%, 24.0%, and 25.2%). Rates of uninsurance/underinsurance were highest at affluent and impoverished hospitals (18.0, 16.4%, 17.7%, and 19.2%). Higher disadvantage hospitals serve fewer minorities (32.6%, 21.3%, 20.7%, and 24.0%), except in rural areas (2.9%, 6.7%, 6.5%, and 15.5%). In multivariable analyses, the impoverished hospital ADI quartile did not predict odds of serving as a safety-net or predominantly minority-serving hospital.

CONCLUSIONS

Hospitals in impoverished areas disproportionately serve underserved EGS patient populations but are less likely to have robust resources for EGS care or train future EGS surgeons. These findings have implications for measures to improve equity in EGS outcomes.

Social determinants of health and hospital readmissions: can the HOSPITAL risk score be improved by the inclusion of social factors?

Background

The HOSPITAL Risk Score (HRS) predicts 30-day hospital readmissions and is internationally validated. Social determinants of health (SDOH) such as low socioeconomic status (SES) affect health outcomes and have been postulated to affect readmission rates. We hypothesized that adding SDOH to the HRS could improve its predictive accuracy.

Methods

Records of 37,105 inpatient admissions at the University of Chicago Medical Center were reviewed. HRS was calculated for each patient. Census tract-level SDOH then were combined with the HRS and the performance of the resultant “Social HRS” was compared against the HRS. Patients then were assigned to 1 of 7 typologies defined by their SDOH and a balanced dataset of 14,235 admissions was sampled from the larger dataset to avoid over-representation by any 1 sociodemographic group. Principal component analysis and multivariable linear regression then were performed to determine the effect of SDOH on the HRS.

Results

The c-statistic for the HRS predicting 30-day readmission was 0.74, consistent with published values. However, the addition of SDOH to the HRS did not improve the c-statistic (0.71). Patients with unfavorable SDOH (no high-school, limited English, crowded housing, disabilities, and age > 65 yrs) had significantly higher HRS (p < 0.05 for all). Overall, SDOH explained 0.2% of the HRS.

Conclusion

At an urban tertiary care center, the addition of census tract-level SDOH to the HRS did not improve its predictive power. Rather, the effects of SDOH are already reflected in the HRS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-020-05989-7.

Performance Of Safety-Net Hospitals In Year 1 Of The Comprehensive Care For Joint Replacement Model

The Comprehensive Care for Joint Replacement (CJR) model of 2016 aims to improve the quality and costs of care for Medicare beneficiaries undergoing hip and knee replacements. However, there are concerns that the safety-net hospitals that care for the greatest number of vulnerable patients may perform poorly in CJR. In this study, we used Medicare’s CJR data to evaluate the performance of 792 hospitals mandated to participate in the first year of CJR. We found that in comparison to non-safety-net hospitals, 42 percent fewer safety-net hospitals qualified for rewards based on their quality and spending performance (33 percent of safety-net hospitals qualified, compared to 57 percent of non-safety-net hospitals), and safety-net hospitals’ rewards per episode were 39 percent smaller ($456 compared to $743). Continuation of this performance trend might place safety-net hospitals at increased risk of penalties in future years. Medicare and hospital strategies such as those that reward high-quality care for vulnerable patients might enable safety-net hospitals to compete effectively in CJR.

Medicare Shared Savings Program and readmission rate among patients with ischemic stroke

OBJECTIVE

Hospitals participating in the Medicare Shared Savings Program (MSSP) share with the Centers for Medicare and Medicaid Services (CMS) the savings generated by reduced cost of care. Our aim was to determine whether MSSP is associated with changes in readmissions and mortality for Medicare patients hospitalized with ischemic stroke, and whether MSSP has a different impact on safety net hospitals (SNHs) compared to non-SNHs.

METHODS

This study was based on the CMS Hospital Compare data for risk-standardized 30-day readmission and mortality rates for Medicare patients hospitalized with ischemic strokes between 2010 and 2017. With a propensity score-matched sample, hospital-level difference-in-difference analysis was used to determine whether MSSP was associated with changes in hospital readmission and mortality as well as to examine the impact of MSSP on SNHs compared to non-SNHs.

RESULTS

MSSP-participating hospitals had slightly greater reductions in readmission rates compared to matched nonparticipating hospitals (difference, 0.25 percentage points; 95% confidence interval [CI], -0.42 to -0.08). Mortality rates decreased among all hospitals, but mortality reduction was not significantly different between MSSP-participating hospitals and matched hospitals (difference, 0.06 percentage points; 95% CI, -0.28 to 0.17). Prior to MSSP, readmission rates in SNHs were higher compared to non-SNHs, but MSSP did not have significantly different impact on hospital readmission and mortality rates for SNHs and non-SNHs.

CONCLUSION

MSSP led to slightly fewer readmissions without increases in mortality for Medicare patients hospitalized with ischemic stroke. Similar reductions in readmission rates were observed in SNHs and non-SNHs participating in MSSP, indicating persistent gaps between SNHs and non-SNHs.

Early Performance of Hospital Value-based Purchasing Program in Medicare: A Systematic Review

BACKGROUND

Under the Affordable Care Act, the Centers for Medicare and Medicaid Services has greatly expanded inpatient fee-for-value programs including the Hospital Value-based Purchasing (HVBP) program. Existing evidence from the HVBP program is mixed. There is a need for a systematic review of the HVBP program to inform discussions on how to improve the program's effectiveness.

OBJECTIVE

To review and summarize studies that evaluated the HVBP program's impact on clinical processes, patient satisfaction, costs and outcomes, or assessed hospital characteristics associated with performance on the program.

DESIGN

We searched the MEDLINE/PubMed, Scopus, ProQuest database for literature published between January 2013 and July 2019 using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines.

