Behavioral Factors and Hospital Admissions/Readmissions in Patients With CHF

Pulmonary Congestion on Lung Ultrasound Predicts Increased Risk of 30-Day Readmission in Heart Failure Patients

OBJECTIVES

Heart failure exacerbations are a common cause of hospitalizations with a high readmission rate. There are few validated predictors of readmission after treatment for acute decompensated heart failure (ADHF). Lung ultrasound (LUS) is sensitive and specific in the assessment of pulmonary congestion; however, it is not frequently utilized to assess for congestion before discharge. This study assessed the association between number of B-lines, on LUS, at patient discharge and risk of 30-day readmission in patients hospitalized for acute decompensated heart failure (ADHF).

METHODS

This was a single-center prospective study of adults admitted to a quaternary care center with a diagnosis of ADHF. At the time of discharge, the patient received an 8-zone LUS exam to evaluate for the presence of B-lines. A zone was considered positive if ≥3 B-lines was present. We assessed the risk of 30-day readmission associated with the number of lung zones positive for B-lines using a log-binomial regression model.

RESULTS

Based on data from 200 patients, the risk of 30-day readmission in patients with 2-3 positive lung zones was 1.25 times higher (95% CI: 1.08-1.45), and in patients with 4-8 positive lung zones was 1.50 times higher (95% CI: 1.23-1.82, compared with patients with 0-1 positive zones, after adjusting for discharge blood urea nitrogen, creatinine, and hemoglobin.

CONCLUSION

Among patients admitted with ADHF, the presence of B-lines at discharge was associated with a significantly increased risk of 30-day readmission, with greater number of lung zones positive for B-lines corresponding to higher risk.

Factors related to early readmissions after acute heart failure: a nested case-control study

AIMS

To describe the main characteristics of patients who were readmitted to hospital within 1 month after an index episode for acute decompensated heart failure (ADHF).

METHODS AND RESULTS

This is a nested case-control study in the ReIC cohort, cases being consecutive patients readmitted after hospitalization for an episode of ADHF and matched controls selected from those who were not readmitted. We collected clinical data and also patient-reported outcome measures, including dyspnea, Minnesota Living with Heart Failure Questionnaire (MLHFQ), Tilburg Frailty Indicator (TFI) and Hospital Anxiety and Depression Scale scores, as well as symptoms during a transition period of 1 month after discharge. We created a multivariable conditional logistic regression model. Despite cases consulted more than controls, there were no statistically significant differences in changes in treatment during this first month. Patients with chronic decompensated heart failure were 2.25 [1.25, 4.05] more likely to be readmitted than de novo patients. Previous diagnosis of arrhythmia and time since diagnosis ≥ 3 years, worsening in dyspnea, and changes in MLWHF and TFI scores were significant in the final model.

CONCLUSION

We present a model with explanatory variables for readmission in the short term for ADHF. Our study shows that in addition to variables classically related to readmission, there are others related to the presence of residual congestion, quality of life and frailty that are determining factors for readmission for heart failure in the first month after discharge.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03300791. First registration: 03/10/2017.

Prevalence and Incidence of Cognitive Impairment and Dementia in Heart Failure - A Systematic Review, Meta-Analysis and Meta-Regression

INTRODUCTION

The burden of cognitive impairment in HF patients is significant and leads to longer hospital stay, higher readmission rates, and increased mortality. This review seeks to synthesize the available studies to determine the prevalence and incidence of cognitive impairment and dementia in HF patients.

METHODS

PubMed, Embase, PsychoINFO and Cochrane databases were systematically searched from their inception through to 3 May 2021. Study and population characteristics, total patients with HF, prevalence of cognitive impairment and dementia in HF patients and cognitive assessment tool were abstracted by two reviewers.

RESULTS

In heart failure patients, overall prevalence for cognitive impairment and dementia was 41.42% (CI) and 19.79% (dementia) respectively. We performed a meta-regression analysis which demonstrated that the risk of cognitive impairment and dementia increased with age.

DISCUSSION

Further research should investigate whether HF accelerates the rate of cognitive decline and the progression of dementia.

