Medical and socioenvironmental predictors of hospital readmission in patients with congestive heart failure

Socio-economic inequalities and heart failure morbidity and mortality: A systematic review and data synthesis

Socio-economic status (SES) has been associated with incident and prevalent heart failure (HF), as well as its morbidity and mortality. However, the precise nature of the relationship between SES and HF remains unclear due to inconsistent data. This study aims to provide a comprehensive assessment and data synthesis of the relationship between SES and HF morbidity and mortality. We performed a systematic search and data synthesis using six databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines. The included studies comprised observational studies that reported on HF incidence and prevalence, HF hospitalizations, worsening HF (WHF) and all-cause mortality, as well as treatment options (medical, device and advanced HF therapies). SES was measured on both individual and area levels, encompassing single (e.g., income, education, employment, social risk score, living conditions and housing characteristics) and composite indicators. Among the 4124 studies screened, 79 were included, with an additional 5 identified through cross-referencing. In the majority of studies, a low SES was associated with an increased HF incidence (72%) and prevalence (75%). For mortality, we demonstrated that low SES was associated with increased mortality in 45% of the studies, with 18% of the studies showing mixed results (depending on the indicator, gender or follow-up) and 38% showing non-significant results. Similar patterns were observed for the association between SES, WHF, medical therapy prescriptions and the utilization of devices and advanced HF therapies. There was no clear pattern in the used SES indicators and HF outcomes. This systematic review, using contemporary data, shows that while socio-economic disparity may influence HF incidence, management and subsequent adverse events, these associations are not uniformly predictive. Our review highlights that the impact of SES varies depending on the specific indicators used, reflecting the complexity of its influence on health disparities. Assessment and recognition of SES as an important risk factor can assist clinicians in early detection and customizing HF treatment, while also aiding policymakers in optimizing resource allocation.

Clinical Utility of Machine Learning-Derived Vocal Biomarkers in the Management of Heart Failure

Background

This study aimed to systematically evaluate voice symptoms during heart failure (HF) treatments and to exploratorily extract HF-related vocal biomarkers.

Methods and Results

This single-center, prospective study longitudinally acquired 839 audio files from 59 patients with acute decompensated HF. Patients' voices were analyzed along with conventional HF indicators (New York Heart Association [NYHA] class, presence of pulmonary congestion and pleural effusion on chest X-ray, and B-type natriuretic peptide [BNP]) and GOKAN scores based on the assessment of a cardiologist. Machine-learning (ML) models to estimate HF conditions were created using a Light Gradient Boosting Machine. Voice analysis identified 27 acoustic features that correlated with conventional HF indicators and GOKAN scores. When creating ML models based on the acoustic features, there was a significant correlation between actual and ML-derived BNP levels (r=0.49; P<0.001). ML models also identified good diagnostic accuracies in determining HF conditions characterized by NYHA class ≥2, BNP ≥300 pg/mL, presence of pulmonary congestion or pleural effusion on chest X-ray, and decompensated HF (defined as NYHA class ≥2 and BNP levels ≥300 pg/mL; accuracy: 75.1%, 69.1%, 68.7%, 66.4%, and 80.4%, respectively).

Conclusions

The present study successfully extracted HF-related acoustic features that correlated with conventional HF indicators. Although the data are preliminary, ML models based on acoustic features (vocal biomarkers) have the potential to infer various HF conditions, which warrant future studies.

Psychometric properties of the Japanese version of the Self-Care of Heart Failure Index version 7.2

AIMS

It is more important for patients with heart failure (HF) to objectively identify their self-care status. The Self-Care of Heart Failure Index (SCHFI) version 7.2 is a reliable and valid instrument comprising three scales: self-care maintenance, symptom perception, and self-care management. We aimed to translate the SCHFI v.7.2 into Japanese and test its validity and reliability.

METHODS AND RESULTS

This was a cross-sectional study. Two translators performed forward and backward translations between English and Japanese. To assess structural validity, confirmatory factor analyses were performed using the structure of the original version. To assess convergent validity, the associations between each scale and self-care self-efficacy were evaluated. To assess internal consistency, model-based internal consistency coefficients were calculated. Participants were 314 Japanese outpatients with HF (mean age: 72.8 ± 12.8 years). Regarding structural validity, all scales showed adequate model fit indices, supporting a two-factor structure with items similar to those in the original version. However, to improve the model fit indices, it was necessary to add error correlations for the self-care maintenance and symptom perception scales. Regarding convergent validity, all scales showed significant associations with self-care self-efficacy. Regarding internal consistency, the model-based internal consistency coefficients were sufficient for all scales (0.739, 0.908, and 0.783 for the self-care maintenance, symptom perception, and self-care management scales, respectively).

CONCLUSION

The Japanese version of the SCHFI v.7.2 had adequate validity and reliability. This instrument is useful for assessing self-care in Japanese HF patients. However, factors influencing self-care should be considered when interpreting results.

Disparities in postoperative complications and perioperative events based on insurance status following elective spine surgery: A systematic review and meta-analysis

Background

Increasing evidence demonstrates disparities among patients with differing insurance statuses in the field of spine surgery. However, no pooled analyses have performed a robust review characterizing differences in postoperative outcomes among patients with varying insurance types.

Methods

A comprehensive literature search of the PUBMED, MEDLINE(R), ERIC, and EMBASE was performed for studies comparing postoperative outcomes in patients with private insurance versus government insurance. Pooled incidence rates and odds ratios were calculated for each outcome and meta-analyses were conducted for 3 perioperative events and 2 types of complications. In addition to pooled analysis, sub-analyses were performed for each outcome in specific government payer statuses.

Results

Thirty-eight studies (5,018,165 total patients) were included. Compared with patients with private insurance, patients with government insurance experienced greater risk of 90-day re-admission (OR 1.84, p<.0001), non-routine discharge (OR 4.40, p<.0001), extended LOS (OR 1.82, p<.0001), any postoperative complication (OR 1.61, p<.0001), and any medical complication (OR 1.93, p<.0001). These differences persisted across outcomes in sub-analyses comparing Medicare or Medicaid to private insurance. Similarly, across all examined outcomes, Medicare patients had a higher risk of experiencing an adverse event compared with non-Medicare patients. Compared with Medicaid patients, Medicare patients were only more likely to experience non-routine discharge (OR 2.68, p=.0007).

Conclusions

Patients with government insurance experience greater likelihood of morbidity across several perioperative outcomes. Additionally, Medicare patients fare worse than non-Medicare patients across outcomes, potentially due to age-based discrimination. Based on these results, it is clear that directed measures should be taken to ensure that underinsured patients receive equal access to resources and quality care.

Developing Multidisciplinary Management of Heart Failure in the Super-Aging Society of Japan

The Japanese population is rapidly aging because of its long life expectancy and low birth rate; additionally, the number of patients with heart failure (HF) is increasing to the extent that HF is now considered a pandemic. According to a recent HF registry study, Japanese patients with HF have both medical and care-related problems. Although hospitalization is used to provide medical services, and institutionalization is used to provide care for frail older adults, it can be difficult to distinguish between them. In this context, multidisciplinary management of HF has become increasingly important in preventing hospital readmissions and maintaining a patient's quality of life. Academia has promoted an increase in the number of certified HF nurses and educators. Researchers have issued numerous guidelines or statements on topics such as cardiac rehabilitation, nutrition, and palliative care, in addition to the diagnosis and treatment of acute and chronic HF. Moreover, the Japanese government has created incentives through various medical and long-term care systems adjustments to increase collaboration between these two fields. This review summarizes current epidemiological registries that focus not only on medical but also care-related problems and the 10 years of multidisciplinary management experience in Japanese medical and long-term care systems.