RESULTS

Of 988 studies reviewed, 33 studies that met the selection criteria were included. A small group of studies (n=7) evaluated the impact of the HVBP program, and no impact on processes or patient outcomes was reported. None of the included studies evaluated the effect of HVBP program on health care costs. Other studies (n=28) evaluated the hospital characteristics associated with HVBP performance, suggesting that safety-net hospitals reportedly performed worse on several quality and cost measures. Other hospital characteristics' associations with performance were unclear.

CONCLUSIONS

Our findings suggest that the current HVBP does not lead to meaningful improvements in quality of care or patient outcomes and may negatively affect safety-net hospitals. More rigorous and comprehensive adjustment is needed for more valid hospital comparisons.

Hospital Performance in the First 6 Years of Medicare's Value-Based Purchasing Program

The Medicare value-based purchasing (VBP) program, ongoing since 2013, uses financial bonuses and penalties to incentivize hospital quality improvements. Previous research has identified characteristics of penalized hospitals, but has not examined characteristics of hospitals with improvements in VBP program performance or consistent good performance. We identify five different trajectories of program performance (improvement, decline, consistent good or poor performance, mixed). A total of 11% of hospitals were penalized every year of the program, 24% improved their VBP program performance, 14% of hospitals consistently earned a bonus, while 18% performed well in the program's early years but experienced declines in performance. In 2013, organizational and community characteristics were associated with higher odds of improving relative to performing poorly every year. Few variables under managers' control were associated with program improvement, though accountable care organization participation was in some models. We find changes in VBP program metrics may have contributed to improvement in some hospitals' program scores.

Increased 30-day readmission rate after craniotomy for tumor resection at safety net hospitals in small metropolitan areas

PURPOSE

Unplanned readmission of post-operative brain tumor patients is often attributed to hospital and patient characteristics and is associated with higher mortality and cost. Previous studies demonstrate multiple patient outcome disparities in safety net hospitals (SNHs) when compared to non-SNHs. This study uses the Nationwide Readmissions Database (NRD) to determine if initial brain tumor resection at SNHs is associated with increased 30-day non-elective readmission rates.

METHODS

Patients with benign or malignant primary or metastatic brain tumor undergoing craniotomy for surgical resection were retrospectively identified in the NRD from 2010 to 2014. SNHs were defined as hospitals with Medicaid and uninsured patient burden in the top quartile. Descriptive and multivariate analyses employing survey-adjusted logistic regression evaluated patient and hospital level factors influencing 30-day readmissions.

RESULTS

During the study period, 83,367 patients met inclusion criteria. 44.7% of patients had a benign tumor, and 55.3% had a malignant tumor. Secondary CNS neoplasm (5.99%), post-operative infection (5.96%), and septicemia (4.26%) caused most readmissions within 30 days. Patients had increased unplanned readmission rates if they underwent craniotomy for tumor resection at a SNH in a small metropolitan area (OR 1.11, 95% CI 1.02-1.21, p = 0.01), but not at a SNH in a large metropolitan area (OR 0.99, 95% CI 0.93-1.05, p = 0.73).

CONCLUSION

This finding may reflect differences in access to care and disparities in neurosurgical resources between small and large metropolitan areas. Inequities in expertise and capacity are relevant as surgical volume was also related to readmission rates. Further studies may be warranted to address such disparities.

An exploration of community partnerships, safety-net hospitals, and readmission rates

OBJECTIVE

To compare hospital-community partnerships among safety-net hospitals relative to non-safety-net hospitals, and explore whether hospital-community partnerships are associated with reductions in readmission rates.

DATA SOURCES

Data from four nationwide hospital-level datasets for 2015-2016, including American Hospital Association (AHA) annual survey, Hospital Inpatient Prospective Payment System (IPPS) data, CMS Hospital Compare, and County Health Rankings National (CHRN) data.

STUDY DESIGN

We first examined how safety-net hospitals partner with nine different community providers, and how the overall and individual partnership patterns differ from those in non-safety-net hospitals. We then explored their association with 30-day readmission rates by diagnosis and hospital wide.

DATA COLLECTION/EXTRACTION METHODS

We included 1979 hospitals across 50 US states.

PRINCIPAL FINDINGS

Safety-net hospitals were more engaged in hospital-community partnerships, especially with local public health, local governments, social services, nonprofits, and insurance companies, relative to their non-safety-net peers. However, we found that such partnerships were not significantly related to reductions in readmission rates. The findings indicated that merely partnering with various community organizations may not be associated with readmission rate reduction.

CONCLUSIONS

Before promoting partnerships with various community organizations for its own sake, further prospective, longitudinal, and evidence-based guidance derived from the study of hospital-community partnerships is needed to make meaningful recommendations aimed at readmission rate reduction in safety-net hospitals.

The effect of hospital safety-net burden on outcomes, cost, and reportable quality metrics after emergent clipping and coiling of ruptured cerebral aneurysms

OBJECTIVE

Safety-net hospitals deliver care to a substantial share of vulnerable patient populations and are disproportionately impacted by hospital payment reform policies. Complex elective procedures performed at safety-net facilities are associated with worse outcomes and higher costs. The effects of hospital safety-net burden on highly specialized, emergent, and resource-intensive conditions are poorly understood. The authors examined the effects of hospital safety-net burden on outcomes and costs after emergent neurosurgical intervention for ruptured cerebral aneurysms.

METHODS

The authors conducted a retrospective analysis of the Nationwide Inpatient Sample (NIS) from 2002 to 2011. Patients ≥ 18 years old who underwent emergent surgical clipping and endovascular coiling for aneurysmal subarachnoid hemorrhage (SAH) were included. Safety-net burden was defined as the proportion of Medicaid and uninsured patients treated at each hospital included in the NIS database. Hospitals that performed clipping and coiling were stratified as low-burden (LBH), medium-burden (MBH), and high-burden (HBH) hospitals.

