Association of Allergy Specialty Care and Asthma Outcomes for Medicaid-Enrolled Children.

OBJECTIVE: To evaluate the comparative effectiveness of allergy specialist care for children with asthma enrolled in the Arkansas Medicaid program. STUDY DESIGN: We used the Arkansas All-Payers Claims Database (APCD) to identify Medicaid-enrolled children with asthma who had an allergy specialist visit in 2018. These children were propensity score matched to children without an allergy specialist visit to evaluate differences in asthma-related adverse events (AAE), specifically emergency department visits and/or hospitalizations in 2019. Multivariable logistic regression was used to assess the association between allergy specialist care in 2018 and AAEs in 2019. RESULTS: Prior to matching, a higher percentage of children with an allergy specialist visit had persistent asthma, were atopic, and received influenza vaccination. In the matched sample, 10.1% of identified patients experienced an AAE in 2019. Adjusted analysis showed 21.0% lower odds of AAEs (aOR: 0.79; 95%CI: 0.63, 0.98) in 2019 for children with an allergy specialist visit (n=2,964) in 2018 compared with those without an allergy specialist visit (ME: 9.1% vs 11.0%; p=0.04). CONCLUSIONS: Children with asthma enrolled in Arkansas Medicaid who saw an allergy specialist were less likely to have an AAE. Asthma quality metrics developed using guideline-based recommendations for allergy specialist care should be considered for asthma health management programs.

Risk of adverse infant outcomes associated with maternal mental health and substance use disorders.

PURPOSE: This study aimed to evaluate the association of mental health and substance use disorders on the risk of adverse infant outcomes overall and by race/ethnicity and payer. METHODS: We used birth certificates (2017-2022; n = 125,071) linked with state-wide insurance claims (2016-2022; n = 7,583,488) to assess the risk of an adverse infant outcome (i.e., prematurity [< 37 weeks gestation] or low birthweight [< 2,500 g]) associated with "any mental health" or "any substance use" disorder overall, by race/ethnicity, and by payer using diagnoses during the 9 months of pregnancy. We additionally evaluated seven specific mental health conditions and four specific substance use disorders. RESULTS: The rate of having an adverse infant outcome was 13.4%. Approximately 21.5% of birthing individuals had a mental health condition, and 8.7% had a substance use disorder. We found increased adjusted risk of an adverse infant outcome associated with having a mental health condition overall (aRR: 1.28; 95%CI: 1.23-1.32) and for all racial/ethnic groups and payers. We additionally found increased risk associated with substance use disorder overall (aRR: 1.32; 95%CI: 1.25-1.40) and for White, Black, privately-covered, and Medicaid-covered individuals. There was increased risk associated with six of seven mental health and three of four substance use disorders. CONCLUSIONS: Given the risk of adverse infant outcomes associated with mental health and substance use disorders across racial/ethnic groups and payers, our findings highlight the critical importance of policies and clinical guidelines that support early identification and treatment of a broad spectrum of mental health and substance use disorders throughout the perinatal period.

Association of copayments with healthcare utilization and expenditures among Medicaid enrollees with a substance use disorder.

BACKGROUND: The purpose of this study was to examine the association between copayments and healthcare utilization and expenditures among Medicaid enrollees with substance use disorders. METHODS: This study used claims data (2020-2021) from a private insurer participating in Arkansas's Medicaid expansion. We compared service utilization and expenditures for enrollees in different Medicaid program structures with varying copayments. Enrollees with incomes above 100 % FPL (N = 10,240) had copayments for substance use treatment services while enrollees below 100 % FPL (N = 2478) did not. Demographic, diagnostic, utilization, and cost information came from claims and enrollment information. The study identified substance use and clinical comorbidities using claims from July through December 2020 and evaluated utilization and costs in 2021. Generalized linear models (GLM) estimated outcomes using single equation and two-part modeling. A gamma distribution and log link were used to model expenditures, and negative binomial models were used to model utilization. A falsification test comparing behavioral health telemedicine utilization, which had no cost sharing in either group, assessed whether differences in the groups may be responsible for observed findings. RESULTS: Substance use enrollees with copayments were less likely to have a substance use or behavioral health outpatient (-0.04 PP adjusted; p = 0.001) or inpatient visit (-0.04 PP; p = 0.001) relative to their counterparts without copayments, equal to a 17 % reduction in substance use or behavioral health outpatient services and a nearly 50 % reduction in inpatient visits. The reduced utilization among enrollees with a copayment was associated with a significant reduction in total expenses ($954; p = 0.001) and expenses related to substance use or behavioral health services ($532; p = 0.001). For enrollees with at least one behavioral health visit, there were no differences in outpatient or inpatient utilization or expenditures between enrollees with and without copayments. Copayments had no association with non-behavioral health or telemedicine services where neither group had cost sharing. CONCLUSION: Copayments serve as an initial barrier to substance use treatment, but are not associated with the amount of healthcare utilization conditional on using services. Policy makers and insurers should consider the role of copayments for treatment services among enrollees with substance use disorders in Medicaid programs.