Machine learning based readmission and mortality prediction in heart failure patients

This study intends to predict in-hospital and 6-month mortality, as well as 30-day and 90-day hospital readmission, using Machine Learning (ML) approach via conventional features. A total of 737 patients remained after applying the exclusion criteria to 1101 heart failure patients. Thirty-four conventional features were collected for each patient. First, the data were divided into train and test cohorts with a 70-30% ratio. Then train data were normalized using the Z-score method, and its mean and standard deviation were applied to the test data. Subsequently, Boruta, RFE, and MRMR feature selection methods were utilized to select more important features in the training set. In the next step, eight ML approaches were used for modeling. Next, hyperparameters were optimized using tenfold cross-validation and grid search in the train dataset. All model development steps (normalization, feature selection, and hyperparameter optimization) were performed on a train set without touching the hold-out test set. Then, bootstrapping was done 1000 times on the hold-out test data. Finally, the obtained results were evaluated using four metrics: area under the ROC curve (AUC), accuracy (ACC), specificity (SPE), and sensitivity (SEN). The RFE-LR (AUC: 0.91, ACC: 0.84, SPE: 0.84, SEN: 0.83) and Boruta-LR (AUC: 0.90, ACC: 0.85, SPE: 0.85, SEN: 0.83) models generated the best results in terms of in-hospital mortality. In terms of 30-day rehospitalization, Boruta-SVM (AUC: 0.73, ACC: 0.81, SPE: 0.85, SEN: 0.50) and MRMR-LR (AUC: 0.71, ACC: 0.68, SPE: 0.69, SEN: 0.63) models performed the best. The best model for 3-month rehospitalization was MRMR-KNN (AUC: 0.60, ACC: 0.63, SPE: 0.66, SEN: 0.53) and regarding 6-month mortality, the MRMR-LR (AUC: 0.61, ACC: 0.63, SPE: 0.44, SEN: 0.66) and MRMR-NB (AUC: 0.59, ACC: 0.61, SPE: 0.48, SEN: 0.63) models outperformed the others. Reliable models were developed in 30-day rehospitalization and in-hospital mortality using conventional features and ML techniques. Such models can effectively personalize treatment, decision-making, and wiser budget allocation. Obtained results in 3-month rehospitalization and 6-month mortality endpoints were not astonishing and further experiments with additional information are needed to fetch promising results in these endpoints.

Cardio SEM: A Novel Approach for a Traffic Light System for Heart Failure Warning Signs

Existing literature on the follow-up of heart failure patients with warning signs shows that it is necessary to increase patients' knowledge and of seeking help in a timely manner. This suggests an opportunity to implement strategies that integrate technology to visualize the risk of decompensation. This article studies the acceptance of Cardio Sem, a traffic light system mobile application for patients with heart failure. A descriptive, observational pilot study was performed with 23 outpatients belonging to a heart failure program. For 4 weeks, patients used Cardio Sem, which allows visualizing the risk of decompensation through a series of questions that patients must answer daily and provides guidance for managing signs and symptoms of decompensation. A technology acceptance questionnaire was applied to all patients, resulting in acceptance of the application, especially in the dimensions that emphasized perceived usefulness (100%), social influence (100%), and behavioral intent (99.8%). Cardio Sem is useful for early detection of symptoms that allow for early response to complications. Acceptance of the application by patients and its ease of use present the possibility to implement it as a complementary tool to promote self-care and effective management of symptoms.

Heart Failure Management Capability and Exacerbation of Heart Failure - A 6-Month Prospective Cohort Study

Background: In households with older individuals, where a patient is experiencing heart failure (HF), effective cooperation between patients and caregivers is crucial for disease management. However, there is limited evidence regarding the impact of cooperative HF management on the incidence of exacerbation. Therefore, the aim of this 6-month prospective cohort study was to investigate the association between HF management capability and exacerbations. Methods and Results: The study enrolled outpatients (age ≥65 years) with chronic HF from a cardiology clinic and their caregivers. Self-care capabilities among patients and caregivers were evaluated using the Self-Care of Heart Failure Index (SCHFI) and Caregiver Contribution-SCHFI, respectively. Total scores were calculated using the highest score for each item. During the follow-up period, 31 patients experienced worsening HF. The analysis revealed no significant association between the total HF management score and HF exacerbation among all eligible patients. However, in patients with preserved left ventricular ejection fraction (LVEF), high HF management capability of the family unit was associated with a reduced risk of HF exacerbation, even after adjusting for the severity of HF. Conclusions: In older patients with HF and preserved LVEF, effective HF management may contribute to a lower risk of exacerbations.

Development of a model predicting cardiac events in heart failure patients with decreased renal function: a retrospective study

BACKGROUND

Inappropriate and multiple medications affect the prognosis of patients with acute decompensated heart failure (ADHF). However, in ADHF patients with decreased renal function, there have been no reports on prognostic factors, including medication data, or models for predicting cardiac events.

AIM

To develop a model including medication data to predict cardiac events in ADHF patients with decreased renal function.

METHOD

This retrospective cohort study included 443 first-time admitted ADHF patients with decreased renal function (estimated glomerular filtration rate < 60 mL/min/1.73 m² at discharge) in the Showa University Fujigaoka Hospital. The primary outcome was cardiac events within one year after discharge, defined as the composite of HF readmission, HF mortality, and cardiovascular mortality. The model for predicting cardiac events was developed using predictive factors extracted by multivariable analysis. The cardiac events curves were visualized using the Kaplan-Meier method and estimated using a log-rank test.

RESULTS

The incidence of cardiac events within one year after discharge was 20.1%. By multivariable analysis, we observed that atrial fibrillation, weight loss < 5%, brain natriuretic peptide ≥ 200 pg/mL, polypharmacy, and beta-blockers use below target dosage were significantly associated with an increased risk of cardiac events. The developed model, the cardiac events rate in the high-risk group was significantly higher than in the low-risk group (41.0 vs. 9.2%, p < 0.001).

CONCLUSION

The developed model for predicting cardiac events will be useful in decision-making to support appropriate early management of ADHF patients with decreased renal function.

Development and appropriateness of a scoring method for International Classification of Functioning, Disabilities, and Health assessment in older patients with heart failure: a Delphi survey of expert panel in Japan

OBJECTIVE

The number of older patients with heart failure (HF) is increasing in Japan and has become a social problem. There is an urgent need to develop a comprehensive assessment methodology based on the common language of healthcare; the International Classification of Functioning, Disability and Health (ICF). The purpose of this study was to develop and confirm the appropriateness of a scoring methodology for 43 ICF categories in older people with HF.

DESIGN

Cross-sectional survey. We applied the RAND/University of California at Los Angeles (UCLA) Appropriateness Method with a modified Delphi method.

SETTING AND PARTICIPANTS

We included a panel of 26 multidisciplinary experts on HF care consisting of home physicians, cardiovascular physicians, care managers, nurses, physical therapists, a pharmacist, occupational therapist, nutritionist and a social worker.

MEASURES

We conducted a literature review of ICF linking rules and developed a questionnaire on scoring methods linked to ICF categories in older people with HF. In the Delphi rounds, we sent the expert panel a questionnaire consisting of three questions for each of the 43 ICF categories. The expert panel responded to the questionnaire items on a 1 (very inappropriate) - 9 (very appropriate) Likert scale and repeated rounds until a consensus of 'Appropriate' and 'Agreement' was reached on all items.

RESULTS

A total of 21 panel members responded to all the Delphi rounds. In the first Delphi round, six question items in four ICF categories did not reach a consensus of 'Agreement', but the result of our modifications based on panel members' suggestions reached to a consensus of 'Appropriate' and 'Agreement' on all questions in the second Delphi round.