RESULTS

A total of 34,647 patients with ruptured cerebral aneurysms underwent clipping and 23,687 underwent coiling. Compared to LBHs, HBHs were more likely to treat black, Hispanic, Medicaid, and uninsured patients (p < 0.001). HBHs were also more likely to be associated with teaching hospitals (p < 0.001). No significant differences were observed among the burden groups in the severity of subarachnoid hemorrhage. After adjusting for patient demographics and hospital characteristics, treatment at an HBH did not predict in-hospital mortality, poor outcome, length of stay, costs, or likelihood of a hospital-acquired condition.

CONCLUSIONS

Despite their financial burden, safety-net hospitals provide equitable care after surgical clipping and endovascular coiling for ruptured cerebral aneurysms and do not incur higher hospital costs. Safety-net hospitals may have the capacity to provide equitable surgical care for highly specialized emergent neurosurgical conditions.

Disparities in length of stay for hip fracture treatment between patients treated in safety-net and non-safety-net hospitals

Background

Length of hospital stay (LOS) for hip fracture treatments is associated with mortality. In addition to patient demographic and clinical factors, hospital and payer type may also influence LOS, and thus mortality, among hip fracture patients; accordingly, outcome disparities between groups may arise from where patients are treated and from their health insurance type. The purpose of this study was to examine if where hip fracture patients are treated and how they pay for their care is associated with outcome disparities between patient groups. Specifically, we examined whether LOS differed between patients treated at safety-net and non-safety-net hospitals and whether LOS was associated with patients’ insurance type within each hospital category.

Methods

A sample of 48,948 hip fracture patients was extracted from New York State’s Statewide Planning and Research Cooperative System (SPARCS), 2014–2016. Using means comparison and X² tests, differences between safety-net and non-safety-net hospitals on LOS and patient characteristics were examined. Relationships between LOS and hospital category (safety-net or non-safety-net) and LOS and insurance type were further evaluated through negative binomial regression models.

Results

LOS was statistically (p ≤ 0.001) longer in safety-net hospitals (7.37 days) relative to non-safety-net hospitals (6.34 days). Treatment in a safety-net hospital was associated with a LOS that was 11.7% (p = 0.003) longer than in a non-safety-net hospital. Having Medicaid was associated with a longer LOS relative to having commercial health insurance.

Conclusion

Where hip fracture patients are treated is associated with LOS and may influence outcome disparities between groups. Future research should examine whether outcome differences between safety-net and non-safety-net hospitals are associated with resource availability and hospital payer mix.

How Have Hospitals in the Mississippi Delta Fared Under the 2019 Revised Hospital Readmissions Reduction Program?

In 2013, the Centers for Medicare and Medicaid Services (CMS) implemented the Hospital Readmissions Reduction Program (2013 HRRP), which financially penalized hospitals if their 30-day readmissions were higher than the national average. Without adjusting for socioeconomic status of patients, the 2013 HRRP overly penalized hospitals caring for the poor, especially hospitals in the Mississippi Delta region, one of the poorest regions in the U.S. In 2019, CMS revised the HRRP (2019 Revised HRRP) to stratify hospitals into quintiles based on the proportion of patients that are dual-eligible Medicare and Medicaid beneficiaries. This study aimed to examine the effect of the 2019 Revised HRRP on financial penalties for Delta hospitals using a difference-in-difference (DID) approach with data from the 2018 and 2019 HRRP Supplemental Files. The DID analysis found that relative to non-Delta hospitals, penalties in Delta hospitals were reduced by 0.08 percentage points from 2018 to 2019 (95% CI for the coefficient: -0.15, -0.01; P = .02), and the probability of a penalty was reduced by 6.64 percentage points (95% CI for the coefficient: -9.54, -3.75; P < .001). The stratification under the 2019 Revised HRRP is an important first step in reducing unfair penalties to hospitals that serve poor populations.

Caring for Patients With Uterine Cancer in Rural and Public Hospitals in New York State

OBJECTIVE

To evaluate perioperative outcomes for women with uterine cancer undergoing hysterectomy at rural and public hospitals in New York State.

METHODS

The New York Statewide Planning And Research Cooperative System database was used to identify women with uterine cancer who underwent hysterectomy from 2000 to 2015. Perioperative complications, inpatient mortality, and resource utilization were compared at rural, public and private hospitals. Multilevel mixed effect log-linear models were developed to evaluate the association between hospital type and outcomes of interest. Patient characteristics, hospital and surgeon clustering were accounted for within the model.

RESULTS

Over the years studied, there were 193 hospitals that cared for 46,298 women with uterine cancer. Of these, 9.8% were public, 15.0% were rural, and 75.1% were private metropolitan. They cared for 11.0%, 2.2% and 86.8% of patients, respectively. The proportion of patients cared for at rural hospitals decreased significantly from 5.2% in 2000 to 0.6% in 2014 (P<.001). There was no change in the volume of patients cared for at public hospitals (11.3 to 10.3%, P>.05). In a multivariable model adjusting for patient risk, there were no significant differences in perioperative morbidity, transfusion and length of stay across the three hospital types (P>.05). Compared with private hospitals, treatment at a rural hospital was associated with increased inpatient mortality (adjusted risk ratio 4.03, 95% CI 1.02-15.97).

CONCLUSION

In New York State, operative uterine cancer care is shifting away from rural hospitals. Public hospitals have similar risk-adjusted outcomes compared with private metropolitan facilities.

Inaugural Readmission Penalties for Total Hip and Total Knee Arthroplasty Procedures Under the Hospital Readmissions Reduction Program

IMPORTANCE

The Hospital Readmissions Reduction Program (HRRP) is a Centers for Medicare and Medicaid Services policy that levies hospital reimbursement penalties based on excess readmissions of patients with 4 medical conditions and 3 surgical procedures. A greater understanding of factors associated with the 3 surgical reimbursement penalties is needed for clinicians in surgical practice.

OBJECTIVE

To investigate the first year of HRRP readmission penalties applied to 2 surgical procedures-elective total hip arthroplasty (THA) and total knee arthroplasty (TKA)-in the context of hospital and patient characteristics.

