Patient Characteristics Predicting Readmission Among Individuals Hospitalized for Heart Failure

Prognostic factors of readmission and mortality after first heart failure hospitalization: results from EPICAL2 cohort

AIMS

We aimed to identify prognostic individual factors in patients with first acute heart failure (HF) hospitalization, considering both death and readmission as part of the natural history of HF.

METHODS AND RESULTS

We used data from the observational, prospective, multicentre EPICAL2 cohort study from which we selected incident cases of acute HF alive at discharge. We relied on an illness-death model to identify prognostic factors on first readmission and on mortality before and after readmission. In 451 patients hospitalized for first acute HF, we observed within the year after discharge, 23 (5.1%) deaths before readmission and 270 (59.9%) first readmissions, of which 60 (22.2%) were followed by death of any cause. First, among patient characteristics, only Charlson index ≥ 8 was associated with first readmission [adjusted hazard ratio (aHR) = 1.6, 95% confidence interval (CI) (1.1-2.3), P = 0.011]. Second, Charlson index ≥ 8 [aHR = 4.2, 95% CI (1.2-14.8), P = 0.025], low blood pressure (BP) [aHR = 12.2, 95% CI (1.9-79.6), P = 0.009], high BP [aHR = 6.9, 95% CI (1.3-36.4), P = 0.023], and prescription of recommended dual or triple HF therapy at index discharge [aHR = 0.2, 95% CI (0.1-0.7), P = 0.014] were associated with mortality before any readmission. Third, Charlson index ≥ 8 [aHR = 2.4, 95% CI (1.1-5.6), P = 0.037] and the time to first readmission (per 30 days additional) [aHR = 1.2; 95% CI (1.1-1.4), P = 0.007] were associated with mortality after readmission.

CONCLUSIONS

Regardless of the prognostic state considered, we showed that comorbidities are of critical prognostic value in a real-world cohort of incident HF cases. This argues in favour of multidisciplinary care in HF.

Nurse-led heart failure educational interventions for patient and informal caregiver dyads: An integrative review

BACKGROUND

Heart failure is a major health problem with significant economic burden in the United States. Educating heart failure dyads (heart failure patient and informal caregiver) is a relatively new domain and is being proposed by providers, policy makers, and third-party payors. Nurse-led dyad education can improve quality of life and reduce hospital admissions in the heart failure population.

OBJECTIVES

This integrative literature review focused on evaluating design, delivery content, and outcomes of nurse-led dyadic educational interventions.

METHODS

PubMed, CINAHL, Cochrane, and Google Scholar databases (1999 -2022) were searched for quantitative and qualitative studies that included these search terms: heart failure, dyads, nonmedical caregivers, caregivers, randomized controlled trials, nurse-led education, education.

RESULTS

The search yielded 92 articles. The results included seven randomized controlled trials and one pilot study conducted from 2005 to 2017. Sample sizes ranged from 20 to 155 dyads. Dyads who received education interventions had positive outcomes. Face-to-face coaching provided stronger outcomes. Interventions varied in length from baseline to three months, with post-intervention follow-ups from one to 12 months.

CONCLUSIONS

A paucity of studies of nurse-led heart failure dyadic educational interventions have been reported in the literature. To advance the science and decrease heart failure readmissions, greater efforts to study and incorporate education and support for heart failure dyads is needed, along with assessment of both patient and caregiver outcomes.

Socioeconomic and Health-Related Factors Affecting Congestive Heart Failure Readmissions

Congestive heart failure (CHF) readmissions are frequent and costly but preventable. The purpose of this study was to analyze socioeconomic and health-related factors of CHF readmissions by examining the relationship between 30-day readmissions of individuals with CHF and their payer status, race, ethnicity, primary language spoken, living arrangement, and comorbidities. This retrospective case-control study used secondary data from 450 CHF patients admitted to a not-for-profit Northern Virginia hospital from July 2014 to December 2017. Data were analyzed using χ 2 and logistic regression. Living arrangements and comorbid chronic renal failure (CRF) were statistically significant predictors of CHF readmissions; all other factors were nonsignificant. Patients who lived with family and those in assisted living facilities were less likely to be readmitted than those who lived alone (odds ratio [OR] = 0.2 and 0.5, respectively). Patients without CRF were less likely to be readmitted than those who had CRF (OR = 0.6). This study contributes data to inform community-based health programs tailored toward frequently readmitted individuals due to CHF exacerbation.