CONCLUSION

The ICF-based scoring method for older people with HF developed in this study was found to be appropriate. Future work is needed to clarify whether comprehensive assessment and information sharing based on ICF contributes to preventing readmissions.

Predictive Modeling of Hospital Readmission: Challenges and Solutions

Hospital readmission prediction is a study to learn models from historical medical data to predict probability of a patient returning to hospital in a certain period, e.g. 30 or 90 days, after the discharge. The motivation is to help health providers deliver better treatment and post-discharge strategies, lower the hospital readmission rate, and eventually reduce the medical costs. Due to inherent complexity of diseases and healthcare ecosystems, modeling hospital readmission is facing many challenges. By now, a variety of methods have been developed, but existing literature fails to deliver a complete picture to answer some fundamental questions, such as what are the main challenges and solutions in modeling hospital readmission; what are typical features/models used for readmission prediction; how to achieve meaningful and transparent predictions for decision making; and what are possible conflicts when deploying predictive approaches for real-world usages. In this paper, we systematically review computational models for hospital readmission prediction, and propose a taxonomy of challenges featuring four main categories: (1) data variety and complexity; (2) data imbalance, locality and privacy; (3) model interpretability; and (4) model implementation. The review summarizes methods in each category, and highlights technical solutions proposed to address the challenges. In addition, a review of datasets and resources available for hospital readmission modeling also provides firsthand materials to support researchers and practitioners to design new approaches for effective and efficient hospital readmission prediction.

Local Supply Of Postdischarge Care Options Tied To Hospital Readmission Rates

The extent to which patients' risk for readmission after a hospitalization is influenced by local availability of postdischarge care options is not currently known. We used national, hospital-level data to assess whether the supply of postdischarge care options in hospitals' catchment areas was associated with readmission rates for Medicare patients after hospitalizations for acute myocardial infarction, heart failure, or pneumonia. Overall, readmission rates were negatively associated with per capita supply of primary care physicians (-0.16 percentage points per standard deviation) and licensed nursing home beds (-0.09 percentage points per standard deviation). In contrast, readmission rates were positively associated with per capita supply of nurse practitioners (0.09 percentage points per standard deviation). Our results suggest potential modifications to the Hospital Readmissions Reduction Program to account for local health system characteristics when assigning penalties to hospitals.

Does scoring patient complexity using COMPRI predict the length of hospital stay? A multicentre case-control study in Japan

OBJECTIVE

To clarify the factors associated with prolonged hospital stays, focusing on the COMplexity PRediction Instrument (COMPRI) score's accuracy in predicting the length of stay of newly hospitalised patients in general internal medicine wards.

DESIGN

A case-control study.

SETTING

Three general internal medicine wards in Chiba Prefecture, Japan.

PARTICIPANTS

Thirty-four newly hospitalised patients were recruited between November 2017 and December 2019, with a final analytic sample of 33 patients. We included hospitals in different cities with general medicine outpatient and ward facilities, who agreed to participate. We excluded any patients who were re-hospitalised within 2 weeks of a prior discharge.

PRIMARY AND SECONDARY OUTCOME MEASURES

Patients' COMPRI scores and their consequent lengths of hospital stay.

RESULTS

The 17 patients (52%) allocated to the long-term hospitalisation group (those hospitalised ≥14 days) had a significantly higher average age, COMPRI score and percentage of participants with comorbid chronic illnesses than the short-term hospitalisation group (<14 days). A logistic regression model (model A, comprising only the COMPRI score as the explanatory variable) and a multiple logistic regression model (model B, comprising variables other than the COMPRI score as explanatory variables) were created as prediction models for the long-term hospitalisation group. When age ≥75 years, a COMPRI score ≥6 and a physician with 10 years' experience were set as explanatory variables, model A showed better predictive accuracy compared with model B (fivefold cross-validation, area under curve of 0.87 vs 0.78). The OR of a patient with a COMPRI score of ≥6 joining the long-term hospitalisation group was 4.25 (95% CI=1.43 to 12.63).

CONCLUSIONS

Clinicians can use the COMPRI score when screening for complexity assessment to identify hospitalised patients at high risk of prolonged hospitalisation. Providing such patients with multifaceted and intensive care may shorten hospital stays.

Exploring risk factors of short-term readmission in heart failure patients: A cohort study

BACKGROUND

The risk of all-cause mortality in patients with heart failure (HF) has been studied previously. Readmission risk of HF patients was rarely explored. Thus, we aimed to explore early warning factors that may influence short-term readmission of HF patients.

METHODS

The data of this study came from an HF database in China. It was a retrospective single-center observational study that collected characteristic data on Chinese HF patients by integrating electronic medical records and follow-up outcome data. Eventually, 1,727 patients with HF were finally included in our study.

RESULTS

In our study, the proportion of HF patients with New York Heart Association (NYHA) class II, III, and IV HF were 17.20%, 52.69%, and 30.11%, respectively. The proportion of patients with readmission within 6 months and readmission within 3 months was 38.33% and 24.20%, respectively. Multivariate logistic regression showed that NYHA class (p _III = 0.028, p _IV < 0.001), diabetes (p = 0.002), Cr (p = 0.003), and RDW-SD (p = 0.039) were risk factors for readmission within 6 months of HF patients. NYHA class (p _III = 0.038, p _IV < 0.001), CCI (p = 0.033), Cr (p = 0.012), UA (p = 0.042), and Na (p = 0.026) were risk factors for readmission within 3 months of HF patients.

CONCLUSIONS

Our study implied risk factors of short-term readmission risk in patients with HF, which may provide policy guidance for the prognosis of patients with HF.

Prognostic Role of Prior Heart Failure Hospitalization Among Patients Hospitalized for Worsening Chronic Heart Failure

BACKGROUND

Hospitalization for heart failure (HF) is associated with increased risk of death among patients with chronic HF. The degree to which hospitalization for HF is a distinct biologic entity with independent prognostic value versus a marker of higher risk chronic HF patients is unclear.

METHODS

After excluding patients with new-onset HF, the ASCEND-HF trial (Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure) included 4205 patients hospitalized for worsening chronic HF with reduced or preserved ejection fraction. The present analysis compared patients by presence or absence of prior HF hospitalization within 12 months and by timing of prior HF hospitalization relative to index hospitalization. Associations with 180-day all-cause mortality were assessed, including adjustment for 27 prespecified clinical factors.

RESULTS

Overall, 2241 (53.3%) patients had a HF hospitalization within the prior 12 months and 1964 (46.7%) did not. Mortality rates at 180 days were 15.5% and 11.9%, respectively. In unadjusted analyses, prior HF hospitalization was associated with increased risk of 180-day mortality (HR, 1.35 [95% CI, 1.14-1.59]; P<0.01). After adjustment, the point estimate was attenuated and the association not statistically significant (HR, 1.18 [95% CI, 0.99-1.40]; P=0.064). Similarly, after adjustment, compared with patients without prior hospitalization, prior HF hospitalization was not associated with mortality, irrespective of timing (0-4 months: HR, 1.10 [95% CI, 0.87-1.39], P=0.41; 4-8 months: HR, 0.95 [95% CI, 0.70-1.27]; P=0.72; 8-12 months: HR, 1.06 [95% CI, 0.74-1.51], P=0.77; >12 months: HR, 0.81 [95% CI, 0.63-1.06], P=0.12).

CONCLUSIONS

In this cohort of patients hospitalized for worsening HF, prior HF hospitalization was not associated with 180-day mortality after comprehensively accounting for patient characteristics measured during the index patient visit. Clinical confounders measured at the point-of-care may explain previously observed associations between prior HF hospitalization and mortality, and these clinical factors may be a more direct means of predicting patient survival. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00475852.