DESIGN, SETTING, AND PARTICIPANTS

Fiscal year 2015 HRRP penalization data from Hospital Compare were linked with the American Hospital Association Annual Survey and with the Healthcare Cost and Utilization Project State Inpatient Database for hospitals in the state of Florida. By using a case-control framework, those hospitals were separated based on HRRP penalty severity, as measured with the HRRP THA and TKA excess readmission ratio, and compared according to orthopedic volume as well as hospital-level and patient-level characteristics. The first year of HRRP readmission penalties applied to surgery in Florida Medicare subsection (d) hospitals was examined, identifying 60 663 Medicare patients who underwent elective THA or TKA in 143 Florida hospitals. The data analysis was conducted from February 2016 to January 2017.

EXPOSURES

Annual hospital THA and TKA volume, other hospital-level characteristics, and patient factors used in HRRP risk adjustment.

MAIN OUTCOMES AND MEASURES

The HRRP penalties with HRRP excess readmission ratios were measured, and their association with annual THA and TKA volume, a common measure of surgical quality, was evaluated. The HRRP penalties for surgical care according to hospital and readmitted patient characteristics were then examined.

RESULTS

Among 143 Florida hospitals, 2991 of 60 663 Medicare patients (4.9%) who underwent THA or TKA were readmitted within 30 days. Annual hospital arthroplasty volume seemed to follow an inverse association with both unadjusted readmission rates (r = -0.16, P = .06) and HRRP risk-adjusted readmission penalties (r = -0.12, P = .14), but these associations were not statistically significant. Other hospital characteristics and readmitted patient characteristics were similar across HRRP orthopedic penalty severity.

CONCLUSIONS AND RELEVANCE

This study's findings suggest that higher-volume hospitals had less severe, but not significantly different, rates of readmission and HRRP penalties, without systematic differences across readmitted patients.

Comparison of 3 Safety-Net Hospital Definitions and Association With Hospital Characteristics

IMPORTANCE

No consensus exists on how to define safety-net hospitals (SNHs) for research or policy decision-making. Identifying which types of hospitals are classified as SNHs under different definitions is key to assessing policies that affect SNH funding.

OBJECTIVE

To examine characteristics of SNHs as classified under 3 common definitions.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional analysis includes noncritical-access hospitals in the Healthcare Cost and Utilization Project State Inpatient Databases from 47 US states for fiscal year 2015, linked to the Centers for Medicare & Medicaid Services Hospital Cost Reports and to the American Hospital Association Annual Survey. Data were analyzed from March 1 through September 30, 2018.

EXPOSURES

Hospital characteristics including organizational characteristics, scope of services provided, and financial attributes.

MAIN OUTCOMES AND MEASURES

Definitions of SNH based on Medicaid and Medicare Supplemental Security Income inpatient days historically used to determine Medicare Disproportionate Share Hospital (DSH) payments; Medicaid and uninsured caseload; and uncompensated care costs. For each measure, SNHs were defined as those within the top quartile for each state.

RESULTS

The 2066 hospitals in this study were distributed across the Northeast (340 [16.5%]), Midwest (587 [28.4%]), South (790 [38.2%]), and West (349 [16.9%]). Concordance between definitions was low; 269 hospitals (13.0%) or fewer were identified as SNHs under any 2 definitions. Uncompensated care captured smaller (200 of 523 [38.2%]) and more rural (65 of 523 [12.4%]) SNHs, whereas DSH index and Medicaid and uncompensated caseload identified SNHs that were larger (264 of 518 [51.0%] and 158 of 487 [32.4%], respectively) and teaching facilities (337 of 518 [65.1%] and 229 of 487 [47.0%], respectively) that provided more essential services than non-SNHs. Uncompensated care also distinguished remarkable financial differences between SNHs and non-SNHs. Under the uncompensated care definition, median (interquartile range [IQR]) bad debt ($27.1 [$15.5-$44.3] vs $12.8 [$6.7-$21.6] per $1000 of operating expenses; P < .001) and charity care ($19.9 [$9.3-$34.1] vs $9.1 [$4.0-$18.7] per $1000 of operating expenses) were twice as high and median (IQR) unreimbursed costs ($32.6 [$12.4-$55.4] vs $23.6 [$9.0-$42.7] per $1000 of operating expenses; P < .001) were 38% higher for SNHs than for non-SNHs. Safety-net hospitals defined by uncompensated care burden had lower median (IQR) total (4.7% [0%-9.9%] vs 5.8% [1.2%-11.2%]; P = .003) and operating (0.3% [-8.0% to 7.2%] vs 2.3% [-3.9% to 8.9%]; P < .001) margins than their non-SNH counterparts, whereas differences between SNH and non-SNH profit margins generally were not statistically significant under the other 2 definitions.

CONCLUSIONS AND RELEVANCE

Different SNH definitions identify hospitals with different characteristics and financial conditions. The new DSH formula, which accounts for uncompensated care, may lead to redistributed payments across hospitals. Our results may inform which types of hospitals will experience funding changes as DSH payment policies evolve.

Association of Stratification by Dual Enrollment Status With Financial Penalties in the Hospital Readmissions Reduction Program

IMPORTANCE

Beginning in fiscal year 2019, Medicare's Hospital Readmissions Reduction Program (HRRP) stratifies hospitals into 5 peer groups based on the proportion of each hospital's patient population that is dually enrolled in Medicare and Medicaid. The effect of this policy change is largely unknown.

OBJECTIVE

To identify hospital and state characteristics associated with changes in HRRP-related performance and penalties after stratification.

DESIGN, SETTING, AND PARTICIPANTS

A cross-sectional analysis was performed of all 3049 hospitals participating in the HRRP in fiscal years 2018 and 2019, using publicly available data on hospital penalties, merged with information on hospital characteristics and state Medicaid eligibility cutoffs.

EXPOSURES

The HRRP, under the 2018 traditional method and the 2019 stratification method.

MAIN OUTCOMES AND MEASURES

Performance on readmissions, as measured by the excess readmissions ratio, and penalties under the HRRP both in relative percentage change and in absolute dollars.