Predicting pediatric severe asthma exacerbations: an administrative claims-based predictive model.

OBJECTIVE: Previous machine learning approaches fail to consider race and ethnicity and social determinants of health (SDOH) to predict childhood asthma exacerbations. A predictive model for asthma exacerbations in children is developed to explore the importance of race and ethnicity, rural-urban commuting area (RUCA) codes, the Child Opportunity Index (COI), and other ICD-10 SDOH in predicting asthma outcomes. METHODS: Insurance and coverage claims data from the Arkansas All-Payer Claims Database were used to capture risk factors. We identified a cohort of 22,631 children with asthma aged 5-18 years with 2 years of continuous Medicaid enrollment and at least one asthma diagnosis in 2018. The goal was to predict asthma-related hospitalizations and asthma-related emergency department (ED) visits in 2019. The analytic sample was 59% age 5-11 years, 39% White, 33% Black, and 6% Hispanic. Conditional random forest models were used to train the model. RESULTS: The model yielded an area under the curve (AUC) of 72%, sensitivity of 55% and specificity of 78% in the OOB samples and AUC of 73%, sensitivity of 58% and specificity of 77% in the training samples. Consistent with previous literature, asthma-related hospitalization or ED visits in the previous year (2018) were the two most important variables in predicting hospital or ED use in the following year (2019), followed by the total number of reliever and controller medications. CONCLUSIONS: Predictive models for asthma-related exacerbation achieved moderate accuracy, but race and ethnicity, ICD-10 SDOH, RUCA codes, and COI measures were not important in improving model accuracy.

Economic Report of General Inpatient Hospice in an Academic Medical Center.

This study examined if there was difference in cost of care after implementation of scattered bed inpatient hospice, first implemented in October 2021 in an Academic Medical Center in Arkansas. This retrospective, cross-sectional study compared the cost of care during the pre-implementation phase (n = 121, July 2020-March 2021) to patients admitted to hospice care (n = 84, October 2021-June 2022). Hospice length of stay (LOS) was 4 times longer than the LOS after a Do Not Resuscitate order (DNR) was placed for patients in the pre-implementation period. The end of life costs after the implementation of inpatient hospice was 69% less than the end of life costs in the pre-implementation period.

Asthma Quality Measurement and Adverse Outcomes in Medicaid-Enrolled Children.

OBJECTIVES: To determine the association between the asthma medication ratio (AMR) quality measure and adverse outcomes among Medicaid-enrolled children with asthma in Arkansas, given concerns regarding the utility of the AMR in evaluating pediatric risk of asthma-related adverse events (AAEs). METHODS: We used the Arkansas All-Payer Claims Database to identify Medicaid-enrolled children with asthma using a nonrestrictive case definition and additionally using the standard Healthcare Effectiveness Data and Information Set (HEDIS) persistent asthma definition. We assessed the AMR using the traditional dichotomous HEDIS AMR categorization and across 4 expanded AMR categories. Regression models assessed associations between AMR and AAE including hospitalization and emergency department utilization, with models conducted overall and by race and ethnicity. RESULTS: Of the 22 788 children in the analysis, 9.0% had an AAE (6.7% asthma-related emergency department visits; 3.0% asthma-related hospitalizations). We found poor correlation between AMR and AAE, with higher rates of AAE (10.5%) among children with AMR ≥0.5 compared with AMR <0.5 (8.5%; P < .001), and similar patterns stratified by racial and ethnic subgroups. Expanded AMR categorization revealed notable differences in associations between AMR and AAEs, compared with traditional dichotomous categorization, with worse performance in Black children. CONCLUSIONS: The AMR performed poorly in identifying risk of adverse outcomes among Medicaid-enrolled children with asthma. These findings underscore concerns of the utility of the AMR in population health management and reliance on restrictive HEDIS definitions. New population health frameworks incorporating broader considerations that accurately identify at-risk children are needed to improve equity in asthma management and outcomes.

