Postdischarge environment following heart failure hospitalization: expanding the view of hospital readmission

Leveraging home health aides to improve outcomes in heart failure: A pilot study protocol

Heart failure (HF) affects six million people in the U.S., is associated with high morbidity, mortality, and healthcare utilization.(1, 2) Despite a decade of innovation, the majority of interventions aimed at reducing hospitalization and readmissions in HF have not been successful.(3-7) One reason may be that most have overlooked the role of home health aides and attendants (HHAs), who are often highly involved in HF care.(8-13) Despite their contributions, studies have found that HHAs lack specific HF training and have difficulty reaching their nursing supervisors when they need urgent help with their patients. Here we describe the protocol for a pilot randomized control trial (pRCT) assessing a novel stakeholder-engaged intervention that provides HHAs with a) HF training (enhanced usual care arm) and b) HF training plus a mobile health application that allows them to chat with a nurse in real-time (intervention arm). In collaboration with the VNS Health of New York, NY, we will conduct a single-site parallel arm pRCT with 104 participants (HHAs) to evaluate the feasibility, acceptability, and effectiveness (primary outcomes: HF knowledge; HF caregiving self-efficacy) of the intervention among HHAs caring for HF patients. We hypothesize that educating and better integrating HHAs into the care team can improve their ability to provide support for patients and outcomes for HF patients as well (exploratory outcomes include hospitalization, emergency department visits, and readmission). This study offers a novel and potentially scalable way to leverage the HHA workforce and improve the outcomes of the patients for whom they care. Clinical trial.gov registration: NCT04239911.

Historical Redlining and Heart Failure Outcomes Following Hospitalization in the Southeastern United States

BACKGROUND

Historical redlining, a discriminatory lending practice, is an understudied component of the patient risk environment following hospital discharge. We investigated associations between redlining, patient race, and outcomes following heart failure hospitalization.

METHODS AND RESULTS

We followed a hospital-based cohort of Black and White patients using electronic medical records for acute heart failure hospitalizations between 2010 and 2018 (n=6800). Patient residential census tracts were geocoded according to the 1930s Home Owners' Loan Corporation map grades (A/B: best/still desirable, C: declining, D: redlined). We used Poisson regression to analyze associations between Home Owners' Loan Corporation grade and 30-day outcomes (readmissions, mortality, and their composite). One-third of patients resided in historically redlined tracts (n=2034). In race-stratified analyses, there was a positive association between historically declining neighborhoods and composite readmissions and mortality for Black patients (risk ratio [RR], 1.24 [95% CI, 1.003-1.54]) and an inverse association between redlined neighborhoods and 30-day readmissions among White patients (RR, 0.58 [95% CI, 0.39-0.86]). Examining racial disparities across Home Owners' Loan Corporation grades, Black patients had higher 30-day readmissions (RR, 1.86 [95% CI, 1.31-2.65]) and composite readmissions and mortality (RR, 1.32 [95% CI, 1.04-1.65]) only in historically redlined neighborhoods.

CONCLUSIONS

Historical redlining had potentially mixed impacts on outcomes by race, such that residing in less desirable neighborhoods was associated with an elevated risk of an adverse outcome following heart failure hospitalization in Black patients and a reduced risk in White patients. Moreover, racial disparities in patient outcomes were present only in historically redlined neighborhoods. Additional research is needed to explore observed heterogeneity in outcomes.

Deep learning-based prediction of heart failure rehospitalization during 6, 12, 24-month follow-ups in patients with acute myocardial infarction

Heart failure is a clinical syndrome that occurs when the heart is too weak or stiff and cannot pump enough blood that our body needs. It is one of the most expensive diseases due to frequent hospitalizations and emergency room visits. Reducing unnecessary rehospitalizations is also an important and challenging task that has the potential of saving healthcare costs, enabling discharge planning, and identifying patients at high risk. Therefore, this paper proposes a deep learning-based prediction model of heart failure rehospitalization during 6, 12, 24-month follow-ups after hospital discharge in patients with acute myocardial infarction (AMI). We used the Korea Acute Myocardial Infarction-National Institutes of Health (KAMIR-NIH) registry which included 13,104 patient records and 551 features. The proposed deep learning-based rehospitalization prediction model outperformed traditional machine learning algorithms such as logistic regression, support vector machine, AdaBoost, gradient boosting machine, and random forest. The performance of the proposed model was accuracy, the area under the curve, precision, recall, specificity, and F1 score of 99.37%, 99.90%, 96.86%, 98.61%, 99.49%, and 97.73%, respectively. This study showed the potential of a deep learning-based model for cardiology, which can be used for decision-making and medical diagnosis tool of heart failure rehospitalization in patients with AMI.

Relation of Neighborhood Disadvantage to Heart Failure Symptoms and Hospitalizations

Residence in socioeconomically deprived neighborhoods may influence patient's health-related behaviors and overall health. We evaluated the association of neighborhood disadvantage on heart failure (HF) symptom burden and hospitalization rates. We characterized neighborhood deprivation in 359 HF subjects (age 56 ± 13 years, 52% black) in metropolitan Atlanta using the Area Deprivation Index (ADI). ANOVA was used to compare HF symptoms measured using the Kansas City Cardiomyopathy Questionnaire, and HF Self-Care Index across ADI tertiles. Zero-inflated Poisson regression was used to compare rates of recurrent HF hospitalization (HFH) across ADI tertiles. Subjects living in more deprived neighborhoods were more likely to be black, have Medicare or Medicaid insurance, and have a lower ejection fraction than those living in less deprived neighborhoods (all p ≤ 0.005). Subjects in more deprived neighborhoods had more severe HF symptoms (p < 0.001), but there was no difference in HF Self-Care Index scores across ADI tertiles. Subjects living in more deprived neighborhoods had a higher odds of being hospitalized for HF than subjects in less deprived neighborhoods. Once subjects had experienced a HFH, however, the association between ADI and the risk of recurrent HFH varied by racial group. In whites, increasing ADI was associated with a marginally decreased risk of recurrent HFH, while there was no association between ADI and recurrent HFH in blacks. In conclusion, patients with HF living in more deprived neighborhoods have greater symptom burden and are more likely to experience a HFH than those living in less deprived neighborhoods.