RESULTS

The study sample included 3049 hospitals. The mean proportion of dually enrolled beneficiaries ranged from 9.5% in the lowest quintile to 44.7% in the highest quintile. At the hospital level, changes in penalties ranged from an increase of $225 000 to a decrease of more than $436 000 after stratification. In total, hospitals in the lowest quintile of dual enrollment saw an increase of $12 330 157 in penalties, while those in the highest quintile of dual enrollment saw a decrease of $22 445 644. Teaching hospitals (odds ratio [OR], 2.13; 95% CI, 1.76-2.57; P < .001) and large hospitals (OR, 1.51; 95% CI, 1.22-1.86; P < .001) had higher odds of receiving a reduced penalty. Not-for-profit hospitals (OR, 0.64; 95% CI, 0.52-0.80; P < .001) were less likely to have a penalty reduction than for-profit hospitals, and hospitals in the Midwest (OR, 0.44; 95% CI, 0.34-0.57; P < .001) and South (OR, 0.42; 95% CI, 0.30-0.57; P < .001) were less likely to do so than hospitals in the Northeast. Hospitals with patients from the most disadvantaged neighborhoods (OR, 2.62; 95% CI, 2.03-3.38; P < .001) and those with the highest proportion of beneficiaries with disabilities (OR, 3.12; 95% CI, 2.50-3.90; P < .001) were markedly more likely to see a reduction in penalties, as were hospitals in states with the highest Medicaid eligibility cutoffs (OR, 1.79; 95% CI, 1.50-2.14; P < .001).

CONCLUSIONS AND RELEVANCE

Stratification of the hospitals under the HRRP was associated with a significant shift in penalties for excess readmissions. Policymakers should monitor the association of this change with readmission rates as well as hospital financial performance as the policy is fully implemented.

Adjusting for social risk factors impacts performance and penalties in the hospital readmissions reduction program

OBJECTIVE

Medicare's Hospital Readmissions Reduction Program (HRRP) does not account for social risk factors in risk adjustment, and this may lead the program to unfairly penalize safety-net hospitals. Our objective was to determine the impact of adjusting for social risk factors on HRRP penalties.

STUDY DESIGN

Retrospective cohort study.

DATA SOURCES/STUDY SETTING

Claims data for 2 952 605 fee-for-service Medicare beneficiaries with acute myocardial infarction (AMI), congestive heart failure (CHF) or pneumonia from December 2012 to November 2015.

PRINCIPAL FINDINGS

Poverty, disability, housing instability, residence in a disadvantaged neighborhood, and hospital population from a disadvantaged neighborhood were associated with higher readmission rates. Under current program specifications, safety-net hospitals had higher readmission ratios (AMI, 1.020 vs 0.986 for the most affluent hospitals; pneumonia, 1.031 vs 0.984; and CHF, 1.037 vs 0.977). Adding social factors to risk adjustment cut these differences in half. Over half the safety-net hospitals saw their penalty decline; 4-7.5 percent went from having a penalty to having no penalty. These changes translated into a $17 million reduction in penalties to safety-net hospitals.

CONCLUSIONS

Accounting for social risk can have a major financial impact on safety-net hospitals. Adjustment for these factors could reduce negative unintended consequences of the HRRP.

Hospital uncompensated care and patient experience: An instrumental variable approach

OBJECTIVE

Examine the endogenous relationship between uncompensated care and hospital patient experience scores.

DATA SOURCES/STUDY SETTING

The Hospital Consumer Assessment of Healthcare Providers and Systems Survey, CMS Healthcare Cost Report Information System, and the US Census Bureau.

STUDY DESIGN

The exogenous change in uncompensated care caused by the 2014 Medicaid expansion was exploited to measure the effect of uncompensated care on patient experience scores using a 2SLS regression with instrumental variables approach.

DATA COLLECTION/EXTRACTION METHODS

U.S. general, short-term hospitals whose DSH status remained constant and had nonmissing data for 2011-2015, which totaled 969 unique hospitals per year.

PRINCIPAL FINDINGS

The effect of uncompensated care on patient experience was in the predicted direction, with three of the 10 measures being statistically significant. A one percentage point increase in uncompensated care costs resulted in a 0.25-0.50 percentage point decrease in select patient experience scores.

CONCLUSIONS

Results indicate a weak relationship between uncompensated care and patient experience scores, as a reduction in uncompensated care is related to quality improvement for some hospitals. These findings have implications for hospitals as they navigate changing reimbursement structures and policy makers considering changes to Obama-era health care reforms.

The Importance of Safety-Net Hospitals in Emergency General Surgery

INTRODUCTION

Safety-net hospitals provide care to an inherently underprivileged patient population. These hospitals have previously been shown to have inferior surgical outcomes after complex, elective procedures, but little is known about how hospital payer-mix correlates with outcomes after more common, emergent operations.

METHODS

The University HealthSystem Consortium database was queried for all emergency general surgery procedures performed from 2009 to 2015. Emergency general surgery was defined as the seven operative procedures recently identified as contributing most to the national burden. Only urgent and emergent admissions were included (n = 653,305). Procedure-specific cohorts were created and hospitals were grouped according to safety-net burden. Multivariate analyses were done to study the effect of safety-net burden on hospital outcomes.

RESULTS

For all seven emergency procedures, patients at hospitals with a high safety-net burden were more likely to be young and black (p < 0.01 each). Patients at high-burden hospitals had similar severity of illness scores to those at other hospitals. Compared with lower burden hospitals, in-hospital mortality rates at high-burden hospitals were similar or lower in five of seven procedures (p = NS or < 0.01, respectively). After adjusting for patient factors, high-burden hospitals had similar or lower odds of readmission in six of seven procedures, hospital length of stay in four of seven procedures, and cost of care in three of seven procedures (p = NS or < 0.01, respectively).

