Reducing Hospital Readmissions: Addressing the Impact of Food Security and Nutrition

Diet and Food and Nutrition Insecurity and Cardiometabolic Disease

Poor nutrition is the leading cause of poor health, health care spending, and lost productivity in the United States and globally, which acts through cardiometabolic diseases as precursors to cardiovascular disease, cancer, and other conditions. There is great interest in how the social determinants of health (the conditions in which people are born, live, work, develop, and age) impact cardiometabolic disease. Food insecurity is an example of a powerful social determinant of health that impacts health outcomes. Nutrition insecurity, a distinct but related concept to food insecurity, is a direct determinant of health. In this article, we provide an overview of how diet in early life relates to cardiometabolic disease and then continue to focus on the concepts of food insecurity and nutrition insecurity. In the discussions herein we make important distinctions between the concepts of food insecurity and nutrition insecurity and provide a review of their concepts, histories, measurement and assessment devices, trends and prevalence, and links to health and health disparities. The discussions here set the stage for future research and practice to directly address the negative consequences of food and nutrition insecurity.

Importance of Nutrition Security to CVD Prevention Efforts in the USA

PURPOSE OF REVIEW

The importance of addressing nutrition security for the primary and secondary prevention of cardiovascular disease (CVD) in the USA is reviewed by describing the relationships between food security, diet quality, and CVD risk along with the ability of governmental, community, and healthcare policies and interventions to address nutrition security.

RECENT FINDINGS

Existing safety net programs have shown to be effective at improving food security and diet quality and reducing risk for CVD, but continued efforts to increase reach and improve standards are needed. Adoption of policies, healthcare initiatives, and community- and individual-level interventions addressing the nutritional intake of socioeconomically disadvantaged populations may also lessen CVD burden, but scaling interventions remains a key challenge. Research suggests simultaneously addressing food security and diet quality is feasible and could help reduce socioeconomic disparities in CVD morbidity and mortality. Intervening at multiple levels among high-risk groups should be a priority.

Association of Medicaid Expansion With Quality in Safety-Net Hospitals

IMPORTANCE

Safety-net hospitals (SNHs) operate under limited financial resources and have had challenges providing high-quality care. Medicaid expansion under the Affordable Care Act led to improvements in hospital finances, but whether this was associated with better hospital quality, particularly among SNHs given their baseline financial constraints, remains unknown.

OBJECTIVE

To compare changes in quality from 2012 to 2018 between SNHs in states that expanded Medicaid vs those in states that did not.

DESIGN, SETTING, AND PARTICIPANTS

Using a difference-in-differences analysis in a cohort study, performance on quality measures was compared between SNHs, defined as those in the highest quartile of uncompensated care in the pre-Medicaid expansion period, in expansion vs nonexpansion states, before and after the implementation of Medicaid expansion. A total of 811 SNHs were included in the analysis, with 316 in nonexpansion states and 495 in expansion states. The study was conducted from January to November 2020.

EXPOSURES

Time-varying indicators for Medicaid expansion status.

MAIN OUTCOMES AND MEASURES

The primary outcome was hospital quality measured by patient-reported experience (Hospital Consumer Assessment of Healthcare Providers and Systems Survey), health care-associated infections (central line-associated bloodstream infections, catheter-associated urinary tract infections, and surgical site infections following colon surgery) and patient outcomes (30-day mortality and readmission rates for acute myocardial infarction, heart failure, and pneumonia). Secondary outcomes included hospital financial measures (uncompensated care and operating margins), adoption of electronic health records, provision of safety-net services (enabling, linguistic/translation, and transportation services), or safety-net service lines (trauma, burn, obstetrics, neonatal intensive, and psychiatric care).

RESULTS

In this difference-in-differences analysis of a cohort of 811 SNHs, no differential changes in patient-reported experience, health care-associated infections, readmissions, or mortality were noted, regardless of Medicaid expansion status after the Affordable Care Act. There were modest differential increases between 2012 and 2016 in the adoption of electronic health records (mean [SD]: nonexpansion states, 99.4 [7.4] vs 99.9 [3.8]; expansion states, 94.6 [22.6] vs 100.0 [2.2]; 1.7 percentage points; P = .02) and between 2012 and 2018 in the number of inpatient psychiatric beds (mean [SD]: nonexpansion states, 24.7 [36.0] vs 23.6 [39.0]; expansion states: 29.3 [42.8] vs 31.4 [44.3]; 1.4 beds; P = .02) among SNHs in expansion states, although they were not statistically significant at a threshold adjusted for multiple comparisons. In subgroup analyses comparing SNHs with higher vs lower baseline operating margins, an isolated differential improvement was noted in heart failure readmissions among SNHs with lower baseline operating margins in expansion states (mean [SD], 22.8 [2.1]; -0.53 percentage points; P = .001).