Understanding the Complexity of Heart Failure Risk and Treatment in Black Patients

Although care of patients with heart failure (HF) has improved in the past decade, important disparities in HF outcomes persist based on race/ethnicity. Age-adjusted HF-related cardiovascular disease death rates are higher for Black patients, particularly among young Black men and women whose rates of death are 2.6- and 2.97-fold higher, respectively, than White men and women. Similarly, the rate of HF hospitalization for Black men and women is nearly 2.5-fold higher when compared with Whites, with costs that are significantly higher in the first year after HF hospitalization. While the relative rate of HF hospitalization has improved for other race/ethnic minorities, the disparity in HF hospitalization between Black and White patients has not decreased during the last decade. Although access to care and socioeconomic status have been traditional explanations for the observed racial disparities in HF outcomes, contemporary data suggest that novel factors including genetic susceptibility as well as social determinants of health and implicit bias may play a larger role in health outcomes than previously appreciated. The purpose of this review is to describe the complex interplay of factors that influence racial disparities in HF incidence, prevalence, and disease severity, with a highlight on evolving knowledge that will impact the clinical care and address future research needs to improve HF disparities in Blacks.

Readmission rates following heart failure: a scoping review of sex and gender based considerations

Background

Although hospital readmission for heart failure (HF) is an issue for both men and women, little is known about differences in readmission rates by sex. Consequently, strategies to optimize readmission reduction programs and care strategies for women and men remain unclear. Our study aims were: (1) to identify studies examining readmission rates according to sex, and (2) to provide a qualitative overview of possible considerations for the impact of sex or gender.

Methods

We conducted a scoping review using the Arksey and O’Malley framework to include full text articles published between 2002 and 2017 drawn from multiple databases (MEDLINE, EMBASE), grey literature (i.e. National Technical information, Duck Duck Go), and expert consultation. Eligible articles included an index heart failure episode, readmission rates, and sex/gender-based analysis.

Results

The search generated 5887 articles, of which 746 underwent full abstract text consideration for eligibility. Of 164 eligible articles, 34 studies addressed the primary outcome, 103 studies considered sex differences as a secondary outcome and 25 studies stratified data for sex. Good inter-rater agreement was reached: 83% title/abstract; 88% full text; kappa: 0.69 (95%CI: 0.53–0.85). Twelve of 34 studies reported higher heart failure readmission rates for men and six studies reported higher heart failure readmission rates for women. Using non composite endpoints, five studies reported higher HF readmission rates for men compared to three studies reporting higher HF readmission rates for women. Overall, there was heterogeneity between studies when examined by sex, but one observation emerged that was related to the timing of readmissions. Readmission rates for men were higher when follow-up duration was longer than 1 year. Women were more likely to experience higher readmission rates than men when time to event was less than 1 year.

Conclusions

Future studies should consider different time horizons in their designs and avoid the use of composite measures, such as readmission rates combined with mortality, which are highly skewed by sex. Co-interventions and targeted post-discharge approaches with attention to sex would be of benefit to the HF patient population.

Social Determinants of Health and 90-Day Mortality After Hospitalization for Heart Failure in the REGARDS Study

Background

Outcomes following heart failure (HF) hospitalizations are poor, with 90‐day mortality rates of 15% to 20%. Although prior studies found associations between individual social determinants of health (SDOH) and post‐discharge mortality, less is known about how an individuals’ total burden of SDOH affects 90‐day mortality.

Methods and Results

We included participants of the REGARDS (Reasons for Geographic and Racial Differences in Stroke) Study who were Medicare beneficiaries aged ≥65 years discharged alive after an adjudicated HF hospitalization. Guided by the Healthy People 2020 Framework, we examined 9 SDOH. First, we examined age‐adjusted associations between each SDOH and 90‐day mortality; those associated with 90‐day mortality were used to create an SDOH count. Next, we determined the hazard of 90‐day mortality by the SDOH count, adjusting for confounders. Over 10 years, 690 participants were hospitalized for HF at 440 unique hospitals in the United States; there were a total of 79 deaths within 90 days. Overall, 28% of participants had 0 SDOH, 39% had 1, and 32% had ≥2. Compared with those with 0, the age‐adjusted hazard ratio for 90‐day mortality among those with 1 SDOH was 2.89 (95% CI, 1.46–5.72) and was 3.06 (1.51–6.19) among those with ≥2 SDOH. The adjusted hazard ratio was 2.78 (1.37–5.62) and 2.57 (1.19–5.54) for participants with 1 SDOH and ≥2, respectively.

Conclusions

While having any of the SDOH studied here markedly increased risk of 90‐day mortality after an HF hospitalization, a greater burden of SDOH was not associated with significantly greater risk in our population.