Cost-benefit analysis of home visiting to reduce infant mortality among preterm infants.

PURPOSE: The Following Baby Back Home (FBBH) visiting program, which is provided by nurse and social worker teams, supports families of low-birthweight preterm infants after discharge from a neonatal intensive care unit. Enrollment in the FBBH program has been documented to reduce the likelihood of infant death. In this study, we conducted a cost-benefit analysis of the FBBH program. DESIGN AND METHODS: Infants enrolled in the FBBH program (N = 416) were identified through administrative records. Infants in the FBBH program were propensity score matched with comparison infants to estimate the difference in healthcare costs in the first year of life. RESULTS: Infants enrolled in the FBBH program incurred similar medical care costs compared to a comparison group. Avoided deaths, program costs, healthcare costs resulted in net economic benefits of the FBBH program to avoid infant death estimate at $83,020, cost per life saved at $3080, and benefit-to-cost ratio at 27.95. CONCLUSIONS: The FBBH program's net economic benefits from avoided deaths suggest a substantial return on investment of resources, yielding benefits in excess of program and healthcare costs. PRACTICE IMPLICATIONS: It is economically beneficial to provide home visiting services to families of low-birthweight babies by a team comprised of a registered nurse and social worker.

Rates Of Preterm Birth And Low Birthweight: An Analysis Of Racial And Ethnic Populations.

Using National Center for Health Statistics data (2016-20), we evaluated variation in low birthweight and prematurity among racial and ethnic subcategories. Disparities as large as 2.3-fold among rates of low birthweight for "multiple race" subcategories underscore the need for granular data stratification and analysis by racial and ethnic subcategories to address the root causes of inequities in infant outcomes.

Using artificial intelligence to optimize delivery of weight loss treatment: Protocol for an efficacy and cost-effectiveness trial.

Gold standard behavioral weight loss (BWL) is limited by the availability of expert clinicians and high cost of delivery. The artificial intelligence (AI) technique of reinforcement learning (RL) is an optimization solution that tracks outcomes associated with specific actions and, over time, learns which actions yield a desired outcome. RL is increasingly utilized to optimize medical treatments (e.g., chemotherapy dosages), and has very recently started to be utilized by behavioral treatments. For example, we previously demonstrated that RL successfully optimized BWL by dynamically choosing between treatments of varying cost/intensity each week for each participant based on automatic monitoring of digital data (e.g., weight change). In that preliminary work, participants randomized to the AI condition required one-third the amount of coaching contact as those randomized to the gold standard condition but had nearly identical weight losses. The current protocol extends our pilot work and will be the first full-scale randomized controlled trial of a RL system for weight control. The primary aim is to evaluate the hypothesis that a RL-based 12-month BWL program will produce non-inferior weight losses to standard BWL treatment, but at lower costs. Secondary aims include testing mechanistic targets (calorie intake, physical activity) and predictors (depression, binge eating). As such, adults with overweight/obesity (N = 336) will be randomized to either a gold standard condition (12 months of weekly BWL groups) or AI-optimized weekly interventions that represent a combination of expert-led group, expert-led call, paraprofessional-led call, and automated message). Participants will be assessed at 0, 1, 6 and 12 months.

Identification of racial/ethnic disparities associated with severe maternal morbidity using the Arkansas All-Payer Claims Database (2013-2017).

OBJECTIVE: To evaluate the effect of maternal characteristics on the odds of severe maternal morbidity (SMM) through 42 days postpartum. STUDY DESIGN: We conducted a retrospective observational study of 77 172 births using birth certificate and insurance claims data from the Arkansas All Payers Claims Database, years 2013-2017, to identify racial disparities associated with SMM for births between April 1, 2014, and November 19, 2017. METHODS: Multiple logistic regression was used to examine the effect of sociodemographic factors and clinical comorbidities on the odds of SMM among non-Hispanic white ("white"), non-Hispanic Black ("Black"), and Hispanic women. RESULTS: The rate of SMM was 227.41 per 10 000 births, with Black women (330 per 10 000 births; 95% CI: 296.16-366.38), having a significantly higher rates than white women (197; 95% CI: 171.72-225.84) and Hispanic women (180; 95% CI: 155.86-207.54). After adjusting for maternal demographics, birth-related clinical variables, and comorbidities, SMM remained higher among Black women (aOR 1.37; 95% CI 1.11-1.70) relative to white women. CONCLUSIONS: Comorbidities, socioeconomic factors, and other factors did not fully explain the Black-white disparities in SMM. Persistent disparities in the rates of SMM throughout 42 days postpartum among Black women relative to white women points to the need for higher quality, more equitable care for women of color in the fist months postpartum.