Fever and hypothermia do not affect the all-cause 30-day hospital readmission

BACKGROUND

One of the goals of the Affordable Care Act is to decrease hospital readmissions. While widely adhered to, there is no published research to support the practice of delaying discharge if patients exhibit fever or hypothermia in the preceding 24 h, which is the focus of our study.

METHODS

Retrospective analysis of the minimal (Tmin) and maximal (Tmax) body temperatures collected during the last 24 h before discharge of 19,038 inpatients. Fever was defined as Tmax >99.5F (+1SD from the mean Tmax) or >100.2F (+2SDs), and hypothermia as Tmin <97.1F (-1SD from the mean Tmin) or <96.7F (-2SDs).

RESULTS

The overall readmission rate was 10.2% (highest for General Medicine and Pediatrics). The rate of readmission was not different between normothermic patients and those with abnormal body temperature, except for higher readmission rate (12.2%) for patients with fever at 1SD from Tmax compared with normothermic patients (9.96%). Neither fever nor hypothermia was associated with shorter time to readmission, except for fever at 2 SDs from Tmax (10.6 days) compared with normothermic patients (12.6 days). Surprisingly, univariate analysis revealed that higher Tmax and older age were associated with lower readmission probability. Both uni- and multivariate analysis showed that the presence of fever is associated with lower readmission probability. Evaluating 200 individual cases, the most common explanation for body temperature abnormality was infection and 90% of the preventable readmissions were due to infection.

CONCLUSIONS

Abnormal body temperature 24 h prior to discharge was not useful for predicting the probability of readmission.

Clinical and Demographic Profiles of Home Care Patients With Alzheimer's Disease and Related Dementias: Implications for Information Transfer Across Care Settings

Home health care (HHC) clinicians serving individuals with Alzheimer's disease and related dementias (ADRD) do not always have information about the person's ADRD diagnosis, which may be used to improve the HHC plan of care. This retrospective cohort study examined characteristics of 56,652 HHC patients with varied documentation of ADRD diagnoses. Data included clinical assessments and Medicare claims for a 6-month look-back period and 4-year follow-up. Nearly half the sample had an ADRD diagnosis observed in the claims either prior to or following the HHC admission. Among those with a prior diagnosis, 63% did not have it documented on the HHC assessment; the diagnosis may not have been known to the HHC team or incorporated into the care plan. Patients with ADRD had heightened risk for adverse outcomes (e.g., urinary tract infection and aspiration pneumonia). Interoperable data across health care settings should include ADRD-specific elements about diagnoses, symptoms, and risk factors.

[Differences in epaAC© in heart failure patients with or without readmission: A retrospective case-control study]

Differences in epaAC© in heart failure patients with or without readmission: a retrospective case-control study Abstract. Background: Heart failure is one of the most frequent reasons for hospitalization in elderly people. In heart failure, approximately 22.8 % of hospitalised patients are rehospitalised within 30 days. The nursing assessment tool epaAC could provide information on risk factors for readmission. Aim: The aim of this study was to identify possible group differences in the items and scores of the epaAC discharge assessment with regard to the endpoint of unplanned readmissions within 30 days after discharge from index-hospitalisation. Methods: Using a retrospective case-control design, differences in the epaAC variables were investigated by descriptive and comparative statistics. Chi-square test, Wilcoxon test and t-test were performed with two-sided alpha level α < 0.05. Alpha error accumulation was accounted for by Benjamini & Hochberg correction. Results: No significant group differences were found in all items and scores of the discharge epaAC. There is only weak evidence that the presence of acute respiratory impairment at time of discharge is higher in the patient with rehospitalisation than in those without rehospitalisation. Conclusions: The items and scores of the nursing assessment instrument epaAC did not significantly differ between patients with or without 30-days readmission. Further exploration to assess the epaAC's potential to predict rehospitalisation in heart failure is needed.

Prediction models for hospital readmissions in patients with heart disease: a systematic review and meta-analysis

OBJECTIVE

To describe the discrimination and calibration of clinical prediction models, identify characteristics that contribute to better predictions and investigate predictors that are associated with unplanned hospital readmissions.

DESIGN

Systematic review and meta-analysis.

