The Landscape of State Policies Supporting Family Caregivers as Aligned With the National Academy of Medicine Recommendations.

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.

Which Definition of Rurality Should I Use?: The Relative Performance of 8 Federal Rural Definitions in Identifying Rural-Urban Disparities.

BACKGROUND: The federal government uses multiple definitions for identifying rural communities based on various geographies and different elements of rurality. OBJECTIVES: The objectives of this study were to: (1) assess the degree to which rural definitions identify the same areas as rural; and (2) assess rural-urban disparities identified by each definition across socioeconomic, demographic, and health access and outcome measures. RESEARCH DESIGN: We determined the rural status of each census tract and calculated the rural-urban disparity resulting from each definition, as well as across the number of definitions in which tracts were designated as rural (rurality agreement). SUBJECTS: The population in 72,506 census tracts. MEASURES: We used 8 federal rural definitions. Population characteristics included percent with a bachelor's degree, income below 200% poverty, population density, percent with health insurance and whether various health care services were within 30 minutes driving time of the tract centroid. RESULTS: The rural population varied from slightly < 6.9 million people to >75.5 million across definitions. The largest rural-urban disparities were found using Urban Influence Codes. Urbanized Area and Urbanized Cluster tended to generate smaller disparities. Population characteristics such as population density and percent White had notable discontinuities across levels of rurality, while others such as percent with a bachelor's degree and income below 200% poverty varied continuously. CONCLUSIONS: Rural-urban populations and disparities were sensitive to the specific definition and the relative strength of definitions varied across population characteristics. Researchers and policymakers should carefully consider the choice of outcome and region when deciding the most appropriate rural definition.

The Effect of the Magnet Recognition Signal on Hospital Financial Performance.

EXECUTIVE SUMMARY: The objective of this study was to investigate the effect of the Magnet Recognition (MR) signal on hospital financial performance. MR is a quality designation granted by the American Nurses Credentialing Center (ANCC). Growing evidence shows that MR hospitals are associated with various interrelated positive outcomes that have been theorized to affect hospital financial performance.In this study, which covered the period from 2000 to 2010, we applied a pre-post research design using a longitudinal, unbalanced panel of MR hospitals and hospitals that had never received MR designation located in urban areas in the United States. We obtained data for this analysis from Medicare's Hospital Cost Report Information System, the American Hospital Association Annual Survey Database, the Health Resources & Services Administration's Area Resource File, and the ANCC website. Propensity score matching was used to construct the final study sample. We then applied a difference-in-difference model with hospital fixed effects to the matched hospital sample to test the effect of the MR signal, while controlling for both hospital and market characteristics.According to signaling theory, signals aim to reduce the imbalance of information between two parties, such as patients and providers. The MR signal was found to have a significant positive effect on hospital financial performance. These findings support claims in the literature that the nonfinancial benefits resulting from MR lead to improved financial performance. In the current healthcare environment in which reimbursement is increasingly tied to delivery of quality care, healthcare executives may be encouraged to pursue MR to help hospitals maintain their financial viability while improving quality of care.

The relationship between violence in Northern Mexico and potentially avoidable hospitalizations in the USA-Mexico border region.

BACKGROUND: Substantial proportions of US residents in the USA-Mexico border region cross into Mexico for health care; increases in violence in northern Mexico may have affected this access. We quantified associations between violence in Mexico and decreases in access to care for border county residents. We also examined associations between border county residence and access. METHODS: We used hospital inpatient data for Arizona, California and Texas (2005-10) to estimate associations between homicide rates and the probability of hospitalization for ambulatory care sensitive (ACS) conditions. Hospitalizations for ACS conditions were compared with homicide rates in Mexican municipalities matched by patient residence. RESULTS: A 1 SD increase in the homicide rate of the nearest Mexican municipality was associated with a 2.2 percentage point increase in the probability of being hospitalized for an ACS condition for border county patients. Residence in a border county was associated with a 1.3 percentage point decrease in the probability of being hospitalized for an ACS condition. CONCLUSIONS: Increased homicide rates in Mexico were associated with increased hospitalizations for ACS conditions in the USA, although residence in a border county was associated with decreased probability of being hospitalized for an ACS condition. Expanding access in the border region may mitigate these effects by providing alternative sources of care.