Variation in Time Between Testing Positive for COVID-19 and Hospital Admission by Race/Ethnicity and Insurance Status.

Understanding the extent to which demographic and socioeconomic factors play a role in the disparities associated with duration between testing positive for COVID-19 and hospital admission will help in achieving equitable health outcomes. This project linked the statewide COVID-19 registry to administrative datasets to examine the variation in times between testing positive for COVID-19 and hospital admission by race/ethnicity and insurance. In 2020, there were 11,314 patients admitted for COVID-19 in Arkansas. Approximately 42.2% tested positive for COVID-19 on the same day as hospital admission. Black patients had 38% higher odds of hospitalization on the day of testing compared with White patients (p<.001). Medicaid and uninsured patients had 51% and 50% higher odds of admission on the day of testing compared with privately insured patients (both p<.001), respectively. This study highlights the implications of reduced access to testing with respect to equitable health outcomes.

Geographic variation in Medicare home health expenditures.

OBJECTIVES: To quantify geographic variation in home health expenditures per Medicare home health beneficiary and investigate factors associated with this variation. STUDY DESIGN: Retrospective study design analyzing US counties in which at least 1 home health agency served 11 or more beneficiaries in 2016. Several sources of 2016 national public data were used. METHODS: The key variable is county-level Medicare home health expenditures per home health beneficiary. Counties were grouped into quintiles based on per-beneficiary expenditures. Analyses included calculation of coefficients of variation, computation of the ratio of 90th percentile to 10th percentile in expenditures, and linear regression predicting expenditure. The control variables included characteristics of patients, agencies, and communities. RESULTS: Significant variation in home health expenditures was identified across county quintiles, with a 90th-to-10th-percentile expenditure ratio of 2.5. The percentage of for-profit agencies in the lowest quintile was 15.7 compared with 81.7 in the highest quintile of spending. Unadjusted spending differed by $3864 (95% CI, $3793-$3936), compared with $3611 (95% CI, $3514-$3708) in the adjusted model, between counties in spending quintiles 1 and 5. Although state fixed effects explained nearly 20% of the variation in home health expenditures, 42% of the variation remained unexplained. CONCLUSIONS: Home health care exhibits considerable unwarranted variation in per-patient expenditures across counties, signifying inefficiency and waste. Given the expected growth in home health demand, strategies to reduce unwarranted geographic variation are needed.

Healthcare costs and resource utilization associated with renal cell carcinoma among older Americans: A longitudinal case-control study using the SEER-Medicare data.

OBJECTIVES: To determine 1-year and 5-year total healthcare costs and healthcare resource (HRU) associated with renal cell carcinoma (RCC) in older Americans, from a healthcare sector perspective. MATERIALS AND METHODS: This was a longitudinal, retrospective cohort study using the Surveillance, Epidemiology and End Results-Medicare linked data (2006-2014), which included older (≥66 years) patients with primary RCC and 1:5 matched noncancer controls. Patients/controls were followed from diagnosis (pseudo-diagnosis for controls) until death or up to loss-to-follow-up (censored). Per-patient average 1-year and 5-year cumulative total and incremental total healthcare costs and HRU were reported. RESULTS: A total of 11,228 RCC patients were matched to 56,140 controls. Per-patient cumulative average 1-year (incremental = $38,291 [$36,417-$40,165]; $57,588 vs. $19,297) and 5-year (incremental = $68,004 [$55,123-$80,885]; $183,550 vs. $115,547) total costs (excluding prescription drug costs) were 3 and 1.6 times higher for RCC vs. controls. These estimates were 3.6 and 1.7 times higher for RCC vs. controls when prescription costs were included in total costs. Prescription drug costs accounted for 8.4% (incremental = $3,715) and 18.1% (incremental = $15,375) of the 1-year and 5-year incremental total costs, respectively. RCC patients had greater cumulative number of hospitalizations, emergency department visits and prescriptions in 1- and 5-years, compared to controls. CONCLUSIONS: Average first year total cost for a patient with incident diagnosis of RCC is substantially higher than that for controls and it varies depending on the stage at diagnosis. Study findings could help in planning future resource allocation and in determining research and unmet needs in this patient population.