CONCLUSION

Safety-net hospitals provide emergency general surgery services without compromising patient outcomes or incurring greater healthcare resources. These data may help inform the vital role these institutions play in the healthcare of vulnerable patients in the USA.

Primary care clinicians' perspectives about quality measurements in safety-net clinics and non-safety-net clinics

BACKGROUND

Quality metrics, pay for performance (P4P), and value-based payments are prominent aspects of the current and future American healthcare system. However, linking clinic payment to clinic quality measures may financially disadvantage safety-net clinics and their patient population because safety-net clinics often have worse quality metric scores than non-safety net clinics. The Minnesota Safety Net Coalition's Quality Measurement Enhancement Project sought to collect data from primary care providers' (PCPs) experiences, which could assist Minnesota policymakers and state agencies as they create a new P4P system. Our research study aims are to identify PCPs' perspectives about 1) quality metrics at safety net clinics and non-safety net clinics, 2) how clinic quality measures affect patients and patient care, and 3) how payment for quality measures may influence healthcare.

METHODS

Qualitative interviews with 14 PCPs (4 individual interviews and 3 focus groups) who had worked at both safety net and non-safety net primary care clinics in Minneapolis-St Paul Minnesota USA metropolitan area. Qualitative analyses identified major themes.

RESULTS

Three themes with sub-themes emerged. Theme #1: Minnesota's current clinic quality scores are influenced more by patients and clinic systems than by clinicians. Theme #2: Collecting data for a set of specific quality measures is not the same as measuring quality healthcare. Subtheme #2.1: Current quality measures are not aligned with how patients and clinicians define quality healthcare. Theme #3: Current quality measures are a product of and embedded in social and structural inequities in the American health care system. Subtheme #3.1: The current inequitable healthcare system should not be reinforced with financial payments. Subtheme #3.2: Health equity requires new metrics and a new healthcare system. Overall, PCPs felt that the current inequitable quality metrics should be replaced by different metrics along with major changes to the healthcare system that could produce greater health equity.

CONCLUSION

Aligning payment with the current quality metrics could perpetuate and exacerbate social inequities and health disparities. Policymakers should consider PCPs' perspectives and create a quality-payment framework that does not disadvantage patients who are affected by social and structural inequities as well as the clinics and providers who serve them.

Changes to Racial Disparities in Readmission Rates After Medicare's Hospital Readmissions Reduction Program Within Safety-Net and Non-Safety-Net Hospitals

Importance

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.

Objective

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.

Design, Setting, and Participants

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.

Main Outcomes and Measures

Trends in 30-day readmission rates among white and black patients by quarter and differences in trends across periods.

Results

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.

Conclusions and Relevance

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.

Racial and Ethnic Composition of Hospitals' Service Areas and the Likelihood of Being Penalized for Excess Readmissions by the Medicare Program

BACKGROUND

The Hospital Readmission Reduction Program (HRRP) disproportionately penalizes hospitals serving minority communities. The National Academy of Science, Engineering, and Medicine has recommended that the Centers for Medicare and Medicaid Services (CMS) consider adjusting for social risk factors in their risk adjustment methodology. This study examines the association between the racial and ethnic composition of a hospital market and the impact of other social risk factors on the probability of a hospital being penalized under the HRRP.

RESEARCH METHODS AND DATA

This study analyzes data from CMS, the American Hospital Association, and the American Community Survey for 3168 hospitals from 2013 to 2017. We used logistic regression models to estimate the association between the penalty status under HRRP and the racial and ethnic composition of a hospital market, and explored whether this association was moderated by other social risk factors.

RESULTS

Our results indicate that the probability of being penalized increases with the percentage of black and Asian residents in the hospital service area (HSA) and decreased with the percentage of Hispanic residents in the HSA. This association was reduced and became statistically insignificant when we controlled for other social risk factors. The strongest predictors of penalty status were the hospital's share of Medicaid patients and the percent of persons without a high school diploma in the HSA.

CONCLUSIONS

By incorporating relevant social risk factors in the reimbursement methodology, CMS could mitigate the negative effects of HRRP on hospitals serving minority communities.

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

OBJECTIVE

To examine relationships between penalties assessed by Medicare's Hospital Readmission Reduction Program and Value-Based Purchasing Program and hospital financial condition.

DATA SOURCES/STUDY SETTING

Centers for Medicare and Medicaid Services, American Hospital Association, and Area Health Resource File data for 4,824 hospital-year observations.

STUDY DESIGN

Bivariate and multivariate analysis of pooled cross-sectional data.

PRINCIPAL FINDINGS

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.

CONCLUSIONS

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.

Moneyball in Medicare

US policymakers place high priority on tying Medicare payments to the value of care delivered. A critical part of this effort is the Hospital Value-based Purchasing Program (HVBP), which rewards or penalizes hospitals based on their quality and episode-based costs of care and incentivizes integration between hospitals and post-acute care providers. Within HVBP, each patient affects hospital performance on a variety of quality and spending measures, and performance translates directly to changes in program points and ultimately dollars. In short, hospital revenue from a patient consists not only of the DRG payment, but also of that patient's marginal future reimbursement. We estimate the magnitude of the marginal future reimbursement for individual patients across each type of quality and performance measure. We describe how those incentives differ across hospitals, including integrated and safety-net hospitals. We find evidence that hospitals improved their performance over time in the areas where they have the highest marginal incentives to improve care, and that integrated hospitals responded more than non-integrated hospitals.

Differential Impact of Hospital and Community Factors on Medicare Readmission Penalties

OBJECTIVE

To identify hospital/county characteristics and sources of regional heterogeneity associated with readmission penalties.

DATA SOURCES/STUDY SETTING

Acute care hospitals under the Hospital Readmissions Reduction Program from fiscal years 2013 to 2018 were linked to data from the Annual Hospital Association, Centers for Medicare and Medicaid Services, Medicare claims, Hospital Compare, Nursing Home Compare, Area Resource File, Health Inequity Project, and Long-term Care Focus. The final sample contained 3,156 hospitals in 1,504 counties.