Self-reported recall and daily diary-recorded measures of weight monitoring adherence: associations with heart failure-related hospitalization.

BACKGROUND: Weight monitoring is an important element of HF self-care, yet the most clinically meaningful way to evaluate weight monitoring adherence is uncertain. We conducted this study to evaluate the association of (1) self-reported recall and (2) daily diary-recorded weight monitoring adherence with heart failure-related (HF-related) hospitalization. METHODS: We conducted a prospective cohort study among 216 patients within a randomized trial of HF self-care training. All patients had an initial self-care training session followed by 15 calls (median) to reinforce educational material; patients were also given digital scales, instructed to weigh daily, record weights in a diary, and mail diaries back monthly. Weight monitoring adherence was assessed with a self-reported recall question administered at 12 months and dichotomized into at least daily versus less frequent weighing. Diary-recorded weight monitoring was evaluated over 12 months and dichotomized into ≥80% and <80% adherence. HF-related hospitalizations were ascertained through patient report and confirmed through record review. RESULTS: Over 12 months in 216 patients, we identified 50 HF-related hospitalizations. Patients self-reporting daily or more frequent weight monitoring had an incidence rate ratio of 1.34 (95% CI 0.24-7.32) for HF-related hospitalizations compared to those reporting less frequent weight monitoring. Patients who completed ≥80% of weight diaries had an IRR of 0.37 (95% CI 0.18-0.75) for HF-related hospitalizations compared to patients who completed <80% of weight diaries. CONCLUSIONS: Self-reported recall of weight monitoring adherence was not associated with fewer HF hospitalizations. In contrast, diary-recorded adherence ≥80% of days was associated with fewer HF-related hospitalizations. Incorporating diary-based measures of weight monitoring adherence into HF self-care training programs may help to identify patients at risk for HF-related hospitalizations.

A single-item self-report medication adherence question predicts hospitalisation and death in patients with heart failure.

AIMS AND OBJECTIVES: To determine whether a single-item self-report medication adherence question predicts hospitalisation and death in patients with heart failure. BACKGROUND: Poor medication adherence is associated with increased morbidity and mortality. Having a simple means of identifying suboptimal medication adherence could help identify at-risk patients for interventions. DESIGN: We performed a prospective cohort study in 592 participants with heart failure within a four-site randomised trial. METHODS: Self-report medication adherence was assessed at baseline using a single-item question: 'Over the past seven days, how many times did you miss a dose of any of your heart medication?' Participants who reported no missing doses were defined as fully adherent, and those missing more than one dose were considered less than fully adherent. The primary outcome was combined all-cause hospitalisation or death over one year and the secondary endpoint was heart failure hospitalisation. Outcomes were assessed with blinded chart reviews, and heart failure outcomes were determined by a blinded adjudication committee. We used negative binomial regression to examine the relationship between medication adherence and outcomes. RESULTS: Fifty-two percent of participants were 52% male, mean age was 61 years, and 31% were of New York Heart Association class III/IV at enrolment; 72% of participants reported full adherence to their heart medicine at baseline. Participants with full medication adherence had a lower rate of all-cause hospitalisation and death (0·71 events/year) compared with those with any nonadherence (0·86 events/year): adjusted-for-site incidence rate ratio was 0·83, fully adjusted incidence rate ratio 0·68. Incidence rate ratios were similar for heart failure hospitalisations. CONCLUSION: A single medication adherence question at baseline predicts hospitalisation and death over one year in heart failure patients. RELEVANCE TO CLINICAL PRACTICE: Medication adherence is associated with all-cause and heart failure-related hospitalisation and death in heart failure. It is important for clinicians to assess patients' medication adherence on a regular basis at their clinical follow-ups.

Multisite randomized trial of a single-session versus multisession literacy-sensitive self-care intervention for patients with heart failure.