DATA SOURCE

Medline, EMBASE, ICTPR (for study protocols) and Web of Science (for conference proceedings) were searched up to 25 August 2020.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Studies were eligible if they reported on (1) hospitalised adult patients with acute heart disease; (2) a clinical presentation of prediction models with c-statistic; (3) unplanned hospital readmission within 6 months.

PRIMARY AND SECONDARY OUTCOME MEASURES

Model discrimination for unplanned hospital readmission within 6 months measured using concordance (c) statistics and model calibration. Meta-regression and subgroup analyses were performed to investigate predefined sources of heterogeneity. Outcome measures from models reported in multiple independent cohorts and similarly defined risk predictors were pooled.

RESULTS

Sixty studies describing 81 models were included: 43 models were newly developed, and 38 were externally validated. Included populations were mainly patients with heart failure (HF) (n=29). The average age ranged between 56.5 and 84 years. The incidence of readmission ranged from 3% to 43%. Risk of bias (RoB) was high in almost all studies. The c-statistic was <0.7 in 72 models, between 0.7 and 0.8 in 16 models and >0.8 in 5 models. The study population, data source and number of predictors were significant moderators for the discrimination. Calibration was reported for 27 models. Only the GRACE (Global Registration of Acute Coronary Events) score had adequate discrimination in independent cohorts (0.78, 95% CI 0.63 to 0.86). Eighteen predictors were pooled.

CONCLUSION

Some promising models require updating and validation before use in clinical practice. The lack of independent validation studies, high RoB and low consistency in measured predictors limit their applicability.

PROSPERO REGISTRATION NUMBER

CRD42020159839.

Systolic blood pressure at admission and long-term clinical outcomes in patients hospitalized for heart failure

Aims

The study sought to investigate the association between admission systolic blood pressure (SBP) and 1‐year clinical outcomes in patients hospitalized for heart failure (HF) and in subgroups.

Methods

This study was based on the China Patient‐centred Evaluative Assessment of Cardiac Events Prospective Heart Failure Study, which prospectively enrolled patients hospitalized for HF in 52 hospitals from 20 provinces in China between August 2016 and May 2018. Patients were divided into four groups according to the quartiles of SBP at admission. The multivariable Cox proportional hazards regression models were fitted to examine the association between admission SBP and all‐cause death and HF readmission within 1 year after the index hospitalization. Restricted cubic splines were used to explore the non‐linear association between SBP and the clinical outcomes.

Results

Among 4896 patients, those with lower admission SBP were younger, more likely to be male, have left ventricular ejection fraction <40%, and receive β‐blockers, aldosterone antagonists, and diuretics. After adjustment for potential confounders, lower admission SBP was significantly associated with higher all‐cause death and there is no threshold, while we only observed such an association with HF readmission when admission SBP was lower than 120 mmHg. Compared with the 4th SBP quartile, patients in the 1st SBP quartile had higher risk of all‐cause death (hazard ratio, 1.85; 95% confidence interval 1.48–2.33; P < 0.001) and HF readmission (hazard ratio, 1.40; 95% confidence interval 1.19–1.65, P < 0.001). These associations were consistent in most subgroups, such as age, sex, and left ventricular ejection fraction.

Conclusions

In patients hospitalized for HF, lower admission SBP portends an increased risk of 1 year all‐cause death and HF readmission, and these associations were consistent among subgroups.

Frailty and Function in Heart Failure: Predictors of 30-Day Hospital Readmission?

BACKGROUND AND PURPOSE

Although there have been decreases noted in 30-day readmission rates for persons with heart failure since enactment of the Hospital Readmissions Reduction Program, costs related to heart failure readmissions remain high. Consequently, there is a need to better identify persons with heart failure who are at risk for 30-day hospital readmission. Therefore, this study aimed to compare the ability of measures of function and frailty to predict 30-day hospital readmissions for adults 65 years and older with heart failure.

METHODS

Secondary data analysis using the 2011 National Health and Aging Trends Study analysis merged with Medicare claims data. Logistic regression modeling was used to compare the ability of function (Short Physical Performance Battery) and frailty (Fried's Physical Frailty Phenotype) to predict 30-day readmission. Receiver operating characteristic curves were constructed to examine the ability of function and frailty to identify those who were readmitted.