Regional Disparities in Adherence to Guidelines for the Treatment of Chronic Heart Failure

Objective The incidence of chronic heart failure (CHF) is likely to keep increasing in Japan as the population ages, placing increased burdens on medical facilities, particularly on the limited numbers of rural hospitals. We explored the appropriateness of CHF treatment in rural areas in Japan. Methods We compared rates of adherence to therapeutic guidelines for CHF between residents with a left ventricular ejection fraction <35% living in urban areas (n = 207) and those in rural areas (n = 180). Treatments included pharmacological [beta-blockers, angiotensin-converting enzyme inhibitors (ACEi)/angiotensin II receptor blocker (ARB), mineralocorticoid receptor antagonist (MRA) and anticoagulants for atrial fibrillation] and non-pharmacological [implantable cardioverter defibrillator (ICD)/cardiac resynchronization therapy (CRT), cardiac rehabilitation and HF education] approaches. Patients This study included 387 patients with CHF, prior myocardial infarction or cardiomyopathy, and a left ventricular ejection fraction (LVEF) <35% as determined by echocardiography. Results The respective rates of treatments administered in urban and rural areas were as follows: beta-blockers, 91.3% vs. 61.7% (p<0.05); ACEi/ARB, 86.5% vs. 68.3% (p<0.05); MRA, 74.4% vs. 59.4% (p<0.01); anticoagulants, 100% vs. 86.5%, (p<0.05); ICD/CRT, 45.4% vs. 5.0% (p<0.05); cardiac rehabilitation, 32.4% vs. 13.3% (p<0.05) and HF education, 33.3% vs. 32.8% (p=0.75). Conclusion Regional disparities in treatment for CHF persist, even in Japan. Improvements in the use of guideline-directed treatment in rural areas might improve the outcomes for CHF patients.

Living Alone and Gender Differences in Rehospitalization for Heart Failure After Discharge Among Acute Heart Failure Patients

Home treatment for heart failure (HF) is one of the most important problems in patients after discharge as a secondary preventive measure for rehospitalization for HF. However, there are no detailed studies on gender differences in sociopsychological factors such as living alone for HF rehospitalization among patients with acute HF (AHF).This prospective multicenter cohort study enrolled patients with AHF between April 2015 and August 2017. Patients of each gender with first AHF were divided into those living alone and those not living alone. The primary endpoint was defined as rehospitalization for HF after discharge. Cox proportional hazard analysis was performed to determine the association between living alone and the endpoint.Overall, 581 patients were included in this study during the 3-year follow-up. The proportion of rehospitalization for HF was significantly higher in patients living alone than in those not living alone among male patients. However, female patients showed no difference in endpoints between the two groups. The difference was independently maintained even after adjusting for differences in social backgrounds in male patients (adjusted hazard ratio (HR) 2.02; 95% confidence interval (CI), 1.07-3.70). In female patients, the HR for rehospitalization for HF showed no difference between the two groups (adjusted HR, 0.99; 95% CI, 0.56-1.69).In this study population, male patients living alone after first AHF discharge had a higher risk of rehospitalization for HF than those not living alone, but these differences were not observed in female patients.

Long-term management of chronic heart failure patients in internal medicine

Chronic heart failure (CHF) is one of the main disabilities in elderly patients requiring frequent hospitalizations with high health care costs. We studied the outcome of CHF outpatient management in reducing hospitalization after discharge from a division of Internal Medicine at a large 3rd referral regional Hospital. 147 CHF inpatients (M:F: 63:84; mean age 76 ± 9.6 years) admitted for acute exacerbation of CHF were followed up as outpatients at 1, 6, 12 and 24 months after discharge. At baseline, patients underwent: laboratory tests, ECG, echocardiogram and a dedicated-intensive health care educational program involving also their families. The rate of hospitalization in the same group of patients was compared with data from the previous 24 months, a period when patients had been seen elsewhere without disease management programs. Patients had high prevalence of comorbidities and the majority was in NYHA class III or IV. Hypertension and valvular heart disease were the most common causes for CHF. Systolic function was preserved (LVEF ≥ 50%) in 61.9% of cases. Functional NYHA class improved significantly after 6 months and remained stable at 24 months. There was a significant increase in the use of the renin-angiotensin system blockers, beta-blockers and diuretics compared to admission to the ward. At 24 months, hospital readmissions were decreased by 42% as compared to the previous 24 months. Risk factors for re-hospitalizations were anemia, NYHA class III or IV and previous hospitalizations. Establishing an intensive outpatient management program for CHF patients leads to long-term beneficial effects with improved clinical parameters and decreased hospitalization in the setting of Internal Medicine.

Nurse-Led Collaborative Management Using Telemonitoring Improves Quality of Life and Prevention of Rehospitalization in Patients with Heart Failure

The effects of disease management using telemonitoring for patients with heart failure (HF) remain controversial. Hence, we embedded care coordination and enhanced collaborative self-management through interactive communication via a telemonitoring system (collaborative management; CM). This study evaluated whether CM improved psychosocial status and prevented rehospitalization in patients with HF in comparison with self-management education (SM), and usual care (UC).We randomly allocated 59 patients into 3 groups; UC (n = 19), SM (n = 20), and CM (n = 20). The UC group received one patient education session, and the SM and CM groups participated in disease management programs for 12 months. The CM group received telemonitoring concurrently. All groups were followed up for another 12 months. Data were collected at baseline and at 6, 12, 18, and 24 months.The primary endpoint was quality of life (QOL). Secondary endpoints included self-efficacy, self-care, and incidence of rehospitalization. The QOL score improved in CM compared to UC at 18 and 24 months (P < 0.05). There were no significant differences among the 3 groups in self-efficacy and self-care. However, compared within each group, only the CM had significant changes in self-efficacy and in self-care (P < 0.01). Rehospitalization rates were high in the UC (11/19; 57.9%) compared with the SM (5/20; 27.8%) and CM groups (4/20; 20.0%). The readmission-free survival rate differed significantly between the CM and UC groups (P = 0.020).We conclude that CM has the potential to improve psychosocial status in patients with HF and prevent rehospitalization due to HF.

90-day Readmission in Elective Primary Lumbar Spine Surgery in the Inpatient Setting: A Nationwide Readmissions Database Sample Analysis

STUDY DESIGN

Secondary analysis of a large administrative database.

OBJECTIVE

The objectives of this study are to: 1) identify the incidence and cause of 90-day readmissions following primary elective lumbar spine surgery, 2) offer insight into potential risk factors that contribute to these readmissions, and 3) quantify the cost associated with these readmissions.

SUMMARY OF BACKGROUND DATA

As bundled-payment models for the reimbursement of surgical services become more popular in spine, the focus is shifting toward long-term patient outcomes in the context of 90-day episodes of care. With limited data available on national 90-day readmission statistics available, we hope to provide evidence that will aid in the development of more cost-effective perioperative care models.

METHODS

Using ICD-9 coding, we identified all patients 18 years of age and older in the 2014 Nationwide Readmissions Database (NRD) who underwent an elective, inpatient, primary lumbar spine surgery. Using multivariate logistic regression, we identified independent predictors of 90-day readmission while controlling for a multitude of confounding variables and completed a comparative cost analysis.

RESULTS

We identified 169,788 patients who underwent a primary lumbar spine procedure. In total 4268 (2.5%) were readmitted within 90 days. There was no difference in comorbidity burden between cohorts (readmitted vs. not readmitted) as quantified by the Elixhauser Comorbidity index. Independent predictors of increased odds of 90-day readmission were: anemia, uncomplicated diabetes and diabetes with chronic complications, surgical wound disruption and acute myocardial infarction at the time of the index admission, self-pay status, and an anterior surgical approach. Implant complications were identified as the primary related cause of readmission. These readmissions were associated with a significant cost increase.

