Geographic Disparities in Heart Failure Hospitalization Rates Among Medicare Beneficiaries

Clinical characteristics for distinguishing between acute cardiogenic pulmonary edema and community-acquired pneumonia in elderly patients: a prospective observational study

Heart failure and pneumonia are highly prevalent in elderly patients. We conducted a study to evaluate the differences in the patterns of symptoms, laboratory findings, and computed tomography (CT) results in elderly patients with acute cardiogenic pulmonary edema (ACPE) and community-acquired pneumonia (CAP). From January 1, 2015 to December 31, 2017, we studied 140 patients aged >75 years who were diagnosed with ACPE and CAP. Symptoms, laboratory findings, mean ostial pulmonary vein (PV) diameter and patterns on CT images were assessed. The primary measures of diagnostic accuracy were assessed using the positive likelihood ratio (LR+). The cutoff value of ostial PVs for differentiating patients with ACPE from CAP was evaluated using the receiver operating characteristic (ROC) analysis. Ninety-three patients with ACPE, 36 with CAP, and 11 with complicated ACPE/CAP were included. In patients with ACPE, edema (LR+ 5.4) was a moderate factor for rule-in, and a high brain natriuretic peptide level (LR+ 4.2) was weak. In patients with CAP, cough (LR+ 5.7) and leukocytosis (LR+ 5.2) were moderate factors for rule-in, while fever (LR+ 3.8) and a high C-reactive protein level (LR+ 4.8) were weak factors. The mean diameter of ostial PVs in patients with ACPE was significantly larger than that of patients with CAP (15.8± 1.8 mm vs 9.6±1.5 mm, p< 0.01). ROC analysis revealed that an ostial PV diameter cutoff of 12.5 mm was strong evidence for distinguishing ACPE from CAP with an area under the ROC curve of 0.99 and LR+ 36.0. In conclusion, as ACPE and CAP have similar symptoms and laboratory findings, dilated ostial PVs were useful in characterizing CT images to distinguish ACPE from CAP.

Epidemiology of geographic disparities in heart failure among US older adults: a Medicare-based analysis

BACKGROUND

There are prominent geographic disparities in the life expectancy (LE) of older US adults between the states with the highest (leading states) and lowest (lagging states) LE and their causes remain poorly understood. Heart failure (HF) has been proposed as a major contributor to these disparities. This study aims to investigate geographic disparities in HF outcomes between the leading and lagging states.

METHODS

The study was a secondary data analysis of HF outcomes in older US adults aged 65+, using Center for Disease Control and Prevention sponsored Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database and a nationally representative 5% sample of Medicare beneficiaries over 2000-2017. Empiric estimates of death certificate-based mortality from HF as underlying cause of death (CBM-UCD)/multiple cause of death (CBM-MCD); HF incidence-based mortality (IBM); HF incidence, prevalence, and survival were compared between the leading and lagging states. Cox regression was used to investigate the effect of residence in the lagging states on HF incidence and survival.

RESULTS

Between 2000 and 2017, HF mortality rates (per 100,000) were higher in the lagging states (CBM-UCD: 188.5-248.6; CBM-MCD: 749.4-965.9; IBM: 2656.0-2978.4) than that in the leading states (CBM-UCD: 79.4-95.6; CBM-MCD: 441.4-574.1; IBM: 1839.5-2138.1). Compared to their leading counterparts, lagging states had higher HF incidence (2.9-3.9% vs. 2.2-2.9%), prevalence (15.6-17.2% vs. 11.3-13.0%), and pre-existing prevalence at age 65 (5.3-7.3% vs. 2.8-4.1%). The most recent rates of one- (77.1% vs. 80.4%), three- (59.0% vs. 60.7%) and five-year (45.8% vs. 49.8%) survival were lower in the lagging states. A greater risk of HF incidence (Adjusted Hazards Ratio, AHR [95%CI]: 1.29 [1.29-1.30]) and death after HF diagnosis (AHR: 1.12 [1.11-1.13]) was observed for populations in the lagging states. The study also observed recent increases in CBMs and HF incidence, and declines in HF prevalence, prevalence at age 65 and survival with a decade-long plateau stage in IBM in both leading and lagging states.

CONCLUSION

There are substantial geographic disparities in HF mortality, incidence, prevalence, and survival across the U.S.: HF incidence, prevalence at age 65 (age of Medicare enrollment), and survival of patients with HF contributed most to these disparities. The geographic disparities and the recent increase in incidence and decline in survival underscore the importance of HF prevention strategies.