RESULTS AND DISCUSSION

Frailty and function demonstrated comparable ability to predict 30-day readmissions (R2 = 0.087 and R2 = 0.087, respectively). Neither measure identified persons at risk for readmission (AUCSPPB = 0.608; AUCPFP = 0.587).

CONCLUSIONS

Functional assessment demonstrated comparable ability to predict 30-day readmissions in persons with heart failure compared with frailty. However, neither measure was able to identify persons at high risk for readmission. Although frailty status is emphasized in research for older adults with heart failure, functional status is an important patient-level factor associated with readmission.

Readmitted Patients With Heart Failure Sick, Tired, and Symptomatic: A Qualitative Descriptive Study From a Quaternary Academic Medical Center

BACKGROUND AND OBJECTIVE

Heart failure (HF) readmissions will continue to grow unless we have a better understanding of why patients with HF are readmitted. Our purpose was to gain an understanding, from the patients' perspective, of how patients with HF viewed their discharge instructions and how they felt when they got home and were then readmitted in less than 30 days.

METHODS AND RESULTS

We used a qualitative descriptive approach using semistructured interviews with 22 patients with HF. Most participants had multimorbidities, were classified as New York Heart Association class III (n = 13) with reduced ejection fraction (n = 20), and were on home inotrope therapy (n = 13). The overarching theme that emerged was that these participants were sick, tired, and symptomatic. Additional categories within this theme highlight discharge instructions as being clear and easily understood; rich descriptions of physical, emotional, and other symptoms leading up to readmission; and reports of daily activities including what "good" and "not good" days looked like. Moreover, when participants experienced an exacerbation of their HF symptoms, they were sick enough to be readmitted to the hospital.

CONCLUSION

Our findings confirm ongoing challenges with a complex group of sick patients with HF, with the majority on home inotropes with reduced ejection fraction, who developed an unavoidable progression of their illness and subsequent hospital readmission.

Development and Validation of a Nomogram to Predict the 180-Day Readmission Risk for Chronic Heart Failure: A Multicenter Prospective Study

Background: The existing prediction models lack the generalized applicability for chronic heart failure (CHF) readmission. We aimed to develop and validate a widely applicable nomogram for the prediction of 180-day readmission to the patients. Methods: We prospectively enrolled 2,980 consecutive patients with CHF from two hospitals. A nomogram was created to predict 180-day readmission based on the selected variables. The patients were divided into three datasets for development, internal validation, and external validation (mean age: 74.2 ± 14.1, 73.8 ± 14.2, and 71.0 ± 11.7 years, respectively; sex: 50.2, 48.8, and 55.2% male, respectively). At baseline, 102 variables were submitted to the least absolute shrinkage and selection operator (Lasso) regression algorithm for variable selection. The selected variables were processed by the multivariable Cox proportional hazards regression modeling combined with univariate analysis and stepwise regression. The model was evaluated by the concordance index (C-index) and calibration plot. Finally, the nomogram was provided to visualize the results. The improvement in the regression model was calculated by the net reclassification index (NRI) (with tenfold cross-validation and 200 bootstraps). Results: Among the selected 2,980 patients, 1,696 (56.9%) were readmitted within 180 days, and 1,502 (50.4%) were men. A nomogram was established by the results of Lasso regression, univariate analysis, stepwise regression and multivariate Cox regression, as well as variables with clinical significance. The values of the C-index were 0.75 [95% confidence interval (CI): 0.72-0.79], 0.75 [95% CI: 0.69-0.81], and 0.73 [95% CI: 0.64-0.83] for the development, internal validation, and external validation datasets, respectively. Calibration plots were provided for both the internal and external validation sets. Five variables including history of acute heart failure, emergency department visit, age, blood urea nitrogen level, and beta blocker usage were considered in the final prediction model. When adding variables involving hospital discharge way, alcohol taken and left bundle branch block, the calculated values of NRI demonstrated no significant improvements. Conclusions: A nomogram for the prediction of 180-day readmission of patients with CHF was developed and validated based on five variables. The proposed methodology can improve the accurate prediction of patient readmission and have the wide applications for CHF.

Incorporating home healthcare nurses' admission information needs to inform data standards

OBJECTIVE

Patient transitions into home health care (HHC) often occur without the transfer of information needed for critical clinical decisions and the plan of care. Owing to a lack of universally implemented standards, there is wide variation in information transfer. We sought to characterize missing information at HHC admission.