CONCLUSION

There are clearly identifiable risk factors that increase the odds of hospital readmission within 90 days of primary lumbar spine surgery. An overall 90-day readmission rate of 2.5%, while relatively low, carries significantly increased cost to both the patient and hospital.

LEVEL OF EVIDENCE

3.

Clinical and Socioeconomic Predictors of Heart Failure Readmissions: A Review of Contemporary Literature

Heart failure represents a clinical syndrome that results from a constellation of disease processes affecting myocardial function. Although recent studies have suggested a declining or stable incidence of heart failure, patients with heart failure continue to have high hospitalization and readmission rates, resulting in a substantial economic and public health burden. We searched PubMed and Google Scholar to identify published literature from 1998 through 2018 using the following keywords: heart failure, readmissions, predictors, prediction models, and interventions. Cited references were also used to identify relevant literature. Developments in the diagnosis and management of patients with heart failure have improved hospitalization and readmission rates in the past few decades. However, heart failure remains the most common cause of hospitalization in persons older than 65 years. As a result, given the enormous clinical and financial burden associated with heart failure readmissions on health care, there has been growing interest in the investigation of mechanisms aimed at improving outcomes and curtailing associated costs of care. Herein, we review the current literature on clinical and socioeconomic predictors of heart failure readmissions, briefly discussing limitations of existing strategies and providing an overview of current technology aimed at reducing hospitalizations.

Social Factors and Patient Perceptions Associated With Preventable Hospital Readmissions

Background:

Preventable hospital readmissions are costly and erode the quality of care delivery. Few efforts to incorporate the patient perspectives and social factors associated with readmission preventability exist.

Objective:

To identify patient perceptions and social barriers to care related to readmission.

Methods:

Prospective cohort study of 202 respondents readmitted within 30 days of hospital discharge from 2 inpatient adult medicine units at Massachusetts General Hospital, Boston, Massachusetts between January 2012 and January 2016.

Results:

Few participants indicated that their readmission was due to unattainable health care after discharge. Almost half indicated that they needed more general assistance to stay well outside the hospital. Those reporting a barrier related to at least 2 measures of social determinants of health were more likely to have preventable readmissions (34% vs 17%, P = .006). Participants with a history of homelessness or substance use disorder were more likely to have preventable readmissions (44% vs 20%, P = .04 and 32% vs 18%, P = .03, respectively).

Conclusion:

Strengthening nonmedical support systems and general social policy may be required to reduce preventable readmissions.

Implementing community health worker-patient pairings at the time of hospital discharge: A randomized control trial

BACKGROUND

In 2011, there were approximately 3.3 million adult 30-day all-cause hospital readmissions in the US generating $41.3 billion in hospital costs. Community health worker (CHW) care delivery is one of very few interventions demonstrated to reduce health care utilization among populations with chronic disease. While there are a number of studies demonstrating improved disease-specific outcomes with CHW interventions, studies examining the effect of CHW care delivery on 30-day readmission rates are rare.

METHODS

This study is a randomized control trial designed to determine if linking hospitalized patients with chronic disease to community health workers (CHWs) can decrease 30-day readmissions. Participants were randomly assigned to receive the 30-day CHW intervention or usual care (no CHW). All study participants completed surveys at baseline and the end of the study 30 days post-discharge. The primary outcome was 30-day readmission and secondary outcomes included emergency department visits, missed appointments, and patient satisfaction.

RESULTS

We plan to enroll 1200 hospitalized patients during a 24-month intervals. As of December 2017, 350 patients have been consented and randomly assigned to either the intervention or control arm. A number of challenges have been encountered in implementing a CHW initiative at the time of hospital discharge.

CONCLUSION

This trial tests the effectiveness of CHW care delivery at the time of hospital discharge in reducing 30-day readmission rates and improving outcomes among patients with chronic disease. We describe and discuss challenges in launching this CHW intervention and strategies utilized to overcome these obstacles. Clinical Trials.gov registration submitted 3/14/2017: Protocol ID# 2017A050810 and Clinical Trials.gov ID# NCT03085264 Community Health Worker Care Transitions Study (C-CAT).

The association between patient experience factors and likelihood of 30-day readmission: a prospective cohort study

OBJECTIVE

Hospital care comprises nearly a third of US healthcare expenditures. Fifteen to 20 per cent of this spending is considered to be potentially preventable. Risk prediction models have suboptimal accuracy and typically exclude patient experience data. No studies have explored patient perceptions of the likelihood of readmission during index admission. Our objective was to examine associations between patient perceptions of care during index hospital admission and 30-day readmission.

DESIGN

Prospective cohort study.

SETTING

Two inpatient adult medicine units at Massachusetts General Hospital, Boston, Massachusetts.

PARTICIPANTS

Eight hundred and forty-six patients admitted to study units between January 2012 and January 2016 who met eligibility criteria and consented to enrolment.

MAIN OUTCOME

Odds of 30-day readmission.

RESULTS

Of 1754 eligible participants, 846 (48%) were enrolled and 201 (23.8%) were readmitted within 30 days. Readmitted participants were less likely to have a high school diploma/GED (44.3% not readmitted vs 53.5% readmitted, P=0.02). In multivariable models adjusting for baseline differences, respondents who reported being 'very satisfied' with the care received during the index hospitalisation were less likely to be readmitted (adjusted OR 0.61, 95% CI 0.43 to 0.88, P=0.007). Participants reporting doctors 'always listened to them carefully' were less likely to be readmitted (adjusted OR 0.68, 95% CI 0.48 to 0.97, P=0.03). Participants reporting they were 'very likely' to be readmitted were not more likely to be readmitted (adjusted OR 1.35, 95% CI 0.83 to 2.19, P=0.22).

CONCLUSION

Participants reporting high satisfaction and good provider communication were less likely to be readmitted. Rates of readmission were increased among participants stating they were very likely to be readmitted though this association was not statistically significant. Incorporating patient-reported measures during index hospitalisations may improve readmission prediction.

90-day Readmission After Lumbar Spinal Fusion Surgery in New York State Between 2005 and 2014: A 10-year Analysis of a Statewide Cohort

MINI: We assessed 90-day readmission and evaluated risk factors associated with readmission after lumbar spinal fusion surgery in New York State. The overall 90-day readmission rate was 24.8%. Age, sex, race, insurance, procedure, number of operated spinal levels, health service area, and comorbidities are major risk factors for 90-day readmission.

STUDY DESIGN

Retrospective cohort study.

OBJECTIVE

The aim of this study was to assess 90-day readmission and evaluate risk factors associated with readmission after lumbar fusion in New York State.

SUMMARY OF BACKGROUND DATA

Readmission is becoming an important metric for quality and efficiency of health care. Readmission and its predictors following spine surgery are overall poorly understood and limited evidence is available specifically in lumbar fusion.

METHODS

The New York Statewide Planning and Research Cooperative System (SPARCS) was utilized to capture patients undergoing lumbar fusion from 2005 to 2014. Temporal trend of 90-day readmission was assessed using Cochran-Armitage test. Logistic regression was used to examine predictors associated with 90-day readmission.