Association Between Perceived Access to Healthcare and the Perception of Illness Among Peruvian Adults with Chronic Diseases During COVID-19 Pandemic

The COVID-19 pandemic has greatly affected the provision of care for patients with chronic diseases. Due to social restrictions and reductions in contact with health services, the negative perception of chronic disease is expected to have increased. The aim of this study was to determine the association between perceived access to healthcare and the perception of illness among Peruvian population with chronic disease. It was a cross-sectional analytical study, with a sample of 987 inhabitants to whom the questionnaires “Coverage of health services” and “The Brief Illness Perception Questionnaire” (BIPQ) were applied. Having health insurance (PRa = 0.683; 95% CI = 0.613-0.761) acts as a protective factor for a positive illness perception of chronic disease, however, a waiting time greater than 3 months to obtain a medical appointment (PRa = 1.417; 95% CI = 1.319-1.522) and poor access to health services (PRa = 1.435; 95% CI = 1.226-1.681) resulted in the probability of a negative illness perception of chronic disease. Thus, there is an association between perceived poor access to healthcare and the negative illness perception of chronic disease in Peruvian population during pandemic COVID-19.

New Heart Failure After Myocardial Infarction (From the National Cardiovascular Data Registries [NCDR] Linked With All-Payer Claims)

Heart failure (HF) is common in patients presenting with acute myocardial infarction (MI), but incidence and predictors of new onset HF after hospitalization for MI are less well characterized. We evaluated patients hospitalized for acute MI without preceding or concurrent HF in the National Cardiovascular Data Registry (NCDR) CathPCI and Chest Pain-MI registries linked with claims data between April 2010 and March 2017. Cumulative incidence and independent predictors of HF after discharge were determined, and a simplified risk score was developed to predict incident HF following MI. In 337,274 patients with acute MI and no history of HF, 8.0% developed incident HF within 1 year after discharge and 18.8% developed HF within 5 years. Significant predictors of HF after MI included advanced chronic kidney disease (CKD) (HR 2.34, 95% confidence interval [CI] 2.23-2.46 for Stage IV vs Stage I, and HR 2.18, 95% CI 2.07-2.29 for Stage V vs. Stage I), recurrent MI following index MI (HR 2.24, 95% CI 2.19-2.28), African-American race (HR 1.44, 95% CI 1.40-1.48), and diabetes (HR 1.39, 95% CI 1.37-1.42). A risk score of 8 variables predicted HF with modest discrimination (optimism-corrected c-statistic 0.64) and good calibration. In conclusion, nearly 1 in 5 patients in a large nationally representative cohort without preceding or concurrent heart failure at time of MI developed incident HF within 5 years after discharge. Advanced CKD and recurrent MI were the strongest predictors of future HF. Increased recognition of specific risk factors for HF may help inform care strategies following MI.

Trends in heart failure-related cardiovascular mortality in rural versus urban United States counties, 2011-2018: A cross-sectional study

BACKGROUND

Adults in rural counties in the United States (US) experience higher rates broadly of cardiovascular disease (CVD) compared with adults in urban counties. Mortality rates specifically due to heart failure (HF) have increased since 2011, but estimates of heterogeneity at the county-level in HF-related mortality have not been produced. The objectives of this study were 1) to quantify nationwide trends by rural-urban designation and 2) examine county-level factors associated with rural-urban differences in HF-related mortality rates.

METHODS AND FINDINGS

We queried CDC WONDER to identify HF deaths between 2011-2018 defined as CVD (I00-78) as the underlying cause of death and HF (I50) as a contributing cause of death. First, we calculated national age-adjusted mortality rates (AAMR) and examined trends stratified by rural-urban status (defined using 2013 NCHS Urban-Rural Classification Scheme), age (35-64 and 65-84 years), and race-sex subgroups per year. Second, we combined all deaths from 2011-2018 and estimated incidence rate ratios (IRR) in HF-related mortality for rural versus urban counties using multivariable negative binomial regression models with adjustment for demographic and socioeconomic characteristics, risk factor prevalence, and physician density. Between 2011-2018, 162,314 and 580,305 HF-related deaths occurred in rural and urban counties, respectively. AAMRs were consistently higher for residents in rural compared with urban counties (73.2 [95% CI: 72.2-74.2] vs. 57.2 [56.8-57.6] in 2018, respectively). The highest AAMR was observed in rural Black men (131.1 [123.3-138.9] in 2018) with greatest increases in HF-related mortality in those 35-64 years (+6.1%/year). The rural-urban IRR persisted among both younger (1.10 [1.04-1.16]) and older adults (1.04 [1.02-1.07]) after adjustment for county-level factors. Main limitations included lack of individual-level data and county dropout due to low event rates (<20).

CONCLUSIONS

Differences in county-level factors may account for a significant amount of the observed variation in HF-related mortality between rural and urban counties. Efforts to reduce the rural-urban disparity in HF-related mortality rates will likely require diverse public health and clinical interventions targeting the underlying causes of this disparity.