Understanding racial disparities in severe maternal morbidity using Bayesian network analysis.

Previous studies have evaluated the marginal effect of various factors on the risk of severe maternal morbidity (SMM) using regression approaches. We add to this literature by utilizing a Bayesian network (BN) approach to understand the joint effects of clinical, demographic, and area-level factors. We conducted a retrospective observational study using linked birth certificate and insurance claims data from the Arkansas All-Payer Claims Database (APCD), for the years 2013 through 2017. We used various learning algorithms and measures of arc strength to choose the most robust network structure. We then performed various conditional probabilistic queries using Monte Carlo simulation to understand disparities in SMM. We found that anemia and hypertensive disorder of pregnancy may be important clinical comorbidities to target in order to reduce SMM overall as well as racial disparities in SMM.

Association of Health-Related Quality of Life with Overall Survival in Older Americans with Kidney Cancer: A Population-Based Cohort Study.

BACKGROUND: Our purpose was to evaluate associations between health-related quality of life (HRQoL) and overall survival (OS) in a population-based sample of kidney cancer (KC) patients in the US. METHODS: We analyzed a longitudinal cohort (n = 188) using the Surveillance, Epidemiology, and End Results (SEER) database linked with the Medicare Health Outcomes Survey (MHOS; 1998-2014). We included KC patients aged ≥65 years, with a completed MHOS during baseline (pre-diagnosis) and another during follow-up (post-diagnosis). We reported HRQoL as physical component summary (PCS) and mental component summary (MCS) scores and OS as number of months from diagnosis to death/end-of-follow-up. Findings were reported as adjusted hazard ratios (aHRs (95% CI)) from Cox Proportional Hazard models. RESULTS: The aHRs associated with a 3-point lower average (baseline and follow-up) or a 3-point within-patient decline (change) in HRQoL with OS were: (a) baseline: PCS (1.08 (1.01-1.16)) and MCS (1.09 (1.01-1.18)); (b) follow-up: PCS (1.21 (1.12-1.31)) and MCS (1.11 (1.04-1.19)); and (c) change: PCS (1.10 (1.02-1.18)) and MCS (1.02 (0.95-1.10)). CONCLUSIONS: Reduced HRQoL was associated with worse OS and this association was strongest for post-diagnosis PCS, followed by change in PCS and pre-diagnosis PCS. Findings highlight the prognostic value of HRQoL on OS, emphasize the importance of monitoring PCS in evaluating KC prognosis, and contribute additional evidence to support the implementation of patient-reported outcomes in clinical settings.

Association of the COVID-19 pandemic and dying at home due to ischemic heart disease.

The coronavirus disease 2019 (COVID-19) pandemic has been associated with a declining volume of patients seen in the emergency department. Despite the need for seeking urgent care for conditions such as myocardial infarction, many people may not seek treatment. This study seeks to measure associations between the COVID-19 pandemic and location of death among individuals who died from ischemic heart disease (IHD). Data obtained from death certificates from the Arkansas Department of Health was used to conduct a difference-in-difference analysis to assess whether decedents of IHD were more likely to die at home during the pandemic (March 2020 through September 2020). The analysis compared location of death for decedents of IHD pre and during the pandemic to location of death for decedents from non-natural causes. Before the pandemic, 50.0% of decedents of IHD died at home compared to 57.9% dying at home during (through September 2020) the pandemic study period (p < .001). There was no difference in the proportion of decedents who died at home from non-natural causes before and during the pandemic study period (55.8% vs. 53.5%; p = .21). After controlling for confounders, there was a 48% increase in the odds of dying at home from IHD during the pandemic study period (p < .001) relative to the change in dying at home due to non-natural causes. During the study period, there was an increase in the proportion of decedents who died at home due to IHD. Despite the ongoing pandemic, practitioners should emphasize the need to seek urgent care during an emergency.