RESULTS

There were 86,869 patients included in this cohort study. The overall 90-day readmission rate was 24.8%. On a multivariable analysis model, age (odds ratio [OR] comparing ≥75 versus <35 years: 1.24, 95% confidence interval [CI]: 1.13-1.35), sex (OR female to male: 1.19, 95% CI: 1.15-1.23), race (OR African-American to white: 1.60, 95% CI: 1.52-1.69), insurance (OR Medicaid to Medicare: 1.42, 95% CI: 1.33-1.53), procedure (OR comparing thoracolumbar fusion, combined [International Classification of Disease, Ninth Revision, ICD-9: 81.04] to posterior lumbar interbody fusion/transforaminal lumbar spinal fusion [ICD-9: 81.08]: 2.10, 95% CI: 1.49-2.97), number of operated spinal levels (OR comparing four to eight vertebrae to two to three vertebrae: 2.39, 95% CI: 2.07-2.77), health service area ([HSA]; OR comparing Finger Lakes to New York-Pennsylvania border: 0.67, 95% CI: 0.61-0.73), and comorbidity, i.e., coronary artery disease (OR: 1.26, 95% CI: 1.19-1.33) were significantly associated with 90-day readmission. Directions of the odds ratios for these factors were consistent after stratification by procedure type.

CONCLUSION

Age, sex, race, insurance, procedure, number of operated spinal levels, HSA, and comorbidities are major risk factors for 90-day readmission. Our study allows risk calculation to determine high-risk patients before undergoing spinal fusion surgery to prevent early readmission, improve quality of care, and reduce health care expenditures.

LEVEL OF EVIDENCE

3.

Clinical presentation at first heart failure hospitalization does not predict recurrent heart failure admission

Aims

There are limited data on whether clinical presentation at first heart failure (HF) hospitalization predicts recurrent HF events. We aimed to assess predictors of recurrent HF hospitalizations in mild HF patients with an implantable cardioverter defibrillator or cardiac resynchronization therapy with defibrillator.

Methods and results

Data on HF hospitalizations were prospectively collected for patients enrolled in MADIT‐CRT. Predictors of recurrent HF hospitalization (HF2) after the first HF hospitalization were assessed using Cox proportional hazards regression models including baseline covariates and clinical presentation or management at first HF hospitalization. There were 193 patients with first HF hospitalization, and 156 patients with recurrent HF events. Recurrent HF rate after the first HF hospitalization was 43% at 1 year, 52% at 2 years, and 55% at 2.5 years. Clinical signs and symptoms, medical treatment, or clinical management of HF at first HF admission was not predictive for HF2. Baseline covariates predicting recurrent HF hospitalization included prior HF hospitalization (HR = 1.59, 95% CI: 1.15–2.20, P = 0.005), digitalis therapy (HR = 1.58, 95% CI: 1.13–2.20, P = 0.008), and left ventricular end‐diastolic volume >240 mL (HR = 1.62, 95% CI: 1.17–2.25, P = 0.004).

Conclusions

Recurrent HF events are frequent following the first HF hospitalization in patients with implanted implantable cardioverter defibrillator or cardiac resynchronization therapy with defibrillator. Neither clinical presentation nor clinical management during first HF admission was predictive of recurrent HF. Prior HF hospitalization, digitalis therapy, and left ventricular end‐diastolic volume at enrolment predicted recurrent HF hospitalization, and these covariates could be used as surrogate markers for identifying a high‐risk cohort.

Patient Perceptions on Facilitating Follow-Up After Heart Failure Hospitalization

BACKGROUND

Timely follow-up after hospitalization for heart failure (HF) is recommended. However, follow-up is suboptimal, especially in lower socioeconomic groups. Patient-centered solutions for facilitating follow-up post-HF hospitalization have not been extensively evaluated.

METHODS AND RESULTS

Face-to-face surveys were conducted between 2015 and 2016 among 83 racially diverse adult patients (61% African American, 34% Caucasian, and 5% Other) hospitalized for HF at a university hospital centered in a low-income area of Columbus, Ohio. Patient perceptions of methods to facilitate follow-up post-HF hospitalization and likelihood of using interventions were investigated using a Likert scale: 1=very much to 5=not at all. Results were analyzed by Wilcoxon signed-rank test with Bonferroni correction. The response rate was 82%. The annual household income was <$35 000 for 49% of patients. An appointment near the patient's home was the most desired intervention (77%), followed by reminder message (73%), transportation to appointment (63%), and elimination of copayment (59%). Interventions most likely to be used if provided were similarly ranked: reminder message (48%), appointment near home (46%), elimination of copay (46%), and transportation to appointment (39%). There were significant differences (P=0.001) in high-ranking interventions related to location (appointment near home, transportation, home appointment) and reminder for visit compared with low-ranking interventions related to time (weekend appointment, appointment after 5 pm) and telemedicine.

CONCLUSIONS

Among this cohort of racially diverse low-income patients hospitalized with HF, an appointment near the patient's home and a reminder message were the most desired interventions to facilitate follow-up. Further study of similar populations nationwide is warranted.

Prevalence of anemia and its influence on hospital readmissions and emergency department visits in outpatients with heart failure

Background:

Anemia is a frequent comorbidity in patients with heart failure. However, the incidence of anemia in patients with heart failure varies widely, and there is limited evidence on the association between anemia and rehospitalization and on the health consequences of anemia in patients with heart failure.

Aims:

We aimed to identify the prevalence of anemia and its influence on hospital readmissions and emergency department visits in outpatients with heart failure.

Methods:

This cross-sectional study included 284 patients with heart failure diagnosed at outpatient cardiology clinics at a tertiary care university hospital in Cheonan, South Korea. We obtained socio-demographic and clinical information, including frequency of readmissions and emergency department visits, using face-to-face interviews and medical record reviews.

Results:

The prevalence of anemia, defined based on World Health Organization guidelines, was 39.1% among patients with heart failure. Anemia was significantly more prevalent among patients with one or more re-admissions or emergency department visits compared with patients with no history of hospital re-admissions or emergency department visits (42.7% vs. 13.9% ( p = 0.001) and 55.1% vs. 34% ( p = 0.002) respectively). Anemia increased the risk of hospital readmission (odds ratio =8.04, 95% confidence interval, 2.19–29.54) and emergency department visit (odds ratio=2.37, 95% confidence interval, 1.22–4.60) in patients with heart failure.

Conclusion:

It is imperative that patients with heart failure presenting with anemia undergo appropriate nursing assessment and intervention. Future prospective studies targeting interventions to improve anemia are required to determine whether anemia influences readmission rates and emergency department visits.

Hospital Readmission and Social Risk Factors Identified from Physician Notes

OBJECTIVE

To evaluate the prevalence of seven social factors using physician notes as compared to claims and structured electronic health records (EHRs) data and the resulting association with 30-day readmissions.

STUDY SETTING

A multihospital academic health system in southeastern Massachusetts.

STUDY DESIGN

An observational study of 49,319 patients with cardiovascular disease admitted from January 1, 2011, to December 31, 2013, using multivariable logistic regression to adjust for patient characteristics.

DATA COLLECTION/EXTRACTION METHODS

All-payer claims, EHR data, and physician notes extracted from a centralized clinical registry.

PRINCIPAL FINDINGS

All seven social characteristics were identified at the highest rates in physician notes. For example, we identified 14,872 patient admissions with poor social support in physician notes, increasing the prevalence from 0.4 percent using ICD-9 codes and structured EHR data to 16.0 percent. Compared to an 18.6 percent baseline readmission rate, risk-adjusted analysis showed higher readmission risk for patients with housing instability (readmission rate 24.5 percent; p < .001), depression (20.6 percent; p < .001), drug abuse (20.2 percent; p = .01), and poor social support (20.0 percent; p = .01).

CONCLUSIONS

The seven social risk factors studied are substantially more prevalent than represented in administrative data. Automated methods for analyzing physician notes may enable better identification of patients with social needs.

Assessing the Performance of a Modified LACE Index (LACE-rt) to Predict Unplanned Readmission After Discharge in a Community Teaching Hospital

BACKGROUND

The LACE index was designed to predict early death or unplanned readmission after discharge from hospital to the community. However, implementing the LACE tool in real time in a teaching hospital required practical unavoidable modifications.