A Smartphone App for Self-Management of Heart Failure in Older African Americans: Feasibility and Usability Study

Background

Mobile health (mHealth) apps are dramatically changing how patients and providers manage and monitor chronic health conditions, especially in the area of self-monitoring. African Americans have higher mortality rates from heart failure than other racial groups in the United States. Therefore, self-management of heart failure may improve health outcomes for African American patients.

Objective

The aim of the present study was to determine the feasibility of using an mHealth app, and explore the outcomes of quality of life, including self-care maintenance, management, and confidence, among African American patients managing their condition after discharge with a diagnosis of heart failure.

Methods

Prior to development of the app, we conducted qualitative interviews with 7 African American patients diagnosed with heart failure, 3 African American patients diagnosed with cardiovascular disease, and 6 health care providers (cardiologists, nurse practitioners, and a geriatrician) who worked with heart failure patients. In addition, we asked 6 hospital chaplains to provide positive spiritual messages for the patients, since spirituality is an important coping method for many African Americans. These formative data were then used for creating a prototype of the app, named Healthy Heart. Specifically, the Healthy Heart app incorporated the following evidence-based features to promote self-management: one-way messages, journaling (ie, weight and symptoms), graphical display of data, and customized feedback (ie, clinical decision support) based on daily or weekly weight. The educational messages about heart failure self-management were derived from the teaching materials provided to the patients diagnosed with heart failure, and included information on diet, sleep, stress, and medication adherence. The information was condensed and simplified to be appropriate for text messages and to meet health literacy standards. Other messages were derived from interviews conducted during the formative stage of app development, including interviews with African American chaplains. Usability testing was conducted over a series of meetings between nurses, social workers, and computer engineers. A pilot one-group pretest-posttest design was employed with participants using the mHealth app for 4 weeks. Descriptive statistics were computed for each of the demographic variables, overall and subscales for Health Related Quality of Life Scale 14 (HQOL14) and subscales for the Self-Care of Heart Failure Index (SCHFI) Version 6 using frequencies for categorical measures and means with standard deviations for continuous measures. Baseline and postintervention comparisons were computed using the Fisher exact test for overall health and paired t tests for HQOL14 and SCHFI questionnaire subscales.

Results

A total of 12 African American participants (7 men, 5 women; aged 51-69 years) diagnosed with heart failure were recruited for the study. There was no significant increase in quality of life (P=.15), but clinically relevant changes in self-care maintenance, management, and confidence were observed.

Conclusions

An mHealth app to assist with the self-management of heart failure is feasible in patients with low literacy, low health literacy, and limited smartphone experience. Based on the clinically relevant changes observed in this feasibility study of the Healthy Heart app, further research should explore effectiveness in this vulnerable population.

Congestive heart failure-related hospital deaths across the urban-rural continuum in the United States

Congestive heart failure (CHF) is a growing public health problem that affects nearly 6.5 million individuals nationwide. Access to quality outpatient care and disease management programs has been shown to improve disease treatment and prognosis. Rural populations face unique challenges in the availability and accessibility of quality cardiovascular care. In 2018, we conducted a pooled cross-sectional analysis of the Nationwide Inpatient Sample (NIS) for 2009–2014 to examine recent trends in CHF-related hospital deaths in the United States, highlighting urban-rural differences within each census region. We performed a multivariable logistic regression analysis to compare the odds of CHF-related hospital death, by levels of rurality and within each census region. Most CHF-related hospital deaths occurred in the South and Midwest census regions and in large central metropolitan areas. Findings from census region stratified models revealed that non-core residents living within the West (OR 1.47, CI 1.26, 1.71), Midwest (OR 1.30, CI 1.17, 1.44), and South (OR = 1.21, 95% C.I. = 1.12–1.32) had a higher relative risk (but not higher absolute numbers) of experiencing death during a CHF-related hospitalization, compared to patients in large central metropolitan areas. Within each census region, there were also differences in odds of a CHF-related hospital death depending on patient sex, comorbidities, insurance type, median annual income, and year. As efforts to reduce rural health disparities in CHF morbidity continue, more work is needed to understand and test interventions to reduce the risk of death from CHF in noncore areas of the West, Midwest, and South.

Regional differences in heart failure hospitalizations, mortality, and readmissions in Slovenia 2004-2012

Aims

Heart failure (HF) burden is displaying significant inter‐regional differences within Europe and within countries. Due to limited data focusing on regional differences, our aim was to evaluate HF hospitalizations, readmissions, and mortality burden in Slovenian statistical regions.