Hierarchical analysis of factors associated with hospital readmissions for coronary heart disease: A case-control study

AIMS AND OBJECTIVES

To analyse, hierarchically, factors associated with hospital readmissions for acute coronary syndrome.

BACKGROUND

Hospital readmissions have risen, especially in patients with multiple comorbidities, which are most often chronic. The leading causes of hospital readmission include acute coronary syndrome, which is costly and often preventable. Determining clinical and nonclinical variables that increase the chances of readmission is important to assess and evaluate patients hospitalised for coronary heart diseases.

DESIGN

A case-control study whose dependent variable was hospital readmission for acute coronary syndrome.

METHODS

The study included 277 inpatients, of whom 132 were in their first hospitalisation and 145 had already been hospitalised for acute coronary syndrome. The independent variables for this hierarchical model were sociodemographic conditions, life habits, access to health services and physical health measures. Data were obtained by interviews, anthropometric measurements and patient records. Logistic regression analysis was performed using the stepwise technique, with Microsoft Excel and R version 3.2.3. The research was reported via strengthening the reporting of observational studies in epidemiology (STROBE).

RESULTS

In the final hierarchical logistic model, the following risk factors were associated with readmission for acute coronary syndrome: inadequate drug therapy adherence, stress, history of smoking for 30 years or more, and the lack of use of primary healthcare services.

CONCLUSIONS

Clinical and nonclinical variables are related to hospital readmission for acute coronary syndrome and can increase the chance of readmission by up to six times.

RELEVANCE TO CLINICAL PRACTICE

The predictive model can be used to avoid readmission for acute coronary syndrome, and it represents an advance in the prediction of the occurrence of the outcome. This implies the need for a reorientation of the network for postdischarge care in the first hospitalisation for acute coronary syndrome.

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.

Predictive models for identifying risk of readmission after index hospitalization for heart failure: A systematic review

Aims:

Readmission rates for patients with heart failure have consistently remained high over the past two decades. As more electronic data, computing power, and newer statistical techniques become available, data-driven care could be achieved by creating predictive models for adverse outcomes such as readmissions. We therefore aimed to review models for predicting risk of readmission for patients admitted for heart failure. We also aimed to analyze and possibly group the predictors used across the models.

Methods:

Major electronic databases were searched to identify studies that examined correlation between readmission for heart failure and risk factors using multivariate models. We rigorously followed the review process using PRISMA methodology and other established criteria for quality assessment of the studies.

Results:

We did a detailed review of 334 papers and found 25 multivariate predictive models built using data from either health system or trials. A majority of models was built using multiple logistic regression followed by Cox proportional hazards regression. Some newer studies ventured into non-parametric and machine learning methods. Overall predictive accuracy with C-statistics ranged from 0.59 to 0.84. We examined significant predictors across the studies using clinical, administrative, and psychosocial groups.

Conclusions:

Complex disease management and correspondingly increasing costs for heart failure are driving innovations in building risk prediction models for readmission. Large volumes of diverse electronic data and new statistical methods have improved the predictive power of the models over the past two decades. More work is needed for calibration, external validation, and deployment of such models for clinical use.

Incidence of and risk factors for newly diagnosed hyperkalemia after hospital discharge in non-dialysis-dependent CKD patients treated with RAS inhibitors

INTRODUCTION

Renin-angiotensin system (RAS) inhibitors have been increasingly prescribed due to their beneficial effects on end-organ protection. Iatrogenic hyperkalemia is a well-known life-threatening complication of RAS inhibitor use in chronic kidney disease (CKD) patients. We hypothesized that CKD patients treated with RAS inhibitors frequently develop hyperkalemia after hospital discharge even if they were normokalemic during their hospitalization because their lifestyles change substantially after discharge. The present study aimed to examine the incidence of newly diagnosed hyperkalemia, the timing of hyperkalemia, and its risk factors in CKD patients treated with RAS inhibitors at the time of hospital discharge.

METHODS

We retrospectively enrolled patients aged 20 years or older with CKD G3-5 (estimated glomerular filtration rate < 60 mL/min/1.73 m2) and who were treated with RAS inhibitors and discharged from St. Luke's International Hospital between July 2011 and December 2015. Patients who were under maintenance dialysis or had hyperkalemic events before discharge were excluded. Data regarding the patients' age, sex, CKD stage, diabetes mellitus status, malignancy status, combined use of RAS inhibitors, concurrent medication, and hyperkalemic events after discharge were extracted from the hospital database. Our primary outcome was hyperkalemia, defined as serum potassium ≥ 5.5 mEq/L. Multiple logistic regression and Kaplan-Meier analyses were performed to identify the risk factors for and the timing of hyperkalemia, respectively.

RESULTS

Among the 986 patients, 121 (12.3%) developed hyperkalemia after discharge. In the regression analysis, relative to CKD G3a, G3b [odds ratio (OR): 1.88, 95% confidence interval 1.20-2.97] and G4-5 (OR: 3.40, 1.99-5.81) were significantly associated with hyperkalemia. The use of RAS inhibitor combinations (OR: 1.92, 1.19-3.10), malignancy status (OR: 2.10, 1.14-3.86), and baseline serum potassium (OR: 1.91, 1.23-2.97) were also significantly associated with hyperkalemia. The Kaplan-Meier analysis showed that hyperkalemia was most frequent during the early period after discharge, particularly within one month.

CONCLUSION

Hyperkalemia was frequent during the early period after discharge among previously normokalemic CKD patients who were treated with RAS inhibitors. Appropriate follow-up after discharge should be required for these patients, particularly those with advanced CKD or malignancy status, such as hematological malignancy or late-stage malignancy, and those who are treated with multiple RAS inhibitors.