OBJECTIVE

The purpose of this study was to validate the implementation of a modified LACE index (LACE-rt) and test its ability to predict readmission risk using data in a hospital setting.

METHODS

Data from the Canadian Institute for Health Information's Discharge Abstract Database (DAD), the National Ambulatory Care Reporting System (NACRS), and the hospital electronic medical record for one large community hospital in Toronto, Canada, were used in this study. A total of 3855 admissions from September 2013 to July 2014 were analyzed (N=3855) using descriptive statistics, regression analysis, and receiver operating characteristic analysis. Prospectively collected data from DAD and NACRS were linked to inpatient data.

RESULTS

The LACE-rt index was a fair test to predict readmission risk (C statistic=.632). A LACE-rt score of 10 is a good threshold to differentiate between patients with low and high readmission risk; the high-risk patients are 2.648 times more likely to be readmitted than those at low risk. The introduction of LACE-rt had no significant impact on readmission reduction.

CONCLUSIONS

The LACE-rt is a fair tool for identifying those at risk of readmission. A collaborative cross-sectoral effort that includes those in charge of providing community-based care is needed to reduce readmission rates. An eHealth solution could play a major role in streamlining this collaboration.

Socioeconomic and partner status in chronic heart failure: Relationship to exercise capacity, quality of life, and clinical outcomes

BACKGROUND

Prognosis in patients with heart failure (HF) is commonly assessed based on clinical characteristics. The association between partner status and socioeconomic status (SES) and outcomes in chronic HF requires further study.

METHODS

We performed a post hoc analysis of HF-ACTION, which randomized 2,331 HF patients with ejection fraction ≤35% to usual care ± aerobic exercise training. We examined baseline quality of life and functional capacity and outcomes (all-cause mortality/hospitalization) by partner status and SES using adjusted Cox models and explored an interaction with exercise training. Outcomes were examined based on partner status, education level, annual income, and employment.

RESULTS

Having a partner, education beyond high school, an income >$25,000, and being employed were associated with better baseline functional capacity and quality of life. Over a median follow-up of 2.5 years, higher education, higher income, being employed, and having a partner were associated with lower all-cause mortality/hospitalization. After multivariable adjustment, lower mortality was seen associated with having a partner (hazard ratio 0.91, 95% CI 0.81-1.03, P=.15) and more than a high school education (hazard ratio 0.91, CI 0.80-1.02, P=.12), although these associations were not statistically significant. There was no interaction between any of these variables and exercise training on outcomes (all P>.5).

CONCLUSIONS

Having a partner and higher SES were associated with greater functional capacity and quality of life at baseline but were not independent predictors of long-term clinical outcomes in patients with chronic HF. These findings provide information that may be considered as potential variables impacting outcomes.

Psychosocial and nonclinical factors predicting hospital utilization in patients of a chronic disease management program: a prospective observational study

Psychosocial factors such as marital status (odds ratio, 3.52; 95% confidence interval, 1.43-8.69; P = .006) and nonclinical factors such as outpatient nonattendances (odds ratio, 2.52; 95% confidence interval, 1.22-5.23; P = .013) and referrals made (odds ratio, 1.20; 95% confidence interval, 1.06-1.35; P = .003) predict hospital utilization for patients in a chronic disease management program. Along with optimizing patients' clinical condition by prescribed medical guidelines and supporting patient self-management, addressing psychosocial and nonclinical issues are important in attempting to avoid hospital utilization for people with chronic illnesses.

A Correlational Pilot Study of Home Health Nurse Management of Heart Failure Patients and Hospital Readmissions

Heart failure is the leading cause of hospital admissions in patients more than 65 years old. The failure to provide carefully planned care to heart failure patients in the home setting predisposes patients to frequent hospital readmissions due to poor medication compliance, diet, and education of symptom management (Li, Marrow-Howell, & Proctor, 2004). The objective of this pilot study is to show the importance of the home health nurse to follow heart failure patients post hospital discharge. This study uses Lydia Hall's Care, Cure, and Core Theory to show the importance of home health nurse interventions to heart failure patients (Touhy & Birnbach, 2001). According to Stewart and Horowitz (2002), home health multidisciplinary team follow-up may assist patients and caregivers in recognizing the symptoms of the recurring onset of heart failure. The home health team can intervene and assist in management of the symptoms and possibly prevent hospital readmissions.

Health literacy is independently associated with self-care behavior in patients with heart failure

OBJECTIVE

Health literacy (HL) has been recognized as an important concept in patient education and disease management for heart failure (HF). However, previous studies on HL have focused predominantly on the relationships between functional HL (the ability to read and write), comprehensive HL including the ability to access information (communicative HL), and the ability to critically evaluate information (critical HL). Self-care behavior has not been evaluated. This study determined the relationship between functional, communicative, and critical HL and self-care behavior in HF patients.

METHODS

Cross-sectional analysis of the data was completed for HL, HF-related knowledge, and HF-related self-care behaviors. Sociodemographic and clinical characteristics were also assessed. Multivariate linear regression analysis was used to estimate the associations between literacy and self-care behavior.

RESULTS

249 patients with HF were assessed (mean age, 67.7±13.9years). Patients with low HL had poorer knowledge and self-care behavior than those with high HL. Critical HL was an independent determinant of self-care behavior (sβ=-0.154, P=0.027).

CONCLUSIONS

Critical HL was independently associated with self-care behavior in HF patients.

PRACTICE IMPLICATIONS

Effective intervention should be developed to improve patient skills for critically analyzing information and making decisions.

The changes and factors associated with post-discharge self-care behaviors among Chinese patients with heart failure

BACKGROUND

Self-care behavior is essential for achieving good outcomes among patients with heart failure. Understanding the factors associated with self-care over time is important for the provision of appropriate and targeted interventions. However, little is known regarding the changes and factors associated with post-discharge self-care behaviors among Chinese patients with heart failure.

OBJECTIVE

To investigate the changes and factors of self-care behaviors during the first 3 months following discharge among patients with heart failure in the People's Republic of China.

METHODS

A descriptive design with a convenience sample was utilized in this study. Patients (N=128) from two hospitals, West China Hospital and Angjin Hospital, in Chengdu, People's Republic of China, were recruited from June 2013 to June 2014. The instruments used in the study included the following: the Social Support Rating Scale, the Hospital Anxiety and Depression Scale, the Self-Efficacy for Managing Chronic Disease 6-Item Scale, and the European Heart Failure Self-Care Behaviour Scale. Multivariate linear regression analyses were used to identify the factors related to self-care behaviors at baseline, 1 month, and 3 months following discharge.

RESULTS

Patients' self-care behaviors were poor and decreased significantly over time (F=4.09, P<0.05). The factors associated with self-care behaviors at baseline included the following: education level, comorbidities, and social support. The factors related to self-care behaviors at 1 and 3 months following discharge included the following: education level, comorbidities, social support, and self-efficacy. The variances in self-care behaviors attributed to these factors were 43%, 46%, and 42% at baseline, 1 month, and 3 months following discharge, respectively.

CONCLUSION

Additional support should be provided to patients with heart failure with low educational levels and patients with multiple comorbidities. Follow-up, continuity of care, and family caregiver integration following discharge are necessary for the said patients to improve their self-care behaviors and obtain better outcomes.