Methods and results

The Slovenian National Hospitalization Discharge Registry was searched for HF hospitalizations in patients 20 years or over in the period 2004–12. Annual sex and age‐standardized HF hospitalizations, mortality, and HF readmissions rates were calculated for Slovenia and for each Slovenian statistical region. Trends were evaluated using ANOVA. Multiple mixed effect logistic regression models, which included statistical region, admission year, sex, age, intensive care unit treatment, and co‐morbidities as a fixed effect and hospital identifier as a random effect, were calculated for mortality and readmissions. Overall, 156 859 HF hospitalizations (55 522 where HF was coded as a main diagnosis and 43 606 as first HF hospitalizations) were recorded. Annual standardized rates varied considerably between statistical regions for main (220–511) and first HF hospitalization (392–721), 30 day (12.6–27.1) and 1 year mortality (66–117), and 30 day (31–80.8) and 1 year readmission (99–24) (per 100 000 patient years in 2012). Yearly decline in HF hospitalization rates was seen for national main (3.6; 0.001) and first (8.4; 0.083) HF hospitalizations, while individual regional main and first HF hospitalization trends mostly did not reach statistical significance. No relevant differences in mortality and readmission endpoints for statistical regions were seen when adjusted for patient demographics and specific co‐morbidities.

Conclusions

Significant regional differences in standardized HF hospitalization, mortality, and readmissions between the regions were seen. There were no differences in mortality and readmissions between statistical regions for individual similar patients.

Impact of residence altitude on readmission in patients with heart failure

Objective

Mountain districts normally have tougher geographic conditions than plain districts, which might worsen heart failure (HF) conditions in patients. Also, those places frequently are associated with social problems of ageing, underpopulation and fewer medical services, which might cause delay in detection of disease progression and require more admissions. We investigated the association of residence altitude with readmission in patients with HF.

Methods

We followed 452 patients with HF to determine all-cause readmissions over a median of 1.1 years. The altitude of patient residences, population, proportion of the elderly and number of hospitals or clinics in a minor administrative district (Cho-Aza district) located at the residences were examined using data from the 2010 census and Google Maps.

Results

All-cause readmissions were observed in 269 (60%) patients. The altitude of ≥200  m was significantly associated with readmissions (HR, 1.49; 95 % CI 1.12 to 1.96; p=0.006) after adjustment for physical and haemodynamic parameters, left ventricular ejection fraction, brain natriuretic peptide and components of the established score for predicting readmission for HF. Altitude was significantly associated with ageing, underpopulation, fewer hospitals or clinics and lower temperature (all p<0.01), with an increased tendency for readmission during the winter season; however, it was not associated with patient clinical parameters.

Conclusions

High altitude residence may be an important predictor for readmission in patients with HF. This relationship may be confounded by unfavourable sociogeographic conditions at higher altitudes.

Socioeconomic status and access to care and the incidence of a heart failure diagnosis in the inpatient and outpatient settings

PURPOSE

Despite well-documented associations of socioeconomic status with incident heart failure (HF) hospitalization, little information exists on the relationship of socioeconomic status with HF diagnosed in the outpatient (OP) setting.

METHODS

We used Poisson models to examine the association of area-level indicators of educational attainment, poverty, living situation, and density of primary care physicians with incident HF diagnosed in the inpatient (IP) and OP settings among a cohort of Medicare beneficiaries (n = 109,756; 2001-2013).

RESULTS

The age-standardized rate of HF incidence was 35.8 (95% confidence interval [CI], 35.1-36.5) and 13.9 (95% CI, 13.5-14.4) cases per 1000 person-years in IP and OP settings, respectively. The incidence rate differences (IRDs) per 1000 person-years in both settings suggested greater incidence of HF in high- compared to low-poverty areas (IP IRD = 4.47 [95% CI, 3.29-5.65], OP IRD = 1.41 [95% CI, 0.61-2.22]) and in low- compared to high-education areas (IP IRD = 3.73 [95% CI, 2.63-4.82], OP IRD = 1.72 [95% CI, 0.97-2.47]).

CONCLUSIONS

Our results highlight the role of area-level social determinants of health in the incidence of HF in both the IP and OP settings. These findings may have implications for HF prevention policies.

Leading causes of cardiovascular hospitalization in 8.45 million US veterans

Background

We sought to determine the leading causes of cardiovascular (CV) hospitalization, and to describe and compare national rates of CV hospitalization by age, gender, race, ethnicity, region, and year, among U.S. veterans.

Methods

We evaluated the electronic health records of all veterans aged ≥18 years who had accessed any healthcare services at either a VA healthcare facility or a non-VA healthcare facility that was reimbursed by the VA, between January 1 2010 and December 31 2014. Among these 8,452,912 patients, we identified the 5 leading causes of CV hospitalization and compared rates of hospitalization by age, gender, race, ethnicity, region, year and type of VA healthcare user.