Congestive heart failure disease management program: 1-Year population experience from a tertiary center heart failure registry in Saudi Arabia

Aims

We aimed to evaluate congestive heart failure (CHF) multidisciplinary disease management program (DMProg) impact on mortality, readmission rates, length of stay (LOS), and gender health characteristics.

Methods and results

This was a quasi-observational, pre- and post-trial with a parallel nonequivalent group. We enrolled 174 inpatients having CHF with reduced ejection fraction and New York Heart Association (NYHA) Class II–IV, and a total of 197 hospital admissions. A comparative follow-up was performed from 15 December 2014 to 15 December 2015. Among 197 consecutive hospital admissions, 76 (39%) were included in the preintervention or usual care group and 121 (61%) were assigned to the postintervention group. After 1 year, in comparison with the preintervention group, the postintervention group had shorter average LOS in days (7.6 days vs. 11.1 days, p < 0.002), lower 1-year readmission rate (36% vs. 57%, p < 0.003), and lower in-house mortality (1.6% vs. 7.8%, p = 0.03), but similar baseline mortality scores (38.2 vs. 38.6, p = 0.7), 30-day and 90-day readmission rates (15% vs. 18.3%, p = 0.62 and 27.6% vs. 30%, p = 0.65), and 30-day readmission risk score (24.9% vs. 26.2%, p = 0.09). By regression analysis, the DMProg intervention was an independent factor for 1-year readmission reduction (p = 0.001). Kaplan–Meier survival analysis favored the postintervention group (log-rank, p < 0.001).

Conclusion

DMProg significantly decreased 1-year readmission rates, LOS, and in-house mortality.

Predicting Negative Events: Using Post-discharge Data to Detect High-Risk Patients

Predicting negative outcomes, such as readmission or death, and detecting high-risk patients are important yet challenging problems in medical informatics. Various models have been proposed to detect high-risk patients; however, the state of the art relies on patient information collected before or at the time of discharge to predict future outcomes. In this paper, we investigate the effect of including data generated post discharge to predict negative outcomes. Specifically, we focus on two types of patients admitted to the Vanderbilt University Medical Center between 2010-2013: i) those with an acute event - 704 hip fractures and ii) those with chronic problems - 5250 congestive heart failure (CHF) patients. We show that the post-discharge model improved the AUC of the LACE index, a standard readmission scoring function, by 20 - 30%. Moreover, the new model resulted in higher AUCs by 15 - 27% for hip fracture and 10 - 12% for CHF compared to standard models.

Effective Strategies in Reducing Rehospitalizations in Patients With Heart Failure

Aging of the population and prolongation of the lives of patients with heart failure (HF) by advanced therapeutic innovations has led to an elevating number of patients who live with HF. The American Heart Association estimated that 5.1 million Americans were affected with HF in 2013 and approximately 23 million individuals were affected worldwide. Despite the improved management approaches, the mortality rate is still high; less than half of the patients with HF remain alive after 5 years of HF diagnosis and less than a quarter of them after 10 years. HF costs the nation a huge amount of money. The total cost comprises $34.4 billion each year, including the health care services, medications, and loss of productivity. Hospitalization is a common issue in HF, estimated as primary diagnosis in more than 1 million each year. Readmission after initial hospitalization is another concern in patients with HF. Around 25% will be readmitted in the next 30 days after hospital discharge, out of which only one-third is due to HF. It also costs the government an exhausting amount of money. The report of Medicare Payment Advisory Commission that was provided to the congress in 2008 showed that the expenses on HF readmissions were about $903. In this review, we intended to demonstrate the different strategies that could improve the readmission rates in patients with HF and ultimately decrease the health care payments. These strategies include evidence-based management programs, surgical therapy, risk factors adjustment, and disease monitoring.

Lay Consultations in Heart Failure Symptom Evaluation

PURPOSE

Lay consultations can facilitate or impede healthcare. However, little is known about how lay consultations for symptom evaluation affect treatment decision-making. The purpose of this study was to explore the role of lay consultations in symptom evaluation prior to hospitalization among patients with heart failure.

METHODS

Semi-structured interviews were conducted with 60 patients hospitalized for acute decompensated heart failure. Chi-square and Fisher's exact tests, along with logistic regression were used to characterize lay consultations in this sample.

RESULTS

A large proportion of patients engaged in lay consultations for symptom evaluation and decision-making before hospitalization. Lay consultants provided attributions and advice and helped make the decision to seek medical care. Men consulted more often with their spouse than women, while women more often consulted with adult children.

CONCLUSIONS

Findings have implications for optimizing heart failure self-management interventions, improving outcomes, and reducing hospital readmissions.

Contribution of the long-term care insurance certificate for predicting 1-year all-cause readmission compared with validated risk scores in elderly patients with heart failure

Objectives

Readmission is a common and serious problem associated with heart failure (HF). Unfortunately, conventional risk models have limited predictive value for predicting readmission. The recipients of long-term care insurance (LTCI) are frail and have mental and physical impairments. We hypothesised that adjustment of the conventional risk score with an LTCI certificate enables a more accurate appreciation of readmission for HF.

Methods

We investigated 452 patients with HF who were followed up for 1 year to determine all-cause readmission. We obtained their clinical and socioeconomic data, including LTCI. The three clinical risk scores used in our evaluation were Keenan (2008), Krumholz (2000) and Charlson (1994). We used net reclassification improvement (NRI) to assess the incremental benefit.