Reducing hospital readmissions in patients with end-stage kidney disease

ESKD patients have a large burden of disease, with high rates of readmission to hospital compared with the general population. A readmission after an acute index hospital discharge is either planned or unplanned. A proportion of unplanned readmissions are potentially avoidable, and could have been prevented with optimized transitional care. Readmissions pose financial cost to the health care system and emotional cost to patients and caregivers. In other chronic diseases with high readmission risk, such as congestive heart failure, interventions have improved transitional care and reduced readmission risk. In reviewing the existing literature on readmissions in ESKD, the definition and risk of readmission varied widely by study, with many potentially associated factors including comorbid diseases such as anemia and hypoalbuminemia. An ESKD patient's requisite follow-up in the outpatient dialysis facility provides an opportunity to improve transitional care at the time of discharge. Despite this, our review of existing literature found no studies which have tested interventions to reduce the risk of readmission in ESKD patients. We propose a framework to define the determinants of avoidable readmission in ESKD, and use this framework to define a research agenda. Avoidable readmissions in ESKD patients is a topic prime for in-depth study, given the high-risk nature in this patient population, financial and societal costs, and potential for risk modification through targeted interventions.

Clinical Implications of Psychosocial Factors on Pediatric External Fixation Treatment and Recommendations

BACKGROUND

Pediatric limb reconstruction using circular external fixation is a prolonged treatment that interrupts patients' daily function. Patient personality characteristics and expectations may interfere with planned treatment, making complicated medical procedures more challenging. The aims of this study are to identify factors impacting treatment outcome and recommendations for preoperative evaluation and planning.

QUESTIONS/PURPOSES

(1) Are there group differences between patients with and without a preexisting mental health condition(s) in terms of unplanned reoperations? (2) Does the number of surgical procedures before current external fixator placement correlate with the number of unplanned readmissions, unplanned reoperations, and days spent in circular external fixation? (3) Are there group differences between single- compared with two-parent households in terms of inpatient narcotic doses, length of inpatient stay, number of unplanned readmissions, length of readmission(s), and/or unplanned outpatient clinic visits? (4) Does patient age at the time of surgery have an impact on treatment duration, postoperative complications, and treatment outcome?

METHODS

This is a retrospective chart review of pediatric patients who underwent limb reconstruction between 2008 and 2012. Patients with limb length discrepancy > 4 cm or severe angular deformity and who agreed to intervention were treated with circular external fixation. Sixty-seven patients were included; 16 patients were excluded. Statistical analyses included Pearson r correlation and t-test.

RESULTS

Patients who reported preexisting mental health diagnosis (13%) had more unplanned reoperations than patients who did not (no mental health diagnosis; 87%) (mental health diagnosis 3.4 ± 10.3 versus no mental health diagnosis 0.2 ± 0.5 reoperation[s], p = 0.022). Number of previous surgical procedures correlated with number of unplanned reoperations (r = 0.448, p < 0.001), number of unplanned readmissions (r = 0.375, p < 0.001), and number of days in an apparatus (r = 0.275, p = 0.018). Compared with patients from two-parent households, patients from single-parent households received a greater number of inpatient narcotic doses (single-parent 129 ± 118 versus two-parent 73 ± 109 doses, p = 0.039), longer length of inpatient stay (single-parent 73 ± 63 versus two-parent 40 ± 65 days, p = 0.036), more unplanned readmissions (single-parent 0.4 ± 0.1 versus two-parent 0.2 ± 0.2 readmission, p = 0.024), longer hospitalization when readmitted (single-parent 5 ± 11 versus two-parent 1 ± 3 day(s), p = 0.025), and fewer unplanned outpatient visits (single-parent 0.2 ± 0.8 versus two-parent 0.9 ± 1.1 visit, p = 0.005). Apparatus applications with successful outcome had higher average age than those with poor outcome (successful outcome 16 ± 3 versus poor outcome 13 ± 4 years old, p = 0.011). Age at time of apparatus application correlated with number of prescribed antibiotics (r = 0.245, p = 0.036) and number of days in an apparatus (r = 0.233, p = 0.047).

CONCLUSIONS

As a result of the inherent challenges of limb reconstruction, surgical candidates should be preoperatively assessed and mitigating psychosocial factors managed to maximize successful treatment outcome.

LEVEL OF EVIDENCE

Level IV, therapeutic study.

Relation of Acute Heart Failure Hospital Length of Stay to Subsequent Readmission and All-Cause Mortality

Heart failure (HF) hospitalization length of stay (LOS) has been associated with the risk of subsequent readmission and mortality. We identified 19,927 hospitalized patients with HF who were discharged alive from 2008 to 2011 from 3 Kaiser Permanente regions. In adjusted Cox models using LOS 3 to 4 days as the reference category, shorter LOS was not significantly associated with hospital readmissions. LOS of 5 to 10 days was associated with 17% greater risk of readmission within 30 days (hazard ratio [HR] 1.17, 95% confidence interval [CI] 1.07 to 1.28) and 9% greater risk within 1 year (HR 1.09, 95% CI 1.03 to 1.15). LOS of 11 to 29 days was associated with increased readmission risk of 52% at 30 days (HR 1.52, 95% CI 1.30 to 1.76) and 25% at 1 year (HR 1.25, 95% CI 1.16 to 1.35). Mortality risk within 30 days among those with LOS of 1 day was 47% lower (HR 0.53, 95% CI 0.43 to 0.65) and 32% lower at 1 year (HR 0.68, 95% CI 0.62 to 0.74). LOS of 2 days was associated with lower mortality risk of 17% (HR 0.83, 95% CI 0.76 to 0.90) at 1 year. At LOS 5 to 10 days, 30-day and 1-year risk of mortality was increased by 52% (HR 1.52, 95% CI 1.30 to 1.76) and 25% (HR 1.25, 95% CI 1.16 to 1.35), respectively. LOS of 11 to 29 days was associated with 171% higher mortality risk at 30 days (HR 2.71, 95% CI 2.19 to 3.35) and 73% at 1 year (HR 1.73, 95% CI 1.53 to 1.97). Longer LOS during the index HF hospitalization was associated with readmission and mortality within 30 days and 1 year independent of co-morbidities and cardiovascular risk factors. These results suggest that LOS may be a proxy for the severity of HF during the index hospitalization.

Validation of the Readmission Risk Score in Heart Failure Patients at a Tertiary Hospital

BACKGROUND

The Readmission Risk score (RR score) is a software application developed to identify patients at increased risk for readmission. This score was developed to improve on the methodology for 30-day risk-standardized all-cause readmission rates (RSRRs) used by the Centers for Medicare and Medicaid Services for its quality reporting system. However, the utility of the RR score in clinical practice has not been independently validated.

METHODS AND RESULTS

We included patients admitted with the primary discharge diagnosis of congestive heart failure (CHF) from September 2011 to August 2013. Data on individual components of the RR score were obtained by means of detailed chart review. We calculated the RR score of all admissions and examined its ability to predict 30-day all-cause readmission. We repeated the analysis by randomly selecting 1 admission per patient and also by including only those ≥ 65 years old. A total of 1,046 admissions met the inclusion criteria. Of these, 369 (35.28%) were readmitted within 30 days of discharge. The performance of the RR score was poor, with an area under the receiver operating characteristic curve (AUC) of 0.61 (95% confidence interval [CI] 0.57-0.64) for all age groups and 0.59 (95% CI 0.53-0.64) for patients aged ≥ 65 years. The AUC for the RR score was 0.58 (95% CI 0.50-0.65) in a randomly selected patient-level model. However, patients in the highest quartile of RR score were twice as likely to be readmitted as those in the lowest quartile (47.24% vs 24.69%; P < .001). The sensitivity and specificity of the RR score in predicting all cause readmissions were poor.

CONCLUSION

Based on our single-institution data, patients with CHF readmitted within 30 days had a higher RR score than those not readmitted. The ability of the RR score to predict future all-cause readmission was modest at best.