BACKGROUND: Self-care training can reduce hospitalization for heart failure (HF), and more intensive intervention may benefit more vulnerable patients, including those with low literacy. METHODS AND RESULTS: A 1-year, multisite, randomized, controlled comparative effectiveness trial with 605 patients with HF was conducted. Those randomized to a single session received a 40-minute in-person, literacy-sensitive training; the multisession group received the same initial training and then ongoing telephone-based support. The primary outcome was combined incidence of all-cause hospitalization or death; secondary outcomes included HF-related hospitalization and HF-related quality of life, with prespecified stratification by literacy. Overall, the incidence of all-cause hospitalization and death did not differ between intervention groups (incidence rate ratio, 1.01; 95% confidence interval, 0.83-1.22). The effect of multisession training compared with single-session training differed by literacy group: Among those with low literacy, the multisession training yielded a lower incidence of all-cause hospitalization and death (incidence rate ratio, 0.75; 95% confidence interval, 0.45-1.25), and among those with higher literacy, the multisession intervention yielded a higher incidence (incidence rate ratio, 1.22; 95% confidence interval, 0.99-1.50; interaction P=0.048). For HF-related hospitalization, among those with low literacy, multisession training yielded a lower incidence (incidence rate ratio, 0.53; 95% confidence interval, 0.25-1.12), and among those with higher literacy, it yielded a higher incidence (incidence rate ratio, 1.32; 95% confidence interval, 0.92-1.88; interaction P=0.005). HF-related quality of life improved more for patients receiving multisession than for those receiving single-session interventions at 1 and 6 months, but the difference at 12 months was smaller. Effects on HF-related quality of life did not differ by literacy. CONCLUSIONS: Overall, an intensive multisession intervention did not change clinical outcomes compared with a single-session intervention. People with low literacy appear to benefit more from multisession interventions than people with higher literacy. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00378950.

Low literacy is associated with increased risk of hospitalization and death among individuals with heart failure.

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.

Characteristics of Hospitals by Graduate Medical Education Expense Category: Implications for Rural Residency Program Expansion.

PURPOSE: To describe how the characteristics of the hospitals and communities they serve vary across the 4 hospital graduate medical education (GME) expense categories (according to Section 131 of the Consolidated Appropriations Act of 2021) and identify the rurally located never claimer hospitals that are most similar to teaching hospitals, signaling that they might be good candidates for new rural GME programs. METHOD: Hospital categories and characteristics were gathered from the March 2022 Medicare Cost Reports; 2022 County Health Rankings & Roadmaps data were used for community characteristics. Each acute hospital was classified into 1 of the following 4 mutually exclusive hospital categories: category A, category B, established teaching hospital (ETH), and never claimer. Multinomial logistic regressions were conducted to estimate the adjusted associations of hospital characteristics with hospital categories and to identify the never claimer hospitals in rural locations that have characteristics similar to teaching hospitals (category A, category B, and ETHs). RESULTS: Out of 3,590 hospitals, 2,075 (57.8%) were never claimer hospitals. After adjusting for multiple characteristics, rural hospitals had a similar probability of being in each hospital category as that of urban hospitals. Never claimer hospitals served an older population and were located in communities with more uninsured adults and children and less availability of primary care physicians, dentists, and mental health professionals. CONCLUSIONS: This study demonstrated that most hospitals in every category, but especially teaching hospitals (i.e., category A hospitals, category B hospitals, and ETHs), were concentrated in urban areas. Larger hospitals (measured by net patient revenue) were more likely to report GME expenses (i.e., be a category A hospital, a category B hospital, or an ETH). The study suggests that there are roughly 145 rural never claimer hospitals that might be strong candidates for initiating new residency programs.

Impact of including drug spending in oncology alternative payment models.