Results

Patients with LTCI were significantly older, and had a higher prevalence of cerebrovascular disease and dementia than those without LTCI. One-year all-cause readmission (n=193, 43%) was significantly associated with all risk scores, receiving LTCI and the category of LTCI. Receiving LTCI was associated with readmission independent of all risk scores (HR, 1.59 to 1.63; all p<0.01). Adding LTCI to all risk scores led to a significantly improved reclassification, which was observed in the subgroup of patients with HF with preserved ejection fraction (≥50%) but not in the subgroup with reduced ejection fraction (<50%).

Conclusions

Possession of an LTCI certificate was independently associated with 1-year all-cause readmission after adjusting for validated clinical risk scores in patients with HF. Adding LTCI status significantly improved the model performance for readmission risk, particularly in patients with HF and preserved ejection fraction.

Palliative Care and Cardiovascular Disease and Stroke: A Policy Statement From the American Heart Association/American Stroke Association

The mission of the American Heart Association/American Stroke Association includes increasing access to high-quality, evidence-based care that improves patient outcomes such as health-related quality of life and is consistent with the patients’ values, preferences, and goals. Awareness of and access to palliative care interventions align with the American Heart Association/American Stroke Association mission. The purposes of this policy statement are to provide background on the importance of palliative care as it pertains to patients with advanced cardiovascular disease and stroke and their families and to make recommendations for policy decisions. Palliative care, defined as patient- and family-centered care that optimizes health-related quality of life by anticipating, preventing, and treating suffering, should be integrated into the care of all patients with advanced cardiovascular disease and stroke early in the disease trajectory. Palliative care focuses on communication, shared decision making about treatment options, advance care planning, and attention to physical, emotional, spiritual, and psychological distress with inclusion of the patient’s family and care system. Our policy recommendations address the following: reimbursement for comprehensive delivery of palliative care services for patients with advanced cardiovascular disease and stroke; strong payer-provider relationships that involve data sharing to identify patients in need of palliative care, identification of better care and payment models, and establishment of quality standards and outcome measurements; healthcare system policies for the provision of comprehensive palliative care services during hospitalization, including goals of care, treatment decisions, needs of family caregivers, and transition to other care settings; and health professional education in palliative care as part of licensure requirements.

Pathways to potentially preventable hospitalizations for diabetes and heart failure: a qualitative analysis of patient perspectives

BACKGROUND

Potentially preventable hospitalizations (PPH) for heart failure (HF) and diabetes mellitus (DM) cost the United States over $14 billion annually. Studies about PPH typically lack patient perspectives, especially across diverse racial/ethnic groups with known PPH health disparities.

METHODS

English-speaking individuals with a HF or DM-related PPH (n = 90) at the largest hospital in Hawai'i completed an in-person interview, including open-ended questions on precipitating factors to their PPH. Using the framework approach, two independent coders identified patient-reported factors and pathways to their PPH.

RESULTS

Seventy-two percent of respondents were under 65 years, 30 % were female, 90 % had health insurance, and 66 % had previously been hospitalized for the same problem. Patients' stories identified immediate, precipitating, and underlying reasons for the admission. Underlying background factors were critical to understanding why patients had the acute problems necessitating their hospitalizations. Six, non-exclusive, underlying factors included: extreme social vulnerability (e.g., homeless, poverty, no social support, reported by 54 % of respondents); health system interaction issues (e.g., poor communication with providers, 44 %); limited health-related knowledge (42 %); behavioral health issues (e.g., substance abuse, mental illness, 36 %); denial of illness (27 %); and practical problems (e.g., too busy, 6 %). From these findings, we developed a model to understand an individual's pathways to a PPH through immediate, precipitating, and underlying factors, which could help identify potential intervention foci. We demonstrate the model's utility using five examples.

CONCLUSIONS

In a young, predominately insured population, factors well outside the traditional purview of the hospital, or even clinical medicine, critically influenced many PPH. Patient perspectives were vital to understanding this issue. Innovative partnerships and policies should address these issues, including linkages to social services and behavioral health.

The Tosca Registry: An Ongoing, Observational, Multicenter Registry for Chronic Heart Failure

The ageing of the population in western countries, the continuous increase of the prevalence of chronic diseases, the frequent coexistence of several morbid conditions (comorbidity) requires health professionals and Institutions to face difficult challenges, including increasing costs, need for more effective and sustainable therapies, and organizational issues. The European Innovation Partnership on Active and Healthy Ageing aims at enabling European citizens to lead healthy, active and independent lives while ageing. We herein discuss some key concepts bearing a special significance in the light of the Partnership aims, and present research and educational projects active in our local environment. Among these, the multicentre project TOSCA (Trattamento Ormonale nello Scompenso CArdiaco) that, although primarily focused on the understanding of the interactions between hormones and chronic heart failure (CHF), is also aimed at developing more effective models of clinical care. We provide the scientific background and current stage of the project. In the context of a growing complexity of the patients' clinical management, the polipharmacy is a new arising challenge for clinicians, bearing direct economic, organizational and clinical implications. A better understanding, characterization and management of this issue represent an additional target of the TOSCA network.

