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Monitoring and improving rural health is challenging because of varied and conflicting concepts of just what rural means. Federal, state, and local agencies and data resources use different definitions, which may lead to confusion and inequity in the distribution of resources depending on the definition used. This article highlights how inconsistent definitions of rural may lead to measurement bias in research, the interpretation of research outcomes, and differential eligibility for rural-focused grants and other funding. We conclude by making specific recommendations on how policy makers and researchers could use these definitions more appropriately, along with definitions we propose, to better serve rural residents. We also describe concepts that may improve the definition of and frame the concept of rurality.

From January 2005 through December 2015, 105 rural hospitals closed. This study examined associations between community characteristics and rural hospital closure. Compared with other rural hospitals that were at high risk of financial distress but remained open over the same time period, closed rural hospitals had a smaller market share (p < .0001) despite being in areas with higher population density (p < .05), were located nearer to another hospital (p < .0001), and were located in markets that had a higher rate of unemployment (p < .05) and a higher percentage of Black (p < .05) and Hispanic (p < .01) residents. These results have three implications for rural health policy: rural hospital closures may disproportionately affect racial and ethnic minorities, community characteristics in combination with other factors make it likely that rural hospital closures will continue, and rural hospital closures illuminate the need for new models of reimbursement and health care delivery to meet the needs of rural communities.

There are limited population-based studies of determinants of physical therapy use for chronic low back pain (LBP) and of the types of treatments received by individuals who see a physical therapist. The purposes of this study were: (1) to identify determinants of physical therapy use for chronic LBP, (2) to describe physical therapy treatments for chronic LBP, and (3) to compare use of treatments with current best evidence on care for this condition. This study was a cross-sectional, population-based telephone survey of North Carolinians. Five hundred eighty-eight individuals with chronic LBP who had sought care in the previous year were surveyed on their health and health care use. Bivariate and multivariable analyses were conducted to identify predisposing, enabling, and need characteristics associated with physical therapy use. Descriptive analyses were conducted to determine the use of physical treatments for individuals who saw a physical therapist. Use of treatments was compared with evidence from systematic reviews. Of our sample, 29.7% had seen a physical therapist in the previous year, with a mean of 15.6 visits. In multivariable analyses, receiving workers' compensation, seeing physician specialists, and higher Medical Outcomes Study 12-Item Short-Form Health Survey questionnaire (SF-12) physical component scores were positively associated with physical therapy use. Having no health insurance was negatively associated with physical therapy use. Exercise was the most frequent treatment received (75% of sample), and traction was the least frequent treatment received (7%). Some effective treatments were underutilized, whereas some ineffective treatments were overutilized. Only one state was examined, and findings were based on patient report. Fewer than one third of individuals with chronic LBP saw a physical therapist. Health-related and non-health-related factors were associated with physical therapy use. Individuals who saw a physical therapist did not always receive evidence-based treatments. There are potential opportunities for improving access to and quality of physical therapy for chronic LBP.

Rural hospitals differ from urban hospitals in many ways. For example, rural hospitals are more reliant on public payers and have lower operating margins. In addition, enrollment in the health insurance Marketplaces of the Affordable Care Act (ACA) has varied across rural and urban areas. This study employed a difference-in-differences approach to evaluate the average effect of Medicaid expansion in 2014 on payer mix and profitability for urban and rural hospitals, controlling for secular trends. For both types of hospitals, we found that Medicaid expansion was associated with increases in Medicaid-covered discharges. However, the increases in Medicaid revenue were greater among rural hospitals than urban hospitals, and the decrease in the proportion of costs for uncompensated care were greater among urban hospitals than rural hospitals. This preliminary analysis of the early effects of Medicaid expansion suggests that its financial impacts may be different for hospitals in urban and rural locations.