Clinical characteristics and risk factors of preventable hospital readmissions within 30 days

Knowledge regarding preventable hospital readmissions is scarce. Our aim was to compare the clinical characteristics of potentially preventable readmissions (PPRs) with non-PPRs. Additionally, we aimed to identify risk factors for PPRs. Our study included readmissions within 30 days after discharge from 1 of 7 hospital departments. Preventability was assessed by multidisciplinary meetings. Characteristics of the readmissions were collected and 23 risk factors were analyzed. Of the 1120 readmissions, 125 (11%) were PPRs. PPRs occurred equally among different departments (p = 0.21). 29.6% of PPRs were readmitted by a practitioner of a different medical specialty than the initial admission (IA) specialist. The PPR group had more readmissions within 7 days (PPR 54% vs. non-PPR 44%, p = 0.03). The median LOS was 1 day longer for PPRs (p = 0.16). Factors associated with PPR were higher age (p = 0.004), higher socio-economic status (p = 0.049), fewer prior hospital admissions (p = 0.004), and no outpatient visit prior to readmission (p = 0.025). This study found that PPRs can occur at any department in the hospital. There is not a single type of patient that can easily be pinpointed to be at risk of a PPR, probably due to the multifactorial nature of PPRs.

Exercise-Based Cardiac Rehabilitation Improves Cognitive Function Among Patients With Cardiovascular Disease

PURPOSE

To investigate the effects of cardiac rehabilitation (CR) exercise training on cognitive performance and whether the changes are associated with alterations in prefrontal cortex (PFC) oxygenation among patients with cardiovascular disease.

METHODS

Twenty (men: n = 15; women: n = 5) participants from an outpatient CR program were enrolled in the study. Each participant completed a cognitive performance test battery and a submaximal graded treadmill evaluation on separate occasions prior to and again upon completion of 18 individualized CR sessions. A functional near-infrared spectroscopy (fNIRS) device was used to measure left and right prefrontal cortex (LPFC and RPFC) oxygenation parameters (oxyhemoglobin [O2Hb], deoxyhemoglobin [HHb], total hemoglobin [tHb], and oxyhemoglobin difference [Hbdiff]) during the cognitive test battery.

RESULTS

Patients showed improvements in cardiorespiratory fitness (+1.4 metabolic equivalents [METs]) and various cognitive constructs. A significant increase in PFC oxygenation, primarily in the LPFC region, occurred at post-CR testing. Negative associations between changes in cognition (executive function [LPFC O2Hb: r = -0.45, P = .049; LPFC tHb: r = -0.49, P = .030] and fluid composite score [RPFC Hbdiff: r = -0.47, P = .038; LPFC Hbdiff: r = -0.45, P = .048]) and PFC changes were detected. The change in cardiorespiratory fitness was positively associated with the change in working memory score (r = 0.55, P = .016).

CONCLUSION

Cardiovascular disease patients enrolled in CR showed significant improvements in multiple cognitive domains along with increased cortical activation. The negative associations between cognitive functioning and PFC oxygenation suggest an improved neural efficiency.

Risk factors of hospitalization for any medical condition among patients with prior emergency department visits for mental health conditions

BACKGROUND

This longitudinal study identified risk factors for frequency of hospitalization among patients with any medical condition who had previously visited one of six Quebec (Canada) emergency departments (ED) at least once for mental health (MH) conditions as the primary diagnosis.

METHODS

Records of n = 11,367 patients were investigated using administrative databanks (2012-13/2014-15). Hospitalization rates in the 12 months after a first ED visit in 2014-15 were categorized as no hospitalizations (0 times), moderate hospitalizations (1-2 times), and frequent hospitalizations (3+ times). Based on the Andersen Behavioral Model, data on risk factors were gathered for the 2 years prior to the first visit in 2014-15, and were identified as predisposing, enabling or needs factors. They were tested using a hierarchical multinomial logistic regression according to the three groups of hospitalization rate.

RESULTS

Enabling factors accounted for the largest percentage of total variance explained in the study model, followed by needs and predisposing factors. Co-occurring mental disorders (MD)/substance-related disorders (SRD), alcohol-related disorders, depressive disorders, frequency of consultations with outpatient psychiatrists, prior ED visits for any medical condition and number of physicians consulted in specialized care, were risk factors for both moderate and frequent hospitalizations. Schizophrenia spectrum and other psychotic disorders, bipolar disorders, and age (except 12-17 years) were risk factors for moderate hospitalizations, while higher numbers (4+) of overall interventions in local community health service centers were a risk factor for frequent hospitalizations only. Patients with personality disorders, drug-related disorders, suicidal behaviors, and those who visited a psychiatric ED integrated with a general ED in a separate site, or who visited a general ED without psychiatric services were also less likely to be hospitalized. Less urgent and non-urgent illness acuity prevented moderate hospitalizations only.