MATERIALS AND METHODS

We conducted a mixed methods study with 3 diverse HHC agencies. Focus groups with nurses at each agency identified what information supports patient care decisions at admission. Thirty-six in-home admissions with associated documentation review determined the available information. To inform information standards development for the HHC admission process, we compared the types of information desired and available to an international standard for transitions in care information, the Continuity of Care Document (CCD) enhanced with Office of the National Coordinator for Healthcare Information Technology summary terms (CCD/S).

RESULTS

Three-quarters of the items from the focus groups mapped to the CCD/S. Regarding available information at admission, no observation included all CCD/S data items. While medication information was needed and often available for 4 important decisions, concepts related to patient medication self-management appeared in neither the CCD/S nor the admission documentation.

DISCUSSION

The CCD/S mostly met HHC nurses' information needs and is recommended to begin to fill the current information gap. Electronic health record recommendations include use of a data standard: the CCD or the proposed, more parsimonious U.S. Core Data for Interoperability.

CONCLUSIONS

Referral source and HHC agency adoption of data standards is recommended to support structured, consistent data and information sharing.

Clinical Characteristics and Factors Associated with Heart Failure Readmission at a Tertiary Hospital in North-Eastern Tanzania

INTRODUCTION

Heart failure (HF) is characterized by frequent episodes of decompensation, leading to a high hospitalization burden. More than 50% of index hospitalizations for HF patients return within 6 months of discharge. Once the patient is readmitted, the risk of further disease progression and the mortality rate are increased. A lot of patients are readmitted due to factors such as poor medication adherence, infections, or worsening comorbidities. The aim of our study was to identify the inpatient burden of HF readmission and to identify the factors associated with early readmission.

METHODS

A hospital-based cross-sectional analytical study was conducted from November 2018 to April 2019 within the medical wards at Kilimanjaro Christian Medical Centre (KCMC), which is a teaching and referral hospital in north-eastern Tanzania. The study population included all patients with HF admitted within the medical ward. Data were collected using questionnaires and blood and radiological investigations, and analysis was done using Statistical Package for Social Science (SPSS) version 25. Chi-square test was used to compare proportions of categorical variables. Logistic regression was used to determine the likelihood for readmission, and p-value of <0.05 was considered to be statistically significant.

RESULTS

A total of 353 patients were identified with HF, of whom 136 (38.5%) had a previous admission. Of the 136 patients analysed, the mean age was 62.8 years (SD 17.1), and 86 (63.2%) were females. Within 30 days after discharge, 34 (25.0%) of the patients were readmissions. Factors for early readmission were unemployment (OR = 2.38, 95% CI = 1.02-5.54, p = 0.043), poor medication adherence (OR = 3.87, 95% CI = 1.67-8.97, p = 0.002), absence of angiotensin-converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB) (OR = 2.40, 95% CI = 1.09-5.31, p = 0.030), and pleural effusion (OR 3.25, 95% CI = 1.44-7.32, p = 0.004).

CONCLUSION

Heart failure is a burden due to a large number of admissions and readmissions. Factors such as poor medication adherence and absence of adequate HF therapy, especially the absence of regimes containing ACEI or ARB, need to be targeted to reduce the number of readmissions. This will help reduce the risk of further decompensations, disease progression, and mortality rate.

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.

Development of a predictive model of hospitalization in primary care patients with heart failure

BACKGROUND

Heart failure (HF) is the leading cause of hospitalization in people over age 65. Predictive hospital admission models have been developed to help reduce the number of these patients.

AIM

To develop and internally validate a model to predict hospital admission in one-year for any non-programmed cause in heart failure patients receiving primary care treatment.

DESIGN AND SETTING

Cohort study, prospective. Patients treated in family medicine clinics.

METHODS

Logistic regression analysis was used to estimate the association between the predictors and the outcome, i.e. unplanned hospitalization over a 12-month period. The predictive model was built in several steps. The initial examination included a set of 31 predictors. Bootstrapping was used for internal validation.