Previous research on the health effects of caring for grandchildren has had variable findings, including both positive and negative effects on the health of grandparents. The estimated effects of caregiving may be affected by selection, with the health of grandparent affecting the likelihood of undertaking caregiving. The health effects of caregiving also likely differ according to the cultural motivations for caregiving by grandparents. This paper assesses whether selection into caring for grandchildren affects the estimated effects of caregiving on the health of Taiwanese grandparents. We used four waves (1993–2003) of the Survey of Health and Living Status of the Elderly in Taiwan to estimate the effect of grandparent caregiving on self-rated health, mobility, and depression. To control for unobserved selection into caregiving, we employed time-varying instrumental variables (the number of grandchildren and marital status of adult children) in addition to person fixed effects. After adjusting for baseline differences, caregivers had better self-rated health, fewer mobility limitations, and fewer depressive symptoms compared to the non-caregivers, which suggest evidence of health improvement for grandparents. Instrumental variable analysis showed that caring for grandchildren was endogenously determined with grandparents’ mobility limitations, and grandparent caregivers benefited from a significant reduction in the number of mobility limitations. Our finding suggests that caring for grandchildren can be beneficial for the health of Taiwanese grandparents and supports our hypothesis that a culturally expected role of caregiving results in role enhancement.

Policy Points In the absence of federal policy, states adopted policies to support family caregivers, but availability and level of support varies. We describe, compare, and rank state policies to support family caregivers as aligned with National Academy of Medicine recommendations. Although the landscape of state policies supporting caregivers has improved over time, few states provide financial supports as recommended, and benefit restrictions hinder accessibility for all types of family caregivers. Implementing policies supporting family caregivers will become more critical over time, as the reliance on family caregivers as essential providers of long‐term care is only expected to grow as the population ages. Context In the United States in 2020, approximately 26 million individuals provided unpaid care to a family member or friend. On average, 60% of caregivers were employed, and they provided 20.4 hours of care per week on top of employment. Although a handful of patchwork laws exist to aid family caregivers, systematic supports, including comprehensive training, respite, and financial support, remain limited. In the absence of federal supports, states have adopted policies to provide assistance, but they vary in availability and level of support provided. Our objectives were to describe, compare, and rank state policies to support family caregivers over time. Methods We used publicly available data from the AARP Long‐Term Services and Supports State Scorecard, the National Academy for State Health Policy, and Tax Credits for Workers and Families for all 50 states and the District of Columbia (2015‐2019). Findings We found that states had increased supports to family caregivers over this five‐year period, although significant variability in adoption and implementation of policies persists. Approximately 20% of states had enacted policies that exceed the federal Family and Medical Leave Act requirements, and 18% offered paid family leave. However, most states had not improved spousal impoverishment protections for Medicaid beneficiaries. For example, from 2016 to 2019, 24% of states provided fewer or no protections, while 71% of states did not improve spousal impoverishment protections over time. Access to training for caregivers varied based on eligibility criteria (e.g., select populations and/or only co‐residing caregivers). Conclusions Overall, state approaches to support family caregivers vary by eligibility and scope of services. Substantial gaps in support of caregivers, particularly economic supports, persist. Although the landscape of state policies supporting caregivers has improved over time, few states provide financial supports as recommended by the National Academy of Medicine, and benefit restrictions hinder accessibility for all family caregivers.

ABSTRACT BACKGROUND We sought to examine the relationship between literacy and heart failure-related quality of life (HFQOL), and to explore whether literacy-related differences in knowledge, self-efficacy and/or self-care behavior explained the relationship. METHODS We recruited patients with symptomatic heart failure (HF) from four academic medical centers. Patients completed the short version of the Test of Functional Health Literacy in Adults (TOFHLA) and questions on HF-related knowledge, HF-related self-efficacy, and self-care behaviors. We assessed HFQOL with the Heart Failure Symptom Scale (HFSS) (range 0–100), with higher scores denoting better quality of life. We used bivariate (t-tests and chi-square) and multivariate linear regression analyses to estimate the associations between literacy and HF knowledge, self-efficacy, self-care behaviors, and HFQOL, controlling for demographic characteristics. Structural equation modeling was conducted to assess whether general HF knowledge, salt knowledge, self-care behaviors, and self-efficacy mediated the relationship between literacy and HFQOL. RESULTS We enrolled 605 patients with mean age of 60.7 years; 52% were male; 38% were African-American and 16% Latino; 26% had less than a high school education; and 67% had annual incomes under $25,000. Overall, 37% had low literacy (marginal or inadequate on TOFHLA). Patients with adequate literacy had higher general HF knowledge than those with low literacy (mean 6.6 vs. 5.5, adjusted difference 0.63, p < 0.01), higher self-efficacy (5.0 vs. 4.1 ,adjusted difference 0.99, p < 0.01), and higher prevalence of key self-care behaviors (p < 0.001). Those with adequate literacy had better HFQOL scores compared to those with low literacy (63.9 vs. 55.4, adjusted difference 7.20, p < 0.01), but differences in knowledge, self-efficacy, and self-care did not mediate this difference in HFQOL. CONCLUSION Low literacy was associated with worse HFQOL and lower HF-related knowledge, self-efficacy, and self-care behaviors, but differences in knowledge, self-efficacy and self-care did not explain the relationship between low literacy and worse HFQOL.