Results

The top 5 causes of CV hospitalization were: coronary atherosclerosis, heart failure, acute myocardial infarction, stroke and atrial fibrillation. Overall, 297,373 (3.5%) veterans were hospitalized for one or more of these cardiovascular conditions. The percentage of veterans hospitalized for one or more of these CV conditions decreased over time, from 1.23% in 2010 to 1.18% in 2013, followed by a slight increase to 1.20% in 2014. There was significant variation in rates of CV hospitalization by gender, race, ethnicity, geographic region, and urban vs. rural zip code. In particular, older, male, Black, non-Hispanic, urban and Continental region veterans experienced the highest rates of CV hospitalizations.

Conclusions

Among 8.5 million patients enrolled in the VA healthcare system from 2010 to 2014, there was substantial variation in rates of CV hospitalization by age, gender, race, geographical distribution, year, and use of non-VA (vs. VA only) healthcare care facilities.

Cardiovascular Health in African Americans: A Scientific Statement From the American Heart Association

BACKGROUND AND PURPOSE

Population-wide reductions in cardiovascular disease incidence and mortality have not been shared equally by African Americans. The burden of cardiovascular disease in the African American community remains high and is a primary cause of disparities in life expectancy between African Americans and whites. The objectives of the present scientific statement are to describe cardiovascular health in African Americans and to highlight unique considerations for disease prevention and management.

METHOD

The primary sources of information were identified with PubMed/Medline and online sources from the Centers for Disease Control and Prevention.

RESULTS

The higher prevalence of traditional cardiovascular risk factors (eg, hypertension, diabetes mellitus, obesity, and atherosclerotic cardiovascular risk) underlies the relatively earlier age of onset of cardiovascular diseases among African Americans. Hypertension in particular is highly prevalent among African Americans and contributes directly to the notable disparities in stroke, heart failure, and peripheral artery disease among African Americans. Despite the availability of effective pharmacotherapies and indications for some tailored pharmacotherapies for African Americans (eg, heart failure medications), disease management is less effective among African Americans, yielding higher mortality. Explanations for these persistent disparities in cardiovascular disease are multifactorial and span from the individual level to the social environment.

CONCLUSIONS

The strategies needed to promote equity in the cardiovascular health of African Americans require input from a broad set of stakeholders, including clinicians and researchers from across multiple disciplines.

Usefulness of a Noninvasive Device to Identify Elevated Left Ventricular Filling Pressure Using Finger Photoplethysmography During a Valsalva Maneuver

The high rate of re-hospitalization for heart failure might be reduced by improving noninvasive techniques for identifying elevated left ventricular (LV) filling pressure. We previously showed that changes in a finger photoplethysmography (PPG) waveform during the Valsalva maneuver (VM) reflect invasively measured LV end-diastolic pressure (LVEDP). We have since developed a hand-held device that analyzes PPG while guiding the expiratory effort of a VM. Here we assessed the sensitivity and specificity of this device for identifying elevated LVEDP in patients. We tested 82 participants (28 women), aged 40 to 85 years, before a clinically indicated left heart catheterization. Each performed a VM between 18 and 25 mm Hg for 10 seconds into a pressure transducer. PPG was recorded continuously before and during the VM. LVEDP was measured during the catheterization. An equation for calculating LVEDP was derived using (1) ratio of signal amplitudes: minimum during VM to average at baseline, (2) ratio of peak-to-peak time intervals: minimum during VM to average at baseline, and (3) mean blood pressure. Calculated and measured LVEDP were compared. The range of measured LVEDP was 4 to 35 mm Hg. Calculated LVEDP correlated with measured LVEDP (p <0.0001, r = 0.56). A calculated LVEDP >20 mm Hg had a 70% sensitivity and 86% specificity for identifying measured LVEDP >20 mm Hg (area under receiver-operating characteristic curve 0.83). In conclusion, a hand-held device for assessing LV filling pressure had high specificity and good sensitivity for identifying LVEDP >20 mm Hg, a clinically meaningful threshold in heart failure.

Clustering of Five Health-Related Behaviors for Chronic Disease Prevention Among Adults, United States, 2013

Introduction

Five key health-related behaviors for chronic disease prevention are never smoking, getting regular physical activity, consuming no alcohol or only moderate amounts, maintaining a normal body weight, and obtaining daily sufficient sleep. The objective of this study was to estimate the clustering of these 5 health-related behaviors among adults aged 21 years or older in each state and the District of Columbia and to assess geographic variation in clustering.

Methods

We used data from the 2013 Behavioral Risk Factor Surveillance System (BRFSS) to assess the clustering of the 5 behaviors among 395,343 BRFSS respondents aged 21 years or older. The 5 behaviors were defined as currently not smoking cigarettes, meeting the aerobic physical activity recommendation, consuming no alcohol or only moderate amounts, maintaining a normal body mass index (BMI), and sleeping at least 7 hours per 24-hour period. Prevalence of having 4 or 5 of these behaviors, by state, was also examined.