CONCLUSIONS AND RELEVANCE

This difference-in-differences cohort study found that despite reductions in uncompensated care and improvements in operating margins, there appears to be little evidence of quality improvement among SNHs in states that expanded Medicaid compared with those in states that did not.

Dual eligible patients are not the same: How social risk may impact quality measurement's ability to reduce inequities

BACKGROUND

CMS recently decided to produce private "healthcare disparities reports" that include dual eligibility (DE) as the sole stratifying variable used to assess pneumonia readmission disparities.

RESEARCH DESIGN

We measure the relationship between DE status and readmissions, both with and without conceptually relevant social risk factors, including air pollution, severe housing problems, and food insecurity, using data from county- and hospital-level readmission rates, DE status, and social risk factors.

RESULTS

At the county level, the relationship between DE status and readmissions is partially confounded by at least three social risk factors. DE populations vary widely across hospitals, creating unequal between-hospital comparisons.

CONCLUSIONS

Because of differences in the DE population, between-hospital comparisons could be misleading using a methodology that stratifies by DE only. We suggest viable alternatives to sole-factor stratification to properly account for social risk factors and better isolate quality differences that might yield readmission rate inequities.

IMPLICATIONS

CMS's healthcare disparities reports provided to hospitals are limited by relying exclusively on DE proportion as the measure of social risk, undercutting the power of quality measurement and its related incentives to close or minimize healthcare inequities.

Clinical and Sociobehavioral Prediction Model of 30-Day Hospital Readmissions Among People With HIV and Substance Use Disorder: Beyond Electronic Health Record Data

BACKGROUND

Under the Affordable Care Act, hospitals receive reduced reimbursements for excessive 30-day readmissions. However, the Centers for Medicare and Medicaid Services does not consider social and behavioral variables in expected readmission rate calculations, which may unfairly penalize systems caring for socially disadvantaged patients, including patients with HIV.

SETTING

Randomized controlled trial of patient navigation with or without financial incentives in HIV-positive substance users recruited from the inpatient setting at 11 US hospitals.

METHODS

External validation of an existing 30-day readmission prediction model, using variables available in the electronic health record (EHR-only model), in a new multicenter cohort of HIV-positive substance users was assessed by C-statistic and Hosmer-Lemeshow testing. A second model evaluated sociobehavioral factors in improving the prediction model (EHR-plus model) using multivariable regression and C-statistic with cross-validation.

RESULTS

The mean age of the cohort was 44.1 years, and participants were predominantly males (67.4%), non-white (88.0%), and poor (62.8%, <$20,000/year). Overall, 17.5% individuals had a hospital readmission within 30 days of initial hospital discharge. The EHR-only model resulted in a C-statistic of 0.65 (95% confidence interval: 0.60 to 0.70). Inclusion of additional sociobehavioral variables, food insecurity and readiness for substance use treatment, in the EHR-plus model resulted in a C-statistic of 0.74 (0.71 after cross-validation, 95% confidence interval: 0.64 to 0.77).

CONCLUSIONS

Incorporation of detailed social and behavioral variables substantially improved the performance of a 30-day readmission prediction model for hospitalized HIV-positive substance users. Our findings highlight the importance of social determinants in readmission risk and the need to ask about, adjust for, and address them.

Addressing Food Insecurity and Overweight/Obesity in Hospitalized Low-Income Latino Patients

Food insecurity (FI), the limited or unreliable availability of safe and nutritious food, is a pressing public health concern affecting millions of U.S. citizens. Unfortunately, FI tends to impact those who are most vulnerable (e.g., low-income minorities) and potentially increases obesity risks, diet-sensitive disease risks (e.g., hypertension and type 2 diabetes), and hospital utilization. Low-income Latino patients may be particularly sensitive to adverse outcomes based on unaddressed socioeconomic needs. Nurses are in a prime position to assess and address FI in these patients. Our article will discuss how nurses can be advocates in combating FI in Latino patients with overweight/obesity.