In this article, we develop and demonstrate a method for determining whether inclusion of drug costs is the right decision for providers who are considering alternative payment models. * Using claims analysis and understanding of care delivery, providers can assess the pros and cons of including drug costs. * We demonstrate that including drug spending in a cancer chemotherapy bundled payment model may be the best choice for a cancer care provider. * The method demonstrated in this article can be applied to any type of risk-based payment model and can substitute other specific aspects of the payment model beyond drugs. _____ Alternative payment models (APMs) for cancer care (eg, Medicare's Oncology Care Model [OCM] and Enhancing Oncology Model) usually are designed around the total cost of care (TCOC) for a given episode of care. [...]risk-bearing entities (eg, provider groups and health systems) considering participation in APMs that include drug spending often feel overly exposed to the actuarial risk of treating patients who need high-cost drugs. Variation in patient cost that cannot be accounted for by risk adjustment exposes provider groups to significant uncontrollable financial risk in an APM. Savings can arise by achieving better clinical outcomes (eg, reducing hospital admissions), increasing the efficiency of care delivery, implementing pathways, etc.7 Generally, provider groups that participate in APMs expect to receive a positive shared savings payment on average (if that were not the case, the provider group should not participate in the APM).

Tsilimingras et al. 1 investigate whether patients from urban and rural areas have similar rates of adverse events. They carefully consider a sample in one urban community hospital and track rates of adverse events using a rigorous, independently adjudicated method of detecting and classifying adverse events.

ABSTRACT BACKGROUND Low literacy increases the risk for many adverse health outcomes, but the relationship between literacy and adverse outcomes in heart failure (HF) has not been well studied. METHODS We studied a cohort of ambulatory patients with symptomatic HF (NYHA Class II-IV within the past 6 months) who were enrolled in a randomized controlled trial of self-care training recruited from internal medicine and cardiology clinics at four academic medical centers in the US. The primary outcome was combined all-cause hospitalization or death, with a secondary outcome of hospitalization for HF. Outcomes were assessed through blinded interviews and subsequent chart reviews, with adjudication of cause by a panel of masked assessors. Literacy was measured using the short Test of Functional Health Literacy in Adults. We used negative binomial regression to examine whether the incidence of the primary and secondary outcomes differed according to literacy. RESULTS Of the 595 study participants, 37 % had low literacy. Mean age was 61, 31 % were NYHA class III/IV at baseline, 16 % were Latino, and 38 % were African-American. Those with low literacy were older, had a higher NYHA class, and were more likely to be Latino (all p  < 0.001). Adjusting for site only, participants with low literacy had an incidence rate ratio (IRR) of 1.39 (95 % CI: 0.99, 1.94) for all-cause hospitalization or death and 1.36 (1.11, 1.66) for HF-related hospitalization. After adjusting for demographic, clinical, and self-management factors, the IRRs were 1.31 (1.06, 1.63) for all-cause hospitalization and death and 1.46 (1.20, 1.78) for HF-related hospitalization. CONCLUSIONS Low literacy increased the risk of hospitalization for ambulatory patients with heart failure. Interventions designed to mitigate literacy-related disparities in outcomes are warranted.