Discharge Planning and Hospital Readmissions

This study examines the association between the quality of hospital discharge planning and all-cause 30-day readmissions and same-hospital readmissions. The sample included adults aged 18 years and older hospitalized in 16 states in 2010 or 2011 for acute myocardial infarction, heart failure, pneumonia, or total hip or joint arthroplasty. Data from the Hospital Consumer Assessment of Healthcare Providers and Systems measured discharge-planning quality at the hospital level. A generalized linear mixed model was used to estimate the contribution of patient and hospital characteristics to 30-day all-cause and same-hospital readmissions. Discharge-planning quality was associated with (a) lower rates of 30-day hospital readmissions and (b) higher rates of same-hospital readmissions for heart failure, pneumonia, and total hip or joint replacement. These results suggest that by improving inpatient discharge planning, hospitals may be able to influence their 30-day readmissions and increase the likelihood that readmissions will be to the same hospital.

Thirty-Day Readmission Predicts 1-Year Mortality in Acute Pancreatitis

OBJECTIVES

There is limited knowledge of the prognostic indicators after hospital discharge after acute pancreatitis (AP). The aim was to determine risk factors for mortality after discharge in patients admitted with AP.

METHODS

A retrospective cohort study was conducted, including consecutive patients with AP admitted to the Cleveland Clinic between 2007 and 2011. Clinical data, mortality status, and the date of death were collected. Univariable and multivariable Cox regression was performed to determine variables significantly associated with mortality within a year of discharge.

RESULTS

Three hundred thirty-one patients were included in the study, current to July 2012. After a mean follow-up of 20 months, 41 subjects (12.4%) died after discharge from the hospital. Thirty-three (10.0%) died within a year after discharge. In univariable analyses, higher Charlson Comorbidity Index, blood urea nitrogen > 20 on admission, higher Bedside Index of Severity in Acute Pancreatitis scores, longer length of stay, and readmission within 30 days were associated with a higher hazard of mortality. In the multivariable analysis, subjects who were readmitted within 30 days had a 4.5 times higher hazard of dying within a year than those who were not readmitted (hazard ratio, 4.5; 95% confidence interval, 2.2-9.1).

CONCLUSION

A higher Charlson Comorbidity Index, early readmission, and longer hospitalization predict a higher 1-year mortality after AP.

Nurse-Led Multidisciplinary Heart Failure Group Clinic Appointments: Methods, Materials, and Outcomes Used in the Clinical Trial

BACKGROUND

The Self-management and Care of Heart Failure through Group Clinics Trial evaluated the effects of multidisciplinary group clinic appointments on self-care skills and rehospitalizations in high-risk heart failure (HF) patients.

OBJECTIVE

The purpose of this article is to (1) describe key Self-management and Care of Heart Failure through Group Clinics Trial group clinic interactive learning strategies, (2) describe resources and materials used in the group clinic appointment, and (3) present results supporting this patient-centered group intervention.

METHODS

This clinical trial included 198 HF patients (randomized to either group clinical appointments or to standard care). Data were collected from 72 group clinic appointments via patients' (1) group clinic session evaluations, (2) HF self-care behaviors skills, (3) HF-related discouragement and quality of life scores, and (4) HF-related reshopitalizations during the 12-month follow-up. Also, the costs of delivery of the group clinical appointments were tabulated.

RESULTS

Overall, patients rated group appointments as 4.8 of 5 on the "helpfulness" in managing HF score. The statistical model showed a 33% decrease in the rate of rehospitalizations (incidence rate ratio, 0.67) associated with the intervention over the 12-month follow-up period when compared with control patients (χ(2)1=3.9, P=.04). The total cost for implementing 5 group appointments was $243.58 per patient.

CONCLUSION

The intervention was associated with improvements in HF self-care knowledge and home care behavior skills and managing their for HF care. In turn, better self-care was associated with reductions in HF-related hospitalizations.

Identifying risk factors and patterns for unplanned readmission to a general medical service

OBJECTIVE

To identify factors and patterns associated with 7- and 28-day readmission for general medicine patients at a tertiary public hospital.

METHODS

A retrospective observational study was conducted using an administrative database at a general medicine service in a tertiary public hospital between 1 January 2007 and 31 December 2011. Demographic and clinical factors, as well as readmission patterns, were evaluated for the association with 7- and 28-day readmission.

RESULTS

The study cohort included 13 802 patients and the 28-day readmission rate was 10.9%. In multivariate analysis, longer hospital stay of the index admission (adjusted relative risk (ARR) 1.34), Charlson index ≥ 3 (ARR 1.28), discharge against medical advice (ARR 1.87), active malignancy (ARR 1.83), cardiac failure (ARR 1.48) and incomplete discharge summaries (ARR 1.61) were independently associated with increased risk of 28-day readmission. Patients with diseases of the respiratory system, neurological or genitourinary disease, injury and unclassifiable conditions were likely to be readmitted within 7 days. Patients with circulatory and respiratory disease were likely to be readmitted with the same system diagnosis.

CONCLUSION

Readmission of general medicine patients within 28 days is relatively common and is associated with clinical factors and patterns. Identification of these risk factors and patterns will enable the interventions to reduce potentially preventable readmissions.

Electronic medical record-based multicondition models to predict the risk of 30 day readmission or death among adult medicine patients: validation and comparison to existing models

Background

There is increasing interest in using prediction models to identify patients at risk of readmission or death after hospital discharge, but existing models have significant limitations. Electronic medical record (EMR) based models that can be used to predict risk on multiple disease conditions among a wide range of patient demographics early in the hospitalization are needed. The objective of this study was to evaluate the degree to which EMR-based risk models for 30-day readmission or mortality accurately identify high risk patients and to compare these models with published claims-based models.

Methods

Data were analyzed from all consecutive adult patients admitted to internal medicine services at 7 large hospitals belonging to 3 health systems in Dallas/Fort Worth between November 2009 and October 2010 and split randomly into derivation and validation cohorts. Performance of the model was evaluated against the Canadian LACE mortality or readmission model and the Centers for Medicare and Medicaid Services (CMS) Hospital Wide Readmission model.