DATA COLLECTION/EXTRACTION METHODS

Data sources were combined using Medicare hospital identifiers or Federal Information Processing Standard codes.

STUDY DESIGN

A two-level hierarchical model with correlated random effects, also known as the Mundlak correction, was employed with hospitals nested within counties.

PRINCIPAL FINDINGS

Over a third of the variation in readmission penalties was attributed to the county level. Patient sociodemographics and the surrounding access to and quality of care were significantly associated with penalties. Hospital measures of Medicare volume, percentage dual-eligible and Black patients, and patient experience were correlated with unobserved area-level factors that also impact penalties.

CONCLUSIONS

As the readmission risk adjustment does not include any community-level characteristics or geographic controls, the resulting endogeneity bias has the potential to disparately penalize certain hospitals.

Estimates and Temporal Trend for US Nationwide 30-Day Hospital Readmission Among Patients With Ischemic and Hemorrhagic Stroke

IMPORTANCE

Readmission reduction is linked to improved quality of care, saves cost, and is a desirable patient-centered outcome. Nationally representative readmission metrics for patients with stroke are unavailable to date. Such estimates are necessary for benchmarking performance.

OBJECTIVES

To provide US nationwide estimates and a temporal trend for overall, planned, and potentially preventable 30-day hospital readmission among patients with ischemic and hemorrhagic stroke; to investigate the association between hospitals' stroke discharge volume, teaching status, and 30-day readmission; and to highlight reasons for 30-day readmission and explore the association of 30-day readmission in terms of mortality, length of stay, and cost of care among patients with stroke.

DESIGN, SETTING, AND PARTICIPANTS

Cohort, year-wise analysis of the Nationwide Readmissions Database between January 1, 2010, and September 30, 2015. The setting was a population-based cohort study providing national estimates of 30-day readmission. The database represents 50% of all US hospitalizations from 22 geographically dispersed states. Participants were adult (≥18 years) patients with a primary discharge diagnosis of intracerebral hemorrhage, acute ischemic stroke, or subarachnoid hemorrhage. Hospitals were categorized by their annual stroke discharge volume and were classified as teaching hospitals if they had an American Medical Association-approved residency program or had a ratio of full-time equivalent interns and residents to beds of 0.25 or higher.

MAIN OUTCOMES AND MEASURES

Readmission was defined as any admission within 30 days of index hospitalization discharge. Using Centers for Medicare & Medicaid Services-defined algorithms, events were classified as planned or unplanned and as potentially preventable.

RESULTS

Based on study criteria, 2 078 854 eligible patients were included (mean [SE] age, 70.02 [0.07] years; 51.9% female). Thirty-day readmission was highest for patients with intracerebral hemorrhage (13.70%; 95% CI, 13.40%-13.99%), followed by patients with acute ischemic stroke (12.44%; 95% CI, 12.33%-12.55%) and patients with subarachnoid hemorrhage (11.48%; 95% CI, 11.01%-11.96%). On average, there was a 3.3% annual decline in readmission between 2010 and 2014, which was statistically significant for the period of investigation (odds ratio, 0.96; 95% CI, 0.95-0.97). Patients discharged from nonteaching hospitals with high stroke discharge volume were at a significantly higher risk of 30-day readmission, and the top 2 reasons for readmission were acute cerebrovascular disease and septicemia.

CONCLUSIONS AND RELEVANCE

This study suggests that nationally representative readmission metrics can be used to benchmark hospitals' performance, and a temporal trend of 3.3% may be used to evaluate the effectiveness of readmission reduction strategies.

Shifts in Medicaid and Uninsured Payer Mix at Safety-Net and Non-Safety-Net Hospitals During the Great Recession

EXECUTIVE SUMMARY

There has been ongoing concern regarding the viability of safety-net hospitals (SNHs), which care for vulnerable populations. The authors examined payer mix at SNHs and non-SNHs during a period covering the Great Recession using data from the 2006 to 2012 Healthcare Cost and Utilization Project State Inpatient Databases from 38 states. The number of privately insured stays decreased at both SNHs and non-SNHs. Non-SNHs increasingly served Medicaid-enrolled and uninsured patients; in SNHs, the number of Medicaid stays decreased and uninsured stays remained stable. These study findings suggest that SNHs were losing Medicaid-enrolled patients relative to non-SNHs before the Medicaid expansion under the Affordable Care Act (ACA). Postexpansion, Medicaid stays will likely increase for both SNHs and non-SNHs, but the increase at SNHs may not be as large as expected if competition increases. Because hospital stays with private insurance and Medicaid help SNHs offset uncompensated care, a lower-than-expected increase could affect SNHs' ability to care for the remaining uninsured population. Continued monitoring is needed once post-ACA data become available.

Regional Variation in 30-Day Ischemic Stroke Outcomes for Medicare Beneficiaries Treated in Get With The Guidelines-Stroke Hospitals

BACKGROUND

We explored regional variation in 30-day ischemic stroke mortality and readmission rates and the extent to which regional differences in patients, hospitals, healthcare resources, and a quality of care composite care measure explain the observed variation.

METHODS AND RESULTS

This ecological analysis aggregated patient and hospital characteristics from the Get With The Guidelines-Stroke registry (2007-2011), healthcare resource data from the Dartmouth Atlas of Health Care (2006), and Medicare fee-for-service data on 30-day mortality and readmissions (2007-2011) to the hospital referral region (HRR) level. We used linear regression to estimate adjusted HRR-level 30-day outcomes, to identify HRR-level characteristics associated with 30-day outcomes, and to describe which characteristics explained variation in 30-day outcomes. The mean adjusted HRR-level 30-day mortality and readmission rates were 10.3% (SD=1.1%) and 13.1% (SD=1.1%), respectively; a modest, negative correlation (r=-0.17; P=0.003) was found between one another. Demographics explained more variation in readmissions than mortality (25% versus 6%), but after accounting for demographics, comorbidities accounted for more variation in mortality compared with readmission rates (17% versus 7%). The combination of hospital characteristics and healthcare resources explained 11% and 16% of the variance in mortality and readmission rates, beyond patient characteristics. Most of the regional variation in mortality (65%) and readmission (50%) rates remained unexplained.