OBJECTIVES: To develop a method for determining the effect of including drug costs in alternative payment models (APMs). STUDY DESIGN: Retrospective claims analysis. METHODS: Using the Oncology Care Model as an example, we developed an oncology episode payment model for a commercial payer using historical claims data. We defined 6-month episodes of chemotherapy. Using claims data, we characterized episodes and developed a risk adjustment model. We used bootstrapping to estimate the variation in episode cost with drugs included and without. RESULTS: Episode costs were approximately $100,000. Although absolute cost variation was higher when we included drugs, the percent of total cost represented by variation was lower. Under reasonable assumptions about potential savings from drug and nondrug spending, our results suggest that including drugs in APMs can improve the risk-benefit trade-off faced by provider groups. We introduce a risk-mitigated sharing rate that may enable inclusion of drugs in APMs without substantially increasing downside risk. CONCLUSIONS: We have developed a method to assess whether the inclusion of drug spending in APMs is a good decision for provider groups. Including drug costs in episode payments for oncology patients may be preferable for many provider groups.

Bolstering the rural physician workforce in underserved communities: Are Rural Residency Planning and Development Programs finding the sweet spot?

PURPOSE: The purpose of this study is to describe the characteristics of Rural Residency Planning and Development (RRPD) Programs, compare the characteristics of counties with and without RRPD programs, and identify rural places where future RRPD programs could be developed. METHODS: The study sample comprised 67 rural sites training residents in 40 counties in 24 US states. Descriptive statistics were used to describe RRPD programs and logistic regression to predict the probability of a county being an RRPD site as a function of population, primary care physicians (PCP) per 10,000 population, and the social vulnerability index (SVI) compared to a control sample of nonmetro counties without RRPD sites. FINDINGS: Most RRPD grantees (78%) were family medicine programs affiliated with medical schools (97%). RRPD counties were more populous (P<.01), had a higher population density (P<.05), and a higher percent of the non-White or Hispanic population (P = .05) compared to non-RRPD counties. Both higher population (P<.001) and PCP ratio (P = .046) were strong predictors, while SVI (P = .07) was a weak predictor of being an RRPD county. CONCLUSIONS: RRPD sites appear to represent a "sweet spot" of rural counties that have the population and physician supply to support a training program but also are relatively more socially vulnerable with high-need populations. Additional counties fitting this "sweet spot" could be targeted for funding to address health disparities and health workforce maldistribution.

Is adherence to weight monitoring or weight-based diuretic self-adjustment associated with fewer heart failure-related emergency department visits or hospitalizations?

BACKGROUND: Heart failure (HF) self-care interventions can improve outcomes, but less than optimal adherence may limit their effectiveness. We evaluated if adherence to weight monitoring and diuretic self-adjustment was associated with HF-related emergency department (ED) visits or hospitalizations. METHODS AND RESULTS: We performed a case-control analysis nested in a HF self-care randomized trial. Participants received HF self-care training, including weight monitoring and diuretic self-adjustment, which they were to record in a diary. We defined case time periods as HF-related ED visits or hospitalizations in the 7 preceding days; control time periods were defined as 7-day periods free of ED visits and hospitalizations. We used logistic regression to compare weight monitoring and diuretic self-adjustment adherence in case and control time periods, adjusted for demographic and clinical covariates. Among 303 participants, we identified 81 HF-related ED visits or hospitalizations (cases) in 54 patients over 1 year of follow-up. Weight monitoring adherence (odds ratio [OR] 0.42, 95% confidence interval [CI] 0.23-0.76) and diuretic self-adjustment adherence (OR 0.44, 95% CI 0.19-0.98) were both associated with lower adjusted odds of HF-related ED visits or hospitalizations. CONCLUSIONS: Adherence to weight monitoring and diuretic self-adjustment was associated with lower odds of HF-related ED visits or hospitalizations. Adherence to these activities may reduce HF-related morbidity.

The other yearly checkup: your Medicare drug plan.

OBJECTIVES: To quantify seniors' potential savings for switching to a new prescription drug plan (PDP) for 2011 and to assess predictors of which seniors could save most by reviewing their PDPs annually. METHODS: This cross-sectional analysis included 404 Medicare beneficiaries 65 years or older who selected PDPs at Senior PharmAssist (SPA), a pharmacist-led nonprofit in Durham, NC. RESULTS: Seniors had a mean potential savings of $348 for the year. The 62% of beneficiaries who could save by switching plans had a mean potential savings of $559. None of the factors examined predicted whether seniors would have potential savings. Among those with any potential savings, individuals taking more medications ( P = 0.003), people with no low-income subsidy ( P = 0.0002), and first-time consulters ( P = 0.03) had greater potential savings. CONCLUSION: Some seniors can realize substantial cost savings by changing PDPs annually. Pharmacists can help patients save money, reduce sources of nonadherence, and earn appreciation as professionals by alerting patients to these potential savings and referring them to help in selecting a plan.