CONCLUSIONS

Patients with severe and complex health conditions, and higher numbers of both prior outpatient psychiatrist consultations and ED visits for medical conditions had more moderate and frequent hospitalizations as compared with non-hospitalized patients. Patients at risk for frequent hospitalizations were more vulnerable overall and had important biopsychosocial problems. Improved primary care and integrated outpatient services may prevent post-ED hospitalization.

Relationship Between Psychological Distress and Cognitive Function Differs as a Function of Obesity Status in Inpatient Heart Failure

Heart failure (HF) is a chronic medical condition rapidly growing in prevalence. Evidence links HF to cognitive decline, obesity, and psychological distress. The current study examined the association between cognitive function and ejection fraction (EF%), anxiety, depression, and obesity in inpatient HF. Patients completed the Generalized Anxiety Disorder 7-Item Scale (GAD-7), Patient Health Questionnaire 9-Item Scale (PHQ-9), and Mini-Cog while hospitalized for HF. Additional demographic and medical information was gathered via chart review. All models controlled for age. Of 117 patients assessed (49% male), 55% (n = 64) were obese. ANCOVA analyses were conducted comparing those with obesity and without on cognitive function: model A included EF%, model B included depression, and model C included anxiety. All three models were significantly related to cognitive function. There was a significant interaction effect of EF% and obesity and of anxiety and obesity to predict Mini-Cog scores. Post hoc partial correlational analyses revealed that anxiety was negatively associated with Mini-Cog scores among only patients without obesity. Depression was not significantly related to cognitive function in either group. However, patients with obesity demonstrated higher depression and anxiety than patients without. Results suggest that at lower EF%, and with higher anxiety, patients without obesity may be at greater risk of cognitive dysfunction than those with obesity. Cognitive dysfunction among HF patients with obesity may be independent of psychological distress. These findings may reflect the “obesity paradox” observed among HF patients, in that patients with obesity may have a different biopsychosocial presentation, which may lead to unexpected clinical outcomes. Further research is necessary to articulate the relationship of obesity and cognitive function in HF.

Impact on Readmission Reduction Among Heart Failure Patients Using Digital Health Monitoring: Feasibility and Adoptability Study

Background

Heart failure (HF) is a condition that affects approximately 6.2 million people in the United States and has a 5-year mortality rate of approximately 42%. With the prevalence expected to exceed 8 million cases by 2030, projections estimate that total annual HF costs will increase to nearly US $70 billion. Recently, the advent of remote monitoring technology has significantly broadened the scope of the physician’s reach in chronic disease management.

Objective

The goal of our program, named the Heart Health Program, was to examine the feasibility of using digital health monitoring in real-world home settings, ascertain patient adoption, and evaluate impact on 30-day readmission rate.

Methods

A digital medicine software platform developed at Mount Sinai Health System, called RxUniverse, was used to prescribe a digital care pathway including the HealthPROMISE digital therapeutic and iHealth mobile apps to patients’ personal smartphones. Vital sign data, including blood pressure (BP) and weight, were collected through an ambulatory remote monitoring system that comprised a mobile app and complementary consumer-grade Bluetooth-connected smart devices (BP cuff and digital scale) that send data to the provider care teams. Care teams were alerted via a Web-based dashboard of abnormal patient BP and weight change readings, and further action was taken at the clinicians’ discretion. We used statistical analyses to determine risk factors associated with 30-day all-cause readmission.

Results

Overall, the Heart Health Program included 58 patients admitted to the Mount Sinai Hospital for HF. The 30-day hospital readmission rate was 10% (6/58), compared with the national readmission rates of approximately 25% and the Mount Sinai Hospital’s average of approximately 23%. Single marital status (P=.06) and history of percutaneous coronary intervention (P=.08) were associated with readmission. Readmitted patients were also less likely to have been previously prescribed angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (P=.02). Notably, readmitted patients utilized the BP and weight monitors less than nonreadmitted patients, and patients aged younger than 70 years used the monitors more frequently on average than those aged over 70 years, though these trends did not reach statistical significance. The percentage of the 58 patients using the monitors at least once dropped from 83% (42/58) in the first week after discharge to 46% (23/58) in the fourth week.