Labor market participation and productivity costs for female caregivers of minor male children with Duchenne and Becker muscular dystrophies.

INTRODUCTION/AIMS: Duchenne and Becker muscular dystrophies (DBMD) are X-linked neuromuscular disorders characterized by progressive muscle weakness, leading to decreased mobility and multisystem complications. We estimate productivity costs attributable to time spent by a parent caring for a male child under the age of 18 y with DBMD, with particular focus on female caregivers of boys with Duchenne muscular dystrophy (DMD) who have already lost ambulation. METHODS: Primary caregivers of males with DBMD in the Muscular Dystrophy Surveillance and Research Tracking Network (MD STARnet) were surveyed during 2011-2012 on family quality of life measures, including labor market outcomes. Of 211 respondents, 96 female caregivers of boys with DBMD were matched on state, year of survey, respondent's age, child's age, and number of minor children with controls constructed from Current Population Survey extracts. Regression analysis was used to estimate labor market outcomes and productivity costs. RESULTS: Caregivers of boys with DBMD worked 296 h less per year on average than caregivers of unaffected children, translating to a $8816 earnings loss in 2020 U.S. dollars. Caregivers of boys with DMD with ≥4 y of ambulation loss had a predicted loss in annualized earnings of $23,995, whereas caregivers of boys with DBMD of the same ages who remained ambulatory had no loss of earnings. DISCUSSION: Female caregivers of non-ambulatory boys with DMD face additional household budget constraints through income loss. Failure to include informal care costs in economic studies could understate the societal cost-effectiveness of strategies for managing DMD that might prolong ambulation.

Risk-based contracting for high-need Medicaid beneficiaries: The Arkansas PASSE program.

The high cost of health care for people with behavioral health (BH) conditions or intellectual and developmental disabilities (IDD) in the United States led one state to implement the Provider-led Arkansas Shared Savings Entity (PASSE) program. PASSE is a managed care model that puts provider-led organizations at risk for the highest need people with BH conditions or IDD in Medicaid, a public health insurance program for low-income residents. Drawing on key informant interviews and payment models across the United States, we describe the PASSE program, how it compares with state Medicaid programs for similar populations, and prospects for the program. Key informants cited several PASSE features as promising mechanisms to improve beneficiary outcomes: expanded care coordination, service flexibility, incentives for community investments, accountability for cost and quality across physical health, behavioral health, and long-term care, quality target accountability, fostered competition, and provider ownership. Informants worry that PASSE features will be insufficient to catalyze changes in provider behavior. Efforts may be targeted to control costs primarily through service reductions with uncertain effects on quality of care. PASSE hinges on improved care coordination and increased efforts to address social determinants of health. Success or failure in these areas will likely determine whether PASSE leads to improved outcomes for two of the most costly and vulnerable populations.

Financial Performance of Hospitals in the Appalachian Region Under the Hospital Readmissions Reduction Program and Hospital Value-Based Purchasing Program.

PURPOSE: The Hospital Readmission and Reduction Program (HRRP) and Hospital Value-Based Purchasing Program (HVBP) propose to improve quality of patient care by either rewarding or penalizing hospitals through inpatient reimbursement. This study analyzes the effect of both programs on profitability of hospitals located in the Appalachian Region (AR) compared to hospitals in Appalachian states and the rest of the United States. METHODS: This study used a retrospective research design with a longitudinal unbalanced panel dataset from 2008 to 2015. Hospitals participating in both HRRP and HVBP during this time frame were included in the study. A difference-in-difference model with hospital-level fixed effects, controlling for hospital and market characteristics, was used to determine effects of both programs on profitability of hospitals serving the AR, Appalachian states, and the rest of the United States. FINDINGS: After implementation of HRRP and HVBP, only hospitals located in Appalachian states experienced a significant decrease in operating margin (-1.14 percentage points). Unexpectedly, during the same time period, total margin increased significantly for hospitals located in the AR (1.05 percentage points), Appalachian states (1.71 percentage points), and the rest of the United States (2.38 percentage points). CONCLUSIONS: HRRP and HVBP financially incentivize hospitals to focus efforts on improving patient care. The programs may not have the anticipated results. Increases in total margin for all hospitals during the study period indicate access to nonpatient revenues, offsetting the financial penalties from both programs. This revenue source may undermine the program's objectives of delivering value and achieving quality outcomes.