Achieving benchmark financial performance in CAHs: lessons from high performers.

CEOs and CFOs of 19 critical access hospitals (CAHs) that achieved benchmark financial performance over three years were interviewed regarding the strategies they use. The interviews identified nine success factors for exemplary financial performance that were common to all or most of the 19 hospitals. All of the participating executives agreed that other CAHs would likely benefit from applying these nine success factors.

The contributions of survey-based versus administrative measures of socioeconomic status in predicting type of post-acute care for hospitalized Medicare beneficiaries.

OBJECTIVES: To assess and compare the associations between socioeconomic status (SES) measures from two sources (claims vs. survey data) and the type of post-acute care (PAC) locations following hospital discharge. METHODS: This observational study included Medicare Fee-for-Service (FFS) beneficiaries age 65.5 years or older who participated in the Medicare Current Beneficiary Survey (MCBS) and were hospitalized in 2006-2011. Multiple data sets were used including: Area Deprivation Index; Medicare Cost Reports, Provider of Services files, and Area Health Resource File. Multinomial regression models estimated associations between beneficiary's SES and PAC type. SES measures came from surveys (income and education) and administrative records (dual enrollment and area deprivation). PAC types included home with self-care, home health agency, skilled nursing facility (SNF), or inpatient rehabilitation facility. RESULTS: Low income and dual enrollment were associated with higher SNF use while living in a deprived area was associated with lower SNF use and higher use of home with self-care. Dual enrollment and area deprivation were associated with the largest differences. CONCLUSIONS: If policies to modify payment based on SES are considered, administrative measures (dual enrollment and area deprivation) rather than survey measures (education and income) may be sufficient.

The economic effects of rural hospital closures.

OBJECTIVE: To provide an updated analysis of the economic effects of rural hospital closures. STUDY SETTING: Our study sample was national in scope and consisted of nonmetro counties from 2001 to 2018. STUDY DESIGN: We used a difference-in-differences study design to estimate the effect of a hospital closure on county income, population, unemployment, and size of the labor force. Specifically, we compared economic changes over time in nonmetro counties experiencing a hospital closure to changes in a control group of nonmetro counties over the same time period. We also leveraged insight from recent research to control for estimation bias due to heterogeneity in the closure effect over time or across groups defined by when closure was experienced. DATA EXTRACTION: Data on (adjusted gross) annual income (in real dollars), annual population size, and monthly unemployment rate and labor force size were sourced from the Internal Revenue Service, Census Bureau, and Bureau of Labor Statistics, respectively. We used data from the North Carolina Rural Health Research Program to identify counties that experienced a hospital closure. PRINCIPAL FINDINGS: Of the 1759 nonmetro counties in our study sample, 109 experienced a hospital closure during the study period. Relative to the nonclosure counterfactual, closures significantly decreased labor force size, on average, by 1.4% (95% CI: [-2.1%, -0.8%]). Results also suggest that Prospective Payment System (PPS) hospital closures significantly decreased population size, on average, by 1.1% (95% CI: [-1.7%, -0.5%]), relative to the nonclosure counterfactual. CONCLUSIONS: Our analysis suggests that rural hospital closures often have adverse effects on local economic outcomes. Importantly, the negative economic effects of closure appear to be strongest following Prospective Payment System hospital closures and attenuated when the closed hospital is converted to another type of health care facility, allowing for the continued provision of services other than inpatient care.

The effect of progressive, reinforcing telephone education and counseling versus brief educational intervention on knowledge, self-care behaviors and heart failure symptoms.