RESULTS

The study included 251 patients, 64 (25.5%) of whom were admitted to hospital for some unplanned cause over the 12 months following their date of inclusion in the study. Four predictive variables of hospitalization were identified: NYHA class III-IV, OR (95% CI) 2.46 (1.23-4.91); diabetes OR (95% CI) 1.94 (1.05-3.58); COPD OR (95% CI) 3.17 (1.45-6.94); MLHFQ Emotional OR (95% CI) 1.07 (1.02-1.12). AUC 0.723; R2N 0.17; Hosmer-Lemeshow 0.815. Internal validation AUC 0.706.; R2N 0.134.

CONCLUSION

This is a simple model to predict hospitalization over a 12-month period based on four variables: NYHA functional class, diabetes, COPD and the emotional dimension of the MLHFQ scale. It has an acceptable discriminative capacity enabling the identification of patients at risk of hospitalization.

What Predicts Health Care Transitions for Older Adults Following Introduction of LTSS?

Objective: To determine predictors of health care transitions (i.e., acute care service use, transfers from lower to higher intensity services) among older adults new to long-term services and supports [LTSS]. Method: 470 new LTSS recipients followed for 24 months. Multivariable Poisson regression modeling within a generalized estimating equation framework. Results: Being male, having multiple chronic conditions, lower self-reported physical health ratings and lower quality of life ratings at baseline were associated with increased risk of health care transitions. Older adults in assisted living communities and nursing homes experienced decreases in health care transitions over time, while LTSS recipients at home had no change in risk. LTSS recipients who had orders to receive therapy, compared with those who did not, had a lower relative risk of transitions over time. Discussion: Predictors of future health care transitions support the need for LTSS providers to anticipate and monitor this risk for LTSS recipients.

Differences in nutritional status and activities of daily living and mobility in elderly hospitalized patients with heart failure

Aims

This study aims to examine the effect of differences in nutritional status on activities of daily living (ADL) and mobility recovery of hospitalized elderly patients with heart failure (HF).

Methods and results

From among 377 consecutive HF patients who underwent rehabilitation at one acute‐care hospital from January 2013 to August 2015, those who were aged ≥ 65 years could walk with assistance before hospitalization and who were hospitalized for the first time were included in this retrospective cohort study. Exclusion criteria were pacemaker surgery during hospitalization, change to other departments, death during hospitalization, and unmeasured ADL. We investigated patient characteristics, basic attributes, Geriatric Nutritional Risk Index (GNRI), ADL [motor Functional Independence Measure (motor FIM)], and Rivermead Mobility Index (RMI). Of these 377 patients, 96 met the inclusion criteria and were divided into the low GNRI group (n = 38, 83.5 ± 8.3 years, 44.7% male) and high GNRI group (n = 58, 81.0 ± 6.6 years, 55.2%). Patient characteristics and the difference between motor ADL and motility recovery and nutrition data were analysed with unpaired t‐test, χ² test, and two‐way analysis of covariance. In comparing the two groups, the following parameters were significantly lower in the low GNRI group than in the high GNRI group: body mass index (18.7 ± 2.2 vs. 23.2 ± 2.7 kg/m², P < 0.01), albumin (3.4 ± 0.4 vs. 3.8 ± 0.4 g/dL, P < 0.01), diabetes mellitus ratio (21.1% vs. 50.0%, P < 0.01), RMI at discharge (6.8 ± 2.6 vs. 8.2 ± 2.2, P = 0.01), and motor FIM at discharge (67.2 ± 19.5 vs. 75.6 ± 13.3, P = 0.02). RMI showed a significant group and term main effect and interaction effect (P < 0.05). Motor FIM showed a significant main effect of group and term (P < 0.05), and no significant interaction effect.

Conclusions

Low nutritional status in hospitalized elderly HF patients affected their recovery of mobility but did not appear to affect the recovery of ADL.

Individual and Environmental Determinants of Provider Continuity Among Urban Older Adults With Heart Failure: A Retrospective Cohort Study

Objective: Continuity in patient–provider relationships is important to providing high-quality care for older adults with chronic conditions. We investigated individual and environmental determinants of provider continuity for office-based physician visits among urban older adults with heart failure. Method: We linked Medicare claims with data on neighborhood characteristics for a retrospective cohort of community-dwelling Medicare beneficiaries with heart failure in New York City (N = 50,475). Results: Mean continuity using the Bice–Boxerman index was 0.33 (SD = 0.22) (possible range of 0 [no continuity] to 1 [perfect continuity]). Multivariable regression indicated that provider continuity was higher among older, female, and dually eligible beneficiaries. Those with more chronic conditions had higher continuity, controlling for number of medical specialties seen. Continuity was lower for beneficiaries in neighborhoods with high median income and high primary care density. Conclusion: Individual and environmental predictors of provider continuity among urban older adults with heart failure could help to identify those at risk of care fragmentation.