Results

Among the 39,604 adults hospitalized for a broad range of medical reasons, 2.8 % of patients died, 12.7 % were readmitted, and 14.7 % were readmitted or died within 30 days after discharge. The electronic multicondition models for the composite outcome of 30-day mortality or readmission had good discrimination using data available within 24 h of admission (C statistic 0.69; 95 % CI, 0.68-0.70), or at discharge (0.71; 95 % CI, 0.70-0.72), and were significantly better than the LACE model (0.65; 95 % CI, 0.64-0.66; P =0.02) with significant NRI (0.16) and IDI (0.039, 95 % CI, 0.035-0.044). The electronic multicondition model for 30-day readmission alone had good discrimination using data available within 24 h of admission (C statistic 0.66; 95 % CI, 0.65-0.67) or at discharge (0.68; 95 % CI, 0.67-0.69), and performed significantly better than the CMS model (0.61; 95 % CI, 0.59-0.62; P < 0.01) with significant NRI (0.20) and IDI (0.037, 95 % CI, 0.033-0.041).

Conclusions

A new electronic multicondition model based on information derived from the EMR predicted mortality and readmission at 30 days, and was superior to previously published claims-based models.

Electronic supplementary material

The online version of this article (doi:10.1186/s12911-015-0162-6) contains supplementary material, which is available to authorized users.

Advanced (stage D) heart failure: a statement from the Heart Failure Society of America Guidelines Committee

We propose that stage D advanced heart failure be defined as the presence of progressive and/or persistent severe signs and symptoms of heart failure despite optimized medical, surgical, and device therapy. Importantly, the progressive decline should be primarily driven by the heart failure syndrome. Formally defining advanced heart failure and specifying when medical and device therapies have failed is challenging, but signs and symptoms, hemodynamics, exercise testing, biomarkers, and risk prediction models are useful in this process. Identification of patients in stage D is a clinically important task because treatments are inherently limited, morbidity is typically progressive, and survival is often short. Age, frailty, and psychosocial issues affect both outcomes and selection of therapy for stage D patients. Heart transplant and mechanical circulatory support devices are potential treatment options in select patients. In addition to considering indications, contraindications, clinical status, and comorbidities, treatment selection for stage D patients involves incorporating the patient's wishes for survival versus quality of life, and palliative and hospice care should be integrated into care plans. More research is needed to determine optimal strategies for patient selection and medical decision making, with the ultimate goal of improving clinical and patient centered outcomes in patients with stage D heart failure.

Family member accompaniment to routine medical visits is associated with better self-care in heart failure patients

OBJECTIVES

To examine the association between frequency of family member accompaniment to medical visits and heart failure (HF) self-care maintenance and management and to determine whether associations are mediated through satisfaction with provider communication.

METHODS

Cross-sectional survey of 150 HF patients seen in outpatient clinics. HF self-care maintenance and management were assessed using the Self-Care of Heart Failure Index. Satisfaction with provider communication was assessed using a single question originally included in the American Board of Internal Medicine Patient Satisfaction Questionnaire. Frequency of family member accompaniment to visits was assessed using a single-item question. We performed regression analyses to examine associations between frequency of accompaniment and outcomes. Mediation analysis was conducted using MacKinnon's criteria.

RESULTS

Overall, 61% reported accompaniment by family members to some/most/every visit. Accompaniment to some/most/every visit was associated with higher self-care maintenance (β = 6.4, SE 2.5; p = 0.01) and management (β = 12.7, SE 4.9; p = 0.01) scores. Satisfaction with provider communication may mediate the association between greater frequency of accompaniment to visits and self-care maintenance (1.092; p = 0.06) and self-care management (1.428; p = 0.13).

DISCUSSION

Accompaniment to medical visits is associated with better HF self-care maintenance and management, and this effect may be mediated through satisfaction with provider communication.

Steps forward in regulatory pathways for acute and chronic heart failure

A workshop was organized by the Agenzia Italiana del Farmaco (AIFA) to discuss unmet needs and ways forward in the development of medicines in heart failure, their rationale, and cost-effective use. An integrated, multidisciplinary approach, including patients' needs and perspectives, was advocated by all the participants as the way to the most effective treatment regimens. More work is needed for reaching consensus on clinical and functional endpoints, for validating patient reported outcomes and measurements of well-being. Similarly, the integration into the clinical programmes of the health technology assessment/payers perspective, in particular, the evaluation of 'real-life' treatment effectiveness and of health as a value, would help in shifting the development and authorization of medicines from the molecule paradigm to their evaluation in the context of the whole health care regimen. Through this kind of workshop, AIFA is trying to build a template for meetings devoted to debate unmet needs with all stakeholders towards tentative road maps for the future.

Symptom perceptions and self-care behaviors in patients who self-manage heart failure

BACKGROUND

Patients with heart failure (HF) are at heightened risk for acute exacerbation requiring hospitalization. Although timely reporting of symptoms can expedite outpatient treatment and avoid the need for hospitalization, few patients recognize and respond to symptoms until acutely ill.

OBJECTIVE

The purpose of this study was to explore patients' perceptions of symptoms and self-care behaviors for symptom relief, leading up to a HF hospitalization.

METHODS

To examine prehospitalization symptom scenarios, semistructured interviews were conducted with 60 patients hospitalized for acute decompensated HF.