BACKGROUND: The optimal strategy for promoting self-care for heart failure (HF) is unclear. METHODS AND RESULTS: We conducted a randomized trial to determine whether a "teach to goal" (TTG) educational and behavioral support program provided incremental benefits to a brief (1 hour) educational intervention (BEI) for knowledge, self-care behaviors, and HF-related quality of life (HFQOL). The TTG program taught use of adjusted-dose diuretics and then reinforced learning goals and behaviors with 5 to 8 telephone counseling sessions over 1 month. Participants' (n = 605) mean age was 61 years; 37% had marginal or inadequate literacy; 69% had ejection fraction <0.45; and 31% had Class III or IV symptoms. The TTG group had greater improvements in general and salt knowledge (P < .001) and greater increases in self-care behaviors (from mean 4.8 to 7.6 for TTG vs. 5.2 to 6.7 for BEI; P < .001). HFQOL improved from 58.5 to 64.6 for the TTG group but did not change for the BEI group (64.7 to 63.9; P < .001 for the difference in change scores). Improvements were similar regardless of participants' literacy level. CONCLUSIONS: Telephone reinforcement of learning goals and self-care behaviors improved knowledge, health behaviors, and HF-related QOL compared to a single education session.

Relationship between literacy, knowledge, self-care behaviors, and heart failure-related quality of life among patients with heart failure.

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.

Disparities in postacute rehabilitation care for stroke: an analysis of the state inpatient databases.

OBJECTIVE: To determine the extent to which sociodemographic and geographic disparities exist in the use of postacute rehabilitation care (PARC) after stroke. DESIGN: Cross-sectional analysis of data for 2 years (2005-2006) from the State Inpatient Databases. SETTING: All short-term acute-care hospitals in 4 demographically and geographically diverse states. PARTICIPANTS: Individuals (age, ≥45y; mean age, 72.6y) with a primary diagnosis of stroke who survived their inpatient stay (N=187,188). The sample was 52.4% women, 79.5% white, 11.4% black, and 9.1% Hispanic. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: (1) Discharge to an institution versus home. (2) For those discharged to home, receipt of home health (HH) versus no HH care. (3) For those discharged to an institution, receipt of inpatient rehabilitation facility (IRF) or skilled nursing facility (SNF) care. Multilevel logistic regression analyses were conducted to identify sociodemographic and geographic disparities in PARC use, controlling for illness severity/comorbid conditions, hospital characteristics, and PARC supply. RESULTS: Blacks, women, older individuals, and those with lower incomes were more likely to receive institutional care; Hispanics and the uninsured were less likely. Racial minorities, women, older individuals, and those with lower incomes were more likely to receive HH care; uninsured individuals were less likely. Blacks, women, older individuals, the uninsured, and those with lower incomes were more likely to receive SNF versus IRF care. PARC use varied significantly by hospital and geographic location. CONCLUSIONS: Several sociodemographic and geographic disparities in PARC use were identified.

Decline in Inpatient Volume at Rural Hospitals.

PURPOSE: To investigate (1) all-payer inpatient volume changes at rural hospitals and (2) whether trends in inpatient volume differ by organizational and geographic characteristics of the hospital and characteristics of the patient population. METHODS: We used a retrospective, longitudinal study design. Our study sample consisted of rural hospitals between 2011 and 2017. Inpatient volume was measured as inpatient average daily census (ADC). Additional measured hospital characteristics included census region, Medicare payment type, ownership type, number of beds, local competition, total margin, and whether the hospital was located in a Medicaid expansion state. Measured characteristics of the local patient population included total population size, percent of population aged 65 years or older, and percent of population in poverty. To identify predictors of inpatient volume trends, we fit a linear multiple regression model using generalized estimating equations. FINDINGS: Rural hospitals experienced an average change in ADC of -13% between 2011 and 2017. We found that hospital characteristics (eg, census region, Medicare payment type, ownership type, total margin, whether the hospital was located in a Medicaid expansion state) and patient population characteristics (eg, percent of population in poverty) were significant predictors of inpatient volume trends. CONCLUSIONS: Trends in inpatient volume differ by organizational and geographic characteristics of the hospital and characteristics of the patient population. Researchers and policy makers should continue to explore the causal mechanisms of inpatient volume decline and its role in the financial viability of rural hospitals.