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.

Race and Beta-Blocker Survival Benefit in Patients With Heart Failure: An Investigation of Self-Reported Race and Proportion of African Genetic Ancestry

Background

It remains unclear whether beta‐blockade is similarly effective in black patients with heart failure and reduced ejection fraction as in white patients, but self‐reported race is a complex social construct with both biological and environmental components. The objective of this study was to compare the reduction in mortality associated with beta‐blocker exposure in heart failure and reduced ejection fraction patients by both self‐reported race and by proportion African genetic ancestry.

Methods and Results

Insured patients with heart failure and reduced ejection fraction (n=1122) were included in a prospective registry at Henry Ford Health System. This included 575 self‐reported blacks (129 deaths, 22%) and 547 self‐reported whites (126 deaths, 23%) followed for a median 3.0 years. Beta‐blocker exposure (BBexp) was calculated from pharmacy claims, and the proportion of African genetic ancestry was determined from genome‐wide array data. Time‐dependent Cox proportional hazards regression was used to separately test the association of BBexp with all‐cause mortality by self‐reported race or by proportion of African genetic ancestry. Both sets of models were evaluated unadjusted and then adjusted for baseline risk factors and beta‐blocker propensity score. BBexp effect estimates were protective and of similar magnitude both by self‐reported race and by African genetic ancestry (adjusted hazard ratio=0.56 in blacks and adjusted hazard ratio=0.48 in whites). The tests for interactions with BBexp for both self‐reported race and for African genetic ancestry were not statistically significant in any model (P>0.1 for all).

Conclusions

Among black and white patients with heart failure and reduced ejection fraction, reduction in all‐cause mortality associated with BBexp was similar, regardless of self‐reported race or proportion African genetic ancestry.

Facilitating Focused Process Improvement Efforts in Home Health Agencies to Improve Utilization Outcomes Effectively and Efficiently

The aim of this study was to identify a smaller set of clinical practices most associated with the utilization outcomes of the home health agencies. A secondary data analysis approach was adopted using the publicly accessible Home Health Compare repository as the main data source; the control variables such as rurality, agency size, and median income levels were obtained from other public data repositories. Checking for fall risks and starting care in a timely manner were most associated with hospital readmissions. These two practices and treating patients for pain are most associated with the emergency room visit rates. The results provide additional guidance to home health agencies in their prioritized and focused performance improvement initiatives to improve their utilization outcomes.

Investigating the effect of sociodemographic factors on 30-day hospital readmission among medical patients in Toronto, Canada: a prospective cohort study

OBJECTIVE

To examine the influence of patient-level sociodemographic factors on the incidence of hospital readmission within 30 days among medical patients in a large Canadian metropolitan city.

DESIGN

Prospective cohort study.

SETTING AND PARTICIPANTS

Patients admitted to the General Internal Medicine service of an urban teaching hospital in Toronto, Canada participated in a survey of sociodemographic information. Patients were not surveyed if deemed medically unstable, receiving care in medical/surgical step-down beds or were isolated for infection control. Included in the final analysis was a diverse cohort of 1427 adult, non-palliative, patients who were discharged home.

MEASURES

Thirteen patient-level sociodemographic variables were examined in relation to time to unplanned all-cause readmission within 30 days. Illness level was accounted for by the following covariates: self-perceived health status, previous hospital utilisation, primary diagnosis case mix group, Charlson Comorbidity Index score and inpatient length of stay.

RESULTS

Approximately, 14.4% (n=205) of patients experienced readmission within 30 days. Sociodemographic factors were not significantly associated with time to readmission in unadjusted and adjusted analyses. Indicators of illness level, namely, previous hospitalisations, were the strongest risk factors for readmission within this cohort. One previous admission (adjusted HR 1.78; 95% CI 1.22 to 2.59, P<0.01) and at least four previous emergency department visits (adjusted HR 2.33; 95% CI 1.46 to 4.43, P<0.01) were associated with increased hazard of readmission within 30 days.

