Background: The inclusion of Z-codes for social determinants of health (SDOH) in the 10th revision of the International Classification of Diseases (ICD-10) may offer an opportunity to improve data collection of SDOH, but no characterization of their utilization exists on a national all-payer level. Objective: To examine the prevalence of SDOH Z-codes and compare characteristics of patients with and without Z-codes and hospitals that do and do not use Z-codes. Research Design: Retrospective cohort study using 2016 and 2017 National Inpatient Sample. Participants: Total of 14,289,644 inpatient hospitalizations. Measures: Prevalence of SDOH Z-codes (codes Z55–Z65) and descriptive statistics of patients and hospitals. Results: Of admissions, 269,929 (1.9%) included SDOH Z-codes. Average monthly SDOH Z-code use increased across the study period by 0.01% per month (P<0.001). The cumulative number and proportion of hospitals that had ever used an SDOH Z-code also increased, from 1895 hospitals (41%) in January 2016 to 3210 hospitals (70%) in December 2017. Hospitals that coded at least 1 SDOH Z-code were larger, private not-for-profit, and urban teaching hospitals. Compared with admissions without an SDOH Z-code, admissions with them were for patients who were younger, more often male, Medicaid recipients or uninsured. A higher proportion of admissions with SDOH Z-codes were for mental health (44.0% vs. 3.3%, P<0.001) and alcohol and substance use disorders (9.6% vs. 1.1%, P<0.001) compared with those without. Conclusions: The uptake of SDOH Z-codes has been slow, and current coding is likely poorly reflective of the actual burden of social needs experienced by hospitalized patients.

Background and Purpose: The rural-urban life-expectancy gap is widening, but underlying causes are incompletely understood. Prior studies suggest stroke care may be worse for individuals in more rural areas, and technological advancements in stroke care may disproportionately impact individuals in more rural areas. We sought to examine differences and 5-year trends in the care and outcomes of patients hospitalized for stroke across rural-urban strata. Methods: Retrospective cohort study using National Inpatient Sample data from 2012 to 2017. Rurality was classified by county of residence according to the 6-strata National Center for Health Statistics classification scheme. Results: There were 792 054 hospitalizations for acute stroke in our sample. Rural patients were more often white (78% versus 49%), older than 75 (44% versus 40%), and in the lowest quartile of income (59% versus 32%) compared with urban patients. Among patients with acute ischemic stroke, intravenous thrombolysis and endovascular therapy use were lower for rural compared with urban patients (intravenous thrombolysis: 4.2% versus 9.2%, adjusted odds ratio, 0.55 [95% CI, 0.51–0.59], P <0.001; endovascular therapy: 1.63% versus 2.41%, adjusted odds ratio, 0.64 [0.57–0.73], P <0.001). Urban-rural gaps in both therapies persisted from 2012 to 2017. Overall, stroke mortality was higher in rural than urban areas (6.87% versus 5.82%, P <0.001). Adjusted in-patient mortality rates increased across categories of increasing rurality (suburban, 0.97 [0.94–1.0], P =0.086; large towns, 1.05 [1.01–1.09], P =0.009; small towns, 1.10 [1.06–1.15], P <0.001; micropolitan rural, 1.16 [1.11–1.21], P <0.001; and remote rural 1.21 [1.15–1.27], P <0.001 compared with urban patients. Mortality for rural patients compared with urban patients did not improve from 2012 (adjusted odds ratio, 1.12 [1.00–1.26], P <0.001) to 2017 (adjusted odds ratio, 1.27 [1.13–1.42], P <0.001). Conclusions: Rural patients with stroke were less likely to receive intravenous thrombolysis or endovascular therapy and had higher in-hospital mortality than their urban counterparts. These gaps did not improve over time. Enhancing access to evidence-based stroke care may be a target for reducing rural-urban disparities.

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Background: Left ventricular assist device (LVAD) therapy is an increasingly viable alternative for patients who are not candidates for heart transplantation or who are waiting for a suitable donor. We aimed to determine whether there is an association between sex, race/ethnicity, insurance coverage, and neighborhood income and access to/outcomes of LVAD implantation. We further analyzed whether access to LVAD improved in states that did versus did not expand Medicaid. Methods and Results: Retrospective cohort study using State Inpatient Databases to identify patients 18 to 85 years of age admitted for heart failure, cardiogenic shock, or LVAD implantation from 2012 to 2015. Logistic regression analyses adjusting for age, all the sociodemographic factors above, medical comorbidities, and a hospital random effect were used to quantify odds of receipt of LVADs, as well as outcomes conditional on receiving an LVAD, for the sociodemographic groups of interest. A total of 925 770 patients were included; 3972 (0.43%) received LVADs. After adjusting for age, comorbidities, and hospital effects, women (adjusted odds ratio [aOR], 0.45 [0.41–0.49]), black patients (aOR, 0.83 [0.74–0.92]), and Hispanic patients (aOR, 0.74 [0.64–0.87]) were less likely to receive LVADs than whites. Medicare (aOR, 0.79 [0.72–0.86]), Medicaid (aOR, 0.52 [0.46–0.58]), and uninsured patients (aOR, 0.17 [0.11–0.25]) were less likely to receive LVADs than the privately insured, and patients in low-income ZIP codes were less likely than those in higher income areas (aOR, 0.71 [0.65–0.77]). Among those who received LVADs, women (aOR, 1.78 [1.38–2.30]), patients of unknown race or race other than white, black, or Hispanic (aOR, 1.97 [1.42–2.74]), and uninsured patients (aOR, 4.86 [1.92–12.28]) had higher rates of in-hospital mortality. Medicaid expansion was not associated with an increase in LVAD implantation. Conclusions: There are meaningful sociodemographic disparities in access and outcomes for LVAD implantation. Medicaid expansion was not associated with an increase in LVAD rates.