Conclusions

Given the increasing burden of HF, there is a need for an effective and sustainable remote monitoring system for HF patients following hospital discharge. We identified clinical and social factors as well as remote monitoring usage trends that identify targetable patient populations that could benefit most from integration of daily remote monitoring. In addition, we demonstrated that interventions driven by real-time vital sign data may greatly aid in reducing hospital readmissions and costs while improving patient outcomes.

Psychoeducation for chronic cognitive impairment and reduced early readmissions amongst pulmonary inpatients

Patients with chronic pulmonary disease have been found to have among the highest rates of early (30 days) readmissions by the Center for Medicare and Medicaid Services. Proactive identification and psychoeducational intervention for the effect of chronic cognitive impairment on readmission have not been tested in this population. This is a pre-post quality improvement study for service-wide inpatient pulmonary readmission rates in chronic pulmonary disease. We examined the impact of screening patients for likely cognitive impairment and providing patients/families with psychoeducation regarding 'forgetfulness' on 30-day readmission rates on an inpatient pulmonary service. We observed a 50% decline in early readmissions (25.7% > 12.3%) for the inpatient pulmonary service after initiation of screening and psychoeducation of patients/families for improved adherence despite cognitive impairment (t = -2.53, df= 17, p = 0.011). A randomly assigned, controlled clinical trial is warranted.

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.

Identifying Nonclinical Factors Associated With 30-Day Readmission in Patients with Cardiovascular Disease: Protocol for an Observational Study

Background

Cardiovascular disease (CVD) is the leading cause of hospitalization in older adults and high readmission rates have attracted considerable attention as actionable targets to promote efficiency in care and to reduce costs. Despite a plethora of research over the past decade, current strategies to predict readmissions have been largely ineffective and efforts to identify novel clinical predictors have been largely unsuccessful.

Objective

The objective of this study is to examine a wide array of socioeconomic, psychosocial, behavioral, and clinical factors to predict risks of 30-day hospital readmission in cardiovascular patients.

Methods

The study includes patients (aged 18 years and older) admitted for the treatment of cardiovascular-related illnesses at the Duke Heart Center, which is among the nation’s largest and top-ranked cardiovascular care hospitals. The study uses a novel standardized survey to ascertain data on a comprehensive array of patient characteristics that will be linked to their electronic medical records. A series of univariate and multivariate models will be used to estimate the associations between the patient-level factors and 30-day readmissions. The performance of the risk models will be examined based on 2 components of accuracy—model calibration and discrimination—to determine how closely the predicted outcome agrees with the observed (actual) outcome and how well the model distinguishes patients who were readmitted and those who were not. The purpose of this paper is to present the protocol for the implementation of this study.

Results

The study was launched in February 2014 and is actively recruiting patients from the Heart Center. Approximately 550 patients have been enrolled to date and the study is expected to continue recruitment until February 2018. Preliminary results show that participants in the study were aged 63.6 years on average (SD 14.0), predominately male (61.2%), and primarily non-Hispanic white (64.6%) or non-Hispanic black (31.7%). The demographic characteristics of study participants were not significantly different from all patients admitted to the Heart Center during this period with an average age of 65.0 years (SD 15.3) and predominately male (58.6%), non-Hispanic white (62.9%) or non-Hispanic black (31.8%) The integration of the interview data with clinical data from the patient electronic medical records is currently underway. The study has received funding and ethical approval.

Conclusions

Many US hospitals continue to struggle with high readmission rates in patients with cardiovascular disease. The primary objective of this study is to collect and integrate a comprehensive array of patient attributes to develop a powerful yet parsimonious model to stratify risks of rehospitalization in cardiovascular patients. The results of this research also have the potential to identify actionable targets for tailored interventions to improve patient outcomes.