Results

Among US adults, 81.6% were current nonsmokers, 63.9% obtained 7 hours or more sleep per day, 63.1% reported moderate or no alcohol consumption, 50.4% met physical activity recommendations, and 32.5% had a normal BMI. Only 1.4% of respondents engaged in none of the 5 behaviors; 8.4%, 1 behavior; 24.3%, 2 behaviors; 35.4%, 3 behaviors; and 24.3%, 4 behaviors; only 6.3% reported engaging in all 5 behaviors. The highest prevalence of engaging in 4 or 5 behaviors was clustered in the Pacific and Rocky Mountain states. Lowest prevalence was in the southern states and along the Ohio River.

Conclusion

Additional efforts are needed to increase the proportion of the population that engages in all 5 health-related behaviors and to eliminate geographic variation. Collaborative efforts in health care systems, communities, work sites, and schools can promote all 5 behaviors and produce population-wide changes, especially among the socioeconomically disadvantaged.

Rural patients' knowledge about heart failure

BACKGROUND

Heart failure (HF) is a potentially disabling condition requiring significant patient knowledge to manage the requirements of self-care. The need for self-care is important for all patients but particularly for those living in rural areas that are geographically remote from healthcare services.

OBJECTIVE

The aim of this study was to identify the level of knowledge of rural patients with HF and the clinical and demographic characteristics associated with low levels of HF knowledge.

METHODS

Baseline data from 612 patients with HF enrolled in the Rural Education to Improve Outcomes in Heart Failure trial were analyzed using the Heart Failure Knowledge Scale, the Short Test of Functional Health Literacy in Adults, and the anxiety subscale of the Brief Symptom Inventory. Multiple linear regression was used to explore the contribution of sociodemographic and clinical variables to levels of HF knowledge.

RESULTS

The mean (SD) age was 66 (13) years; 59% were men, and 50.5% had an ejection fraction of less than 40%. The mean (SD) percent correct on the Heart Failure Knowledge Scale was 69.5% (13%; range, 25%-100%), with the most frequent incorrect items related to symptoms of HF and the need for daily weights. The men and the older patients scored significantly lower in HF knowledge than did the women and the younger patients (P = 0.002 and 0.011, respectively). The patients with preserved systolic function also scored significantly lower than those with systolic HF (P = 0.030).

CONCLUSIONS

Patients who are at risk for poor self-care because of low levels of HF knowledge can be identified. Older patients, men, and, patients with HF with preserved systolic function may require special educational strategies to gain the knowledge required for effective self-care.

A systematic review of the magnitude and cause of geographic variation in unplanned hospital admission rates and length of stay for ambulatory care sensitive conditions

Background

Unplanned hospital admissions place a large and increasing strain on healthcare budgets worldwide. Many admissions for ambulatory care sensitive conditions (ACSCs) are thought to be preventable, a belief supported by significant geographic variations in admission rates. We conducted a systematic review of the evidence on the magnitude and correlates of geographic variation in ACSC admission rates and length of stay (LOS).

Methods

We performed a search of Medline and Embase databases for English language cross-sectional and cohort studies on 28th March 2013 reporting geographic variation in admission rates or LOS for patients receiving unplanned care across at least 10 geographical units for one of 35 previously defined ACSCs. Forward and backward citation searches were undertaken on all included studies. We provide a narrative synthesis of study findings. Study quality was assessed using a modified Newcastle-Ottawa scale.

Results

We included 39 studies comprising 25 on admission rates and 14 on LOS. Studies generally compared admission rates between regions (e.g. states) and LOS between hospitals. Most of the published research was undertaken in the US, UK or Canada and often focussed on patients with pneumonia, COPD or heart failure. 35 (90 %) studies concluded that geographic variation was present. Primary care quality and secondary care access were frequently suggested as drivers of admission rate variation whilst secondary care quality and adherence to clinical guidelines were often listed as contributors to LOS variation. Several different methods were used to quantify variation, some studies listed raw data, failed to control for confounders and used naive statistical methods which limited their utility.

Conclusions

The substantial geographical variations in the admission rates and LOS of potentially avoidable conditions could be a symptom of variable quality of care and should be a concern for clinicians and policymakers. Policymakers targeting a reduction in unplanned admissions could introduce initiatives to improve primary care access and quality or develop alternatives to admission. Those attempting to curb unnecessarily long LOS could introduce care pathways or guidelines. Methodological work on the quantification and reporting of geographic variation is needed to aid inter-study comparisons.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-015-0964-3) contains supplementary material, which is available to authorized users.

Support for physical activity policies and perceptions of work and neighborhood environments: variance by BMI and activity status at the county and individual levels

PURPOSE

To examine support for local policies encouraging physical activity and perceived neighborhood environment characteristics by physical activity and weight status of respondents across U.S. counties.