Unmet social needs—including food, housing, and utilities—have been associated with negative health outcomes, but most prior research has examined the health associations with a single unmet need or analyzed samples that were homogeneous along one or more dimensions (e.g., older adults or patients with chronic health conditions). We examined the association between unmet social needs and psychosocial and health-related outcomes in a sample of Medicaid beneficiaries from 35 U.S. states. In 2016-2017, 1,214 people completed an online survey about social needs, demographics, and health-related and psychosocial outcomes. Seven items assessing social needs formed an index in which higher scores indicated higher levels of unmet needs. Participants were eligible if they were ≥18 years and had Medicaid. The sample was predominantly female (87%). Most (71%) lived with at least one child ≤18 years, and 49% were White and 33% were African American. Average age was 36 years (SD = 13). The most common unmet needs were not enough money for unexpected expenses (54%) and not enough space in the home (25%). Analyses controlling for recruitment method and demographics showed that increasing levels of unmet social needs were positively associated with stress, smoking, and number of chronic conditions, and negatively associated with future orientation, attitudes toward prevention, days of exercise/week, servings of fruits or vegetables/day, and self-rated health (all p < .01). Results add to the evidence about the relationship between unmet social needs and health. Interventions to help meet social needs may help low-income people improve both their economic situations and their health.

IMPORTANCE Surgical site infection (SSI) is an important patient safety outcome. Although social risk factors have been linked to many adverse health outcomes, it is unknown whether such factors are associated with higher rates of SSI. OBJECTIVES To determine whether social risk factors, including race/ethnicity, insurance status, and neighborhood income, are associated with higher rates of SSI after colectomy or abdominal hysterectomy, 2 surgical procedures for which SSI rates are publicly reported and included in pay-forperformance programs by Medicare and other groups.

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BACKGROUND/OBJECTIVES Launched in October 2018, Medicareʼs Skilled Nursing Facility Value‐Based Purchasing (SNF VBP) program mandates financial penalties for SNFs with high 30‐day readmission rates. Our objective was to identify characteristics of SNFs associated with provider performance under the program. DESIGN Retrospective cross‐sectional analysis using Nursing Home Compare data for the 2019 SNF VBP. Facility‐level regressions examined the relationship between structural characteristics (nursing home size, rurality, profit status, hospital affiliation, region, and Star Ratings) and patient characteristics (neighborhood income, race/ethnicity, dual eligibility, disability, and frailty) and facility performance. SETTING US Medicare. PARTICIPANTS A total of 14 558 SNFs. MEASUREMENTS The 2019 SNF VBP performance scores and penalties. RESULTS Nationally, 72% (10 436) of SNFs were penalized; 21% (2996) received the maximum penalty of 1.98%. In multivariate analyses, rural SNFs were less likely to be penalized (odds ratio [OR] = 0.85; 95% confidence interval [CI] = 0.78‐0.92; P < .001; vs urban), while small SNFs were more likely to be penalized (≤70 beds: OR = 1.28; 95% CI = 1.15‐1.42; P < .001; 71‐120 beds: OR = 1.15; 95% CI = 1.05‐1.26; P = .003; vs >120 beds). SNFs with lower nurse staffing had higher odds of penalties (low: OR = 1.15; 95% CI = 1.03‐1.27; P = .010; vs high); nonprofit and government‐owned SNFs had lower odds of penalties (OR = 0.79; 95% CI = 0.72‐0.87; P < .001; government: OR = 0.72; 95% CI = 0.61‐0.84; P < .001; vs for profit); and SNFs with higher Star Ratings had lower odds of penalties (5 stars: OR = 0.47; 95% CI = 0.40‐0.54; P < .001; vs 1 star). In terms of patient population, SNFs located in low‐income ZIP codes (OR = 1.17; 95% CI = 1.03‐1.34; P = .019) or serving a high proportion of frail patients (OR = 1.39; 95% CI = 1.21‐1.60; P < .001) were more likely to be penalized than other SNFs. SNFs with high proportions of dual, black, Hispanic, or disabled patients did not have higher odds of penalization. CONCLUSION Structural and patient characteristics of SNFs may significantly impact provider performance under the SNF VBP. These findings have implications for policy makers and clinical leaders seeking to improve quality and avoid unintended consequences with VBP in SNFs. J Am Geriatr Soc 68:826–834, 2020