CONCLUSIONS

Thirty-day mortality and readmission rates vary substantially across HRRs and exhibit an inverse relationship. While regional variation in 30-day outcomes were explained by patient and hospital factors differently, much of the regional variation in both outcomes remains unexplained.

Most Hospitals Received Annual Penalties For Excess Readmissions, But Some Fared Better Than Others

The Hospital Readmissions Reduction Program (HRRP) initiated by the Affordable Care Act levies financial penalties against hospitals with excess thirty-day Medicare readmissions. We sought to understand the penalty burden over the program's first five years, focusing on characteristics of hospitals that received penalties during all five years, how penalties changed over time, and the relationship between baseline and subsequent performance. More than half of participating hospitals were penalized by the Centers for Medicare and Medicaid Services in all five years of the program. From fiscal years 2013 to 2017, the growth in average penalties was modest, doubling from 0.29 percent to 0.60 percent, despite increasing opportunities for penalization. The penalty burden was greater in hospitals that were urban, major teaching, large, or for-profit and that treated larger shares of Medicare or socioeconomically disadvantaged patients. Surprisingly, hospitals treating greater proportions of medically complex Medicare patients had a lower cumulative penalty burden compared to those treating fewer proportions of these patients. Lastly, we found that hospitals with high baseline penalties in the first year continued to receive significantly higher penalties in subsequent years. For many hospitals, the HRRP leads to persistent penalization and limited capacity to reduce penalty burden. Alternative structures might avoid persistent penalization, while still motivating reductions in hospital readmissions.

Inappropriate oophorectomy at time of benign premenopausal hysterectomy

OBJECTIVE

We assessed rates of oophorectomy during benign hysterectomy around the release of the American College of Obstetricians and Gynecologists 2008 practice bulletin on prophylactic oophorectomy, and evaluated predictors of inappropriate premenopausal oophorectomy.

METHODS

A cross-sectional administrative database analysis was performed utilizing the California Office of Statewide Health Planning Development Patient Discharge Database for years 2005 to 2011. After identifying all premenopausal women undergoing hysterectomy for benign conditions, International Classification of Diseases (ICD)-9 diagnosis codes were reviewed to create a master list of indications for oophorectomy. We defined appropriate oophorectomy as cases with concomitant coding for ovarian cyst, breast cancer susceptibility gene carrier status, and other diagnoses. Using patient demographics and hospital characteristics to predict inappropriate oophorectomy, a logistic regression model was created.

RESULTS

We identified 57,776 benign premenopausal hysterectomies with oophorectomies during the period studied. Of the premenopausal oophorectomies, 37.7% (21,783) were deemed "inappropriate" with no documented reason for removal. The total number of premenopausal inpatient hysterectomies with oophorectomy decreased yearly (12,227/y in 2005 to 5,930/y in 2011). However, the percentage of inappropriate oophorectomies remained stable. In multivariate analysis, Hispanic and African American ethnicity/race associated with increased odds of inappropriate oophorectomy (P < 0.001). Urban and at low Medi-Cal utilization hospitals showed increased odds of inappropriate oophorectomy.

CONCLUSIONS

In premenopausal women undergoing benign hysterectomy, over one-third undergo oophorectomy without an appropriate indication documented. The rate of inappropriate oophorectomy in California has not changed since the 2008 American College of Obstetricians and Gynecologists guidelines. Whereas the absolute number of inpatient hysterectomies for benign indications has decreased, our work suggests persistent utilization of oophorectomy in premenopausal women, despite well-documented long-term adverse health implications.

Could Pay-for-Performance Worsen Health Disparities?

Pay-for-performance (P4P) has become a prominent component of health care funding in the Affordable Care Act (ACA) era. Although the ACA's future remains unclear, these programs receive bipartisan support and will likely continue to be a part of payment policies. At the same time, racial and class disparities remain among the most pressing of the many challenges facing the US health system. We review evidence of the effects of P4P on disparities at the population and individual levels. Providers caring for predominantly minority patients or those with lower socioeconomic status are known to have poorer quality metrics. Financial penalties run the risk of exacerbating disparities along race and class lines and across hospitals. The evidence regarding P4P programs is mixed, with safety-net hospitals facing greater penalties but with some improvement in outcomes among minority patients. A better understanding of the longitudinal effects of these plans is needed, and policymakers should be conscious of the risks in expanding these programs.

Thirty-Day Inpatient Readmissions for Asian American and Pacific Islander Subgroups Compared With Whites

Asian and Pacific Islander (API) 30-day potentially preventable readmissions (PPRs) are understudied. Hawaii Health Information Corporation data from 2007-2012 statewide adult hospitalizations ( N = 495,910) were used to compare API subgroup and White PPRs. Eight percent of hospitalizations were PPRs. Seventy-two percent of other Pacific Islanders, 60% of Native Hawaiians, and 52% of Whites with a PPR were 18 to 64 years, compared with 22% of Chinese and 21% of Japanese. In multivariable models including payer, hospital, discharge year, residence location, and comorbidity, PPR disparities existed for some API subpopulations 65+ years, including Native Hawaiian men (odds ratio [OR] = 1.14; 95% confidence interval [CI] = 1.04-1.24), Filipino men (OR = 1.19; 95% CI = 1.04-1.38), and other Pacific Islander men (OR = 1.30; 95% CI = 1.19-1.43) and women (OR = 1.23; 95% CI = 1.02-1.51) compared with Whites, while many API groups 18 to 64 years had significantly lower PPR odds. Distinct PPR characteristics across API subpopulations and age groups can inform policy and practice. Further research should determine why elderly API have higher PPR rates, while nonelderly rates are lower.