DESIGN

We used a random-digit-dial, computer-assisted telephone interview (CATI) to conduct a cross-sectional telephone questionnaire in selected U.S. counties in 2011.

SETTING

Counties with high prevalences of obesity and sedentary behavior (HH; n = 884) and counties with low prevalences of obesity and sedentary behavior (LL; n = 171) were selected nationally.

SUBJECTS

Adult respondents from HH (n = 642) and LL (n = 566) counties.

MEASURES

Questions were asked of respondents, pertaining to support for physical activity policies in various settings, neighborhood features, time spent in physical activity and sedentary behaviors, self-reported weight and height, and personal demographic information.

ANALYSIS

Means and frequencies were calculated; bivariable and multivariable linear and logistic regression models, developed. Models were adjusted for individual characteristics and county HH/LL status.

RESULTS

Respondents in LL counties perceived their neighborhood and work environments to be more supportive of healthy behaviors and were more supportive of local physical activity policies than respondents in HH counties (p < .001 for all). Positive neighborhood environment perceptions were related to reduced body mass index, increased physical activity, and decreased sedentary behavior.

CONCLUSION

Policy support and neighborhood environments are associated with behaviors. Results can inform targeting policy agendas to facilitate the improvement of environments (community, work, and school) to be more supportive of physical activity.

Economic impact assessment from the use of a mobile app for the self-management of heart diseases by patients with heart failure in a Spanish region

Currently, cardiovascular diseases are the deadliest diseases with a total of 17 million deaths worldwide. Hence, they are the focus of many mobile applications for smartphones and tablets. This paper will assess the ex-ante economic impact as well as will determine the cost-effectiveness analysis that the use of one of this app, CardioManager, by patients with heart failure will have in a Spanish community, Castile and Leon. For this, a cost-effectiveness analysis using the hidden Markov model were performed in a hypothetical cohort of patients diagnosed with heart failure, based on the information of epidemiological parameters and the costs derived from the management and care of heart failure patients by the Public Health Care System of Castile and Leon. The costs of patient care were estimated from the perspective of the Ministry of Health of Spain using a discount rate of 3 %. Finally, an estimation of the ex-ante impact that would suppose the introduction of CardioManager in the Health Care System is performed. It is concluded that the introduction of CardioManager may generate a 33 % reduction in the cost of management and treatment of the disease. This means that CardioManager may be able to save more than 9,000 € per patient to the local Health Care System of Castile and Leon, which can be translated in a saving of 0.31 % of the total health expenditure of the region.

Comparison of mobile apps for the leading causes of death among different income zones: a review of the literature and app stores

Background

The advances achieved in technology, medicine, and communications in the past decades have created an excellent scenario for the improvement and expansion of eHeath and mHealth in particular. Mobile phones, smartphones, and tablets are exceptional means for the application of mobile health, especially for those diseases and health conditions that are the deadliest worldwide.

Objective

The main aim of this paper was to compare the amount of research and the number of mobile apps dedicated to the diseases and conditions that are the leading causes of death according to the World Health Organization grouped by different income regions. These diseases and conditions were ischemic heart disease; stroke and other cerebrovascular diseases; lower respiratory infections; chronic obstructive pulmonary disease; diarrheal diseases; HIV/AIDS; trachea, bronchus, and lung cancers; malaria; and Alzheimer disease and other dementias.

Methods

Two reviews were conducted. In the first, the systems IEEE Xplore, Scopus, Web of Knowledge, and PubMed were used to perform a literature review of applications related to the mentioned diseases. The second was developed in the currently most important mobile phone apps stores: Google play, iTunes, BlackBerry World, and Windows Phone Apps+Games.

Results

Search queries up to June 2013 located 371 papers and 557 apps related to the leading causes of death, and the following findings were obtained. Alzheimer disease and other dementias are included in the diseases with more apps, although it is not among the top 10 causes of death worldwide, whereas lower respiratory infections, the third leading cause of death, is one of the less researched and with fewer apps. Two diseases that are the first and second of low-income countries (lower respiratory infections and diarrheal diseases) have very little research and few commercial applications. HIV/AIDS, in the top 6 of low-income and middle-income zones, is one of the diseases with more research and applications, although it is not in the top 10 in high-income countries. Trachea, bronchus, and lung cancers are the third cause of death in high-income countries but are one of the least researched diseases with regard to apps.

Conclusions

Concerning mobile apps, there is more work done in the commercial field than in the research field, although the distribution among the diseases is similar in both fields. In general, apps for common diseases of low- and middle-income countries are not as abundant as those for typical diseases of developed countries. Nevertheless, there are some exceptions such as HIV/AIDS, due to its important social conscience; and trachea, bronchus and lung cancers, which was totally unexpected.