CONCLUSIONS

Patient-level sociodemographic factors did not influence the incidence of unplanned all-cause readmission within 30 days. Further research is needed to understand the generalisability of our findings and investigate whether contextual factors, such as access to universal health insurance coverage, attenuate the effects of sociodemographic factors.

Inpatient palliative care referral and 9-month hospital readmission in patients with congestive heart failure: a linked nationwide analysis

OBJECTIVE

End-stage heart failure (HF) is characterized by high symptom burden and frequent hospitalization. Palliative care (PC) is recommended for advanced HF, and there is some evidence in other diseases that this may reduce readmission rates. We attempted examine the association of an inpatient PC visit on hospital readmission for patients admitted with HF.

METHODS

Retrospective linked nationwide analysis from 2013 with 9-month follow-up for all hospital readmissions for patients admitted with HF exacerbations using the Nationwide Readmission Database (NRD). The NRD gathers all hospital admissions for patients from 22 states and tracks patients throughout the year, allowing for examination of readmission statistics. A propensity score model for PC visit was made, and patients were matched in a 1 : 1 fashion.

RESULTS

There were 102 746 patients who survived an admission for HF in the first 3 months of 2013. Of these, 2287 (2.2%) patients had a PC visit as inpatients. After matching based on propensity for a PC visit during the index hospitalization, 2282 patients who received a PC visit were matched to 2282 patients who did not. Those receiving a PC visit were less likely to be readmitted for HF (9.3% vs. 22.4%, P < 0.01) or for any cause (29.0% vs. 63.2%, P < 0.01) during the 9-month follow-up period. The average hospital charges during the follow-up period for the non-PC cohort were $77 643 per patient. The average charges for PC patients were $23 200 (P < 0.01).

CONCLUSIONS

Patients with HF who received an inpatient PC visit had significantly lower rates of all-cause and HF-specific readmission in the subsequent 9 months. Total 9-month hospital charges were also significantly lower for patients who received an inpatient PC visit.

Reducing Readmissions among Heart Failure Patients Discharged to Home Health Care: Effectiveness of Early and Intensive Nursing Services and Early Physician Follow-Up

OBJECTIVE

To compare the effectiveness of two "treatments"-early, intensive home health nursing and physician follow-up within a week-versus less intense and later postacute care in reducing readmissions among heart failure (HF) patients discharged to home health care.

DATA SOURCES

National Medicare administrative, claims, and patient assessment data.

STUDY DESIGN

Patients with a full week of potential exposure to the treatments were followed for 30 days to determine exposure status, 30-day all-cause hospital readmission, other health care use, and mortality. An extension of instrumental variables methods for nonlinear statistical models corrects for nonrandom selection of patients into treatment categories. Our instruments are the index hospital's rate of early aftercare for non-HF patients and hospital discharge day of the week.

DATA EXTRACTION METHODS

All hospitalizations for a HF principal diagnosis with discharge to home health care between July 2009 and June 2010 were identified from source files.

PRINCIPAL FINDINGS

Neither treatment by itself has a statistically significant effect on hospital readmission. In combination, however, they reduce the probability of readmission by roughly 8 percentage points (p < .001; confidence interval = -12.3, -4.1). Results are robust to changes in implementation of the nonlinear IV estimator, sample, outcome measure, and length of follow-up.

CONCLUSIONS

Our results call for closer coordination between home health and medical providers in the clinical management of HF patients immediately after hospital discharge.

Examining Characteristics of Hospitalizations in Heart Failure Patients: Results from the 2009 All-payer Data

Heart failure (HF) is one of the most common chronic and disabling illnesses, resulting in high morbidity and mortality. Readmission rate, one key indicator of healthcare quality and healthcare utilization, is prevalent in HF patients. Inconsistent evidences exist about the impact of rural health disparities on HF patients' readmissions. The purpose of this explorative study was to examine the characteristics of hospitalized HF patients and factors related to readmissions in 2009. The results showed all-cause readmission rates were 13.6%, 23.6%, and 31.6% at 30-, 90- and 180-days respectively. The factors related readmissions included age, income, discharge/transfer status from index hospitalization, and comorbidity. Findings from this analysis suggested additional studies using multiple data sources are needed to have a comprehensive understanding of risk factors related HF patients' healthcare utilization.