RESULTS

Thirty-seven patients (61.7%) said that they had a sense that "something just wasn't quite right" before their symptoms began but were unable to specify further. Signs and symptoms most often recognized by the patients were related to dyspnea (85%), fatigue (53.3%), and edema (41.7%). Few patients interpreted their symptoms as being related to worsening HF and most often attributed symptoms to changes in diet (18.3%) and medications (13.3%). Twenty-six patients (43.3%) used self-care strategies to relieve symptoms before hospital admission. More than 40% of the patients had symptoms at least 2 weeks before hospitalization.

CONCLUSIONS

Despite the wide dissemination of HF evidence-based guidelines, important components of symptom self-management remain suboptimal. Because most of HF self-management occurs in the postdischarge environment, research is needed that identifies how patients interpret symptoms of HF in the specific contexts in which patients self-manage their HF. These findings suggest the need for interventions that will help patients expeditiously recognize, accurately interpret, and use appropriate and safe self-care strategies for symptoms.

Strategies to Reduce 30-Day Readmissions in Older Patients Hospitalized with Heart Failure and Acute Myocardial Infarction

Readmission within 30 days after hospital discharge for common cardiovascular conditions such as heart failure and acute myocardial infarction is extremely common among older persons. To incentivize investment in reducing preventable rehospitalizations, the United States federal government has directed increasing financial penalties to hospitals with higher-than-expected 30-day readmission rates. Uncertainty exists, however, regarding the best approaches to reducing these adverse outcomes. In this review, we summarize the literature on predictors of 30-day readmission, the utility of risk prediction models, and strategies to reduce short-term readmission after hospitalization for heart failure and acute myocardial infarction. We report that few variables have been found to consistently predict the occurrence of 30-day readmission and that risk prediction models lack strong discriminative ability. We additionally report that the literature on interventions to reduce 30-day rehospitalization has significant limitations due to heterogeneity, susceptibility to bias, and lack of reporting on important contextual factors and details of program implementation. New information is characterizing the period after hospitalization as a time of high generalized risk, which has been termed the post-hospital syndrome. This framework for characterizing inherent post-discharge instability suggests new approaches to reducing readmissions.

Associations Between Anticoagulation Therapy and Risks of Mortality and Readmission Among Patients With Heart Failure and Atrial Fibrillation

Background—

Patients with heart failure and atrial fibrillation are at higher risk of thromboembolic events than patients with heart failure alone. Yet, the use of anticoagulation therapy varies in clinical practice, especially among older patients, for whom its effectiveness is poorly understood.

Methods and Results—

Using clinical registry data linked to Medicare claims from 2005 to 2011, we examined outcomes of older patients hospitalized with heart failure and atrial fibrillation who newly initiated anticoagulation therapy at discharge. We used Cox proportional hazards models and inverse probability-weighted treatment estimates to adjust for selection bias. Main outcomes were mortality and readmission at 1 and 3 years. Among 5105 patients in 195 hospitals, 1623 (31.8%) started anticoagulation therapy at discharge. Treated patients had lower unadjusted rates of all-cause mortality (26.4% versus 42.8%; P <0.001) and all-cause readmission (58.4% versus 63.7%; P <0.001) at 1 year. After inverse weighting for the probability of treatment and adjustment for other discharge medications, anticoagulation therapy was associated with significantly lower 1-year mortality (hazard ratio, 0.70; 99% confidence interval, 0.59–0.82), but there was no statistically significant difference in the risk of all-cause readmission (hazard ratio, 0.89; 99% confidence interval, 0.78–1.01) or other readmission outcomes. Results were similar at 3 years.

Conclusions—

Initiation of anticoagulation therapy at hospital discharge was associated with improved mortality at 1 and 3 years but was not associated with improved cardiovascular readmission among older patients with heart failure and atrial fibrillation.

The effect of Massachusetts health reform on 30 day hospital readmissions: retrospective analysis of hospital episode statistics

OBJECTIVES

To analyse changes in overall readmission rates and disparities in such rates, among patients aged 18-64 (those most likely to have been affected by reform), using all payer inpatient discharge databases (hospital episode statistics) from Massachusetts and two control states (New York and New Jersey).

DESIGN

Difference in differences analysis to identify the post-reform change, adjusted for secular changes unrelated to reform.

SETTING

US hospitals in Massachusetts, New York, and New Jersey.

PARTICIPANTS

Adults aged 18-64 admitted for any cause, excluding obstetrical.

MAIN OUTCOME MEASURE

Readmissions at 30 days after an index admission.

RESULTS

After adjustment for known confounders, including age, sex, comorbidity, hospital ownership, teaching hospital status, and nurse to census ratio, the odds of all cause readmission in Massachusetts was slightly increased compared with control states post-reform (odds ratio 1.02, 95% confidence interval 1.01 to 1.04, P<0.05). Racial and ethnic disparities in all cause readmission rates did not change in Massachusetts compared with control states. In analyses limited to Massachusetts only, there were minimal overall differences in changes in readmission rates between counties with differing baseline uninsurance rates, but black people in counties with the highest uninsurance rates had decreased odds of readmission (0.91, 0.84 to 1.00) compared with black people in counties with lower uninsurance rates. Similarly, white people in counties with the highest uninsurance rates had decreased odds of readmission (0.96, 0.94 to 0.99) compared with white people in counties with lower uninsurance rates.

CONCLUSIONS

In the United States, and in Massachusetts in particular, extending health insurance coverage alone seems insufficient to improve readmission rates. Additional efforts are needed to reduce hospital readmissions and disparities in this outcome.