Hospital-level variation in the use of intensive care

OBJECTIVE

To determine the extent to which hospitals vary in the use of intensive care, and the proportion of variation attributable to differences in hospital practice that is independent of known patient and hospital factors.

DATA SOURCE

Hospital discharge data in the State Inpatient Database for Maryland and Washington States in 2006.

STUDY DESIGN

Cross-sectional analysis of 90 short-term, acute care hospitals with critical care capabilities. DATA COLLECTION/METHODS: We quantified the proportion of variation in intensive care use attributable to hospitals using intraclass correlation coefficients derived from mixed-effects logistic regression models after successive adjustment for known patient and hospital factors.

PRINCIPAL FINDINGS

The proportion of hospitalized patients admitted to an intensive care unit (ICU) across hospitals ranged from 3 to 55 percent (median 12 percent; IQR: 9, 17 percent). After adjustment for patient factors, 19.7 percent (95 percent CI: 15.1, 24.4) of total variation in ICU use across hospitals was attributable to hospitals. When observed hospital characteristics were added, the proportion of total variation in intensive care use attributable to unmeasured hospital factors decreased by 26-14.6 percent (95 percent CI: 11, 18.3 percent).

CONCLUSIONS

Wide variability exists in the use of intensive care across hospitals, not attributable to known patient or hospital factors, and may be a target to improve efficiency and quality of critical care.

Geographic variations in heart failure hospitalizations among medicare beneficiaries in the Tennessee catchment area

INTRODUCTION

Although differences in heart failure (HF) hospitalization rates by race and sex are well documented, little is known about geographic variations in hospitalizations for HF, the most common discharge diagnosis for Medicare beneficiaries.

METHODS

Using exploratory spatial data analysis techniques, the authors examined hospitalization rates for HF as the first-listed discharge diagnosis among Medicare beneficiaries in a 10-state Tennessee catchment area, based on the resident states reported by Tennessee hospitals from 2000 to 2004.

RESULTS

The age-adjusted HF hospitalization rate (per 1000) among Medicare beneficiaries was 23.3 [95% confidence interval (CI), 23.3-23.4] for the Tennessee catchment area, 21.4 (95% CI, 21.4-21.5) outside the catchment area and 21.9 (95% CI, 21.9-22.0) for the overall United States. The age-adjusted HF hospitalization rates were also significantly higher in the catchment area than outside the catchment area and overall, among men, women and whites, whereas rates among the blacks were higher outside the catchment area. Beneficiaries in the catchment area also had higher age-specific HF hospitalization rates. Among states in the catchment area, the highest mean county-level rates were in Mississippi (30.6 ± 7.6) and Kentucky (29.2 ± 11.5), and the lowest were in North Carolina (21.7 ± 5.7) and Virginia (21.8 ± 6.6).

CONCLUSIONS

Knowledge of these geographic differences in HF hospitalization rates can be useful in identifying needs of healthcare providers, allocating resources, developing comprehensive HF outreach programs and formulating policies to reduce these differences.

Sacramento area breast cancer epidemiology study: use of postmastectomy breast reconstruction along the rural-to-urban continuum

BACKGROUND

Health care disparities have been documented in rural populations. The authors hypothesized that breast cancer patients in urban counties would have higher rates of postmastectomy breast reconstruction relative to patients in surrounding near-metro and rural counties.

METHODS

The authors used the Surveillance, Epidemiology, and End Results database to identify patients diagnosed with breast cancer and treated with mastectomy in the greater Sacramento area between 2000 and 2006. Counties were categorized as urban, near-metro, or rural. Univariate models evaluated the relationship of rural, near-metro, or urban location with use of breast reconstruction by means of the chi-square test. Multivariate logistic regression models controlling for patient, tumor, and treatment-related factors predicted use of breast reconstruction. The likelihood of undergoing breast reconstruction was reported as odds ratios with 95 percent confidence intervals; significance was set at p≤0.05.

RESULTS

Complete information was available for 3552 breast cancer patients treated with mastectomy. Of these, 718 (20.2 percent) underwent breast reconstruction. On univariate analysis, differences in the rates of breast reconstruction were noted among urban, near-metro, and rural areas (p<0.001). On multivariate analysis, patients from rural (odds ratio, 0.51; 95 percent confidence interval, 0.28 to 0.93; p<0.03) and near-metro (odds ratio, 0.73; 95 percent confidence interval, 0.59 to 0.89; p=0.002) areas had a decreased likelihood of undergoing breast reconstruction relative to patients from urban areas.

CONCLUSIONS

Patients from near-metro and rural areas are less likely to undergo breast reconstruction following mastectomy for breast cancer than their urban counterparts. Differences in use of breast reconstruction detected at a population level should guide future interventions to increase rates of breast reconstruction at the local level.