Prospective correlates of early (30 day) readmissions on a Cardiothoracic Surgery Service

Known to vary widely among hospitals for unclear reasons, early readmissions are associated with higher mortality and are suspected to frequently be due to inadequate discharge preparation/planning. It has been previously documented that the strongest and most consistent predictor of early readmissions in CHF patients is chronic cognitive impairment, and compensatory assistance with adherence on discharge improves early readmission rates. Prospective observational study. The present investigation examined multiple putative perioperative predictors of early readmission in a hospitalized Cardiothoracic Surgery Service. A subtest of the Mini-Cog, Short Term Memory, was the strongestunivariate predictor of early readmissions (p < .001), but the overall Mini-Cog (p = .024), Age (p = .045), Number of Admissions over the Preceding Year (p = .036), an Anxiety Scale (p = .035), Years of Education (p = .055) and a Depression Scale (p = .056) also demonstrated covariation. In a Logistic Regression, only Short Term Memory survived as a predictor variable (p = .007), correctly classifying 76% of patients. Chronic cognitive impairment is a predictor of early readmissions in Cardiothoracic patients. A brief bedside exam interpreted in medical context may permit identification of patients requiring familial assistance for adherence on discharge.

Examining the impact of comorbid serious mental illness on rehospitalization among medical and surgical inpatients

OBJECTIVE

Multiple barriers to quality health care may affect the outcomes of postacute treatment for individuals with serious mental illness (SMI). This study examined rehospitalization for medical and surgical inpatients with and without a comorbid diagnosis of SMI which included psychotic disorders, bipolar disorder and major depression.

METHODS

We examined hospital discharge records for medical and surgical inpatients from a large urban health system. Descriptive statistics and logistic regression models compared 7-, 30-, 60-, 90- and 180-day rehospitalization among medical and surgical inpatients with SMI (n=3221) and without an SMI diagnosis (n=70,858).

RESULTS

Within 6 months following discharge, hospitalized medical patients without an SMI diagnosis (34.3%) and with an SMI diagnosis (43.4%) were rehospitalized (P<.001), while surgical patients without an SMI diagnosis (20.3%) and with an SMI diagnosis (30.0%) were rehospitalized (P<.001). Odds of rehospitalization among medical patients were 1.5 to 2.4 times higher for those with an SMI diagnosis compared to those without an SMI diagnosis (P<.001).

CONCLUSIONS

Medical patients with a comorbid psychotic or major mood disorder diagnosis have an increased likelihood of a medical rehospitalization as compared to those without a comorbid SMI diagnosis. These findings support prior literature and suggest the importance of identifying targeted interventions aimed at lowering the likelihood of rehospitalization among inpatients with a comorbid SMI diagnosis.

Impact of Frailty and Sociodemographic Factors on Hospital Admission From an Emergency Department Observation Unit

Understanding factors associated with an increased risk of hospital admission from emergency department (ED) observation units (OUs) could be valuable in disposition decisions. To evaluate the impact of frailty and sociodemographic factors (SDFs) on admission risk, patients in an ED OU were surveyed. Survey measures included SDFs, social habits, and frailty measured by the Katz Index of Independence in Activities of Daily Living. Of 306 surveyed, 18% were admitted and 82% were discharged. Demographics were similar between groups. More admitted patients responded positively to the Katz Index (28% vs 13%, P = .007; odds ratio = 2.73; 95% CI = 1.35-5.51). College graduation and current employment favored the discharge group, while admitted patients were more likely to receive Social Security disability insurance. Frailty remained associated with admission on multivariable analysis. Frailty, disability insurance, and lower education are predictors of admission from an OU and could serve as screening criteria in disposition decisions.

"Alert and Oriented × 3?" Correlates of Mini-Cog Performance in a Post/Nondelirious Intensive Care Unit Sample

BACKGROUND

Cognitive impairment has been found to be a predictor of adverse medical outcomes, including nonadherence, recurrent medical crises resulting in early readmissions, and death.

OBJECTIVE

The Mini-Cog has been proposed for bedside/clinic cognitive testing. Its validity as a measure of central nervous system (CNS) impairment has never been tested against measures of CNS-medical history, CNS scans, selected laboratory findings, observed in-hospital nondelirious memory impairment, or collateral history from family.

METHODS

We observed Mini-Cog performance in 107 post/nondelirious medical intensive care unit patients and tested its association with age, CNS-medical history, CNS scans, selected laboratory findings, and behavioral history (in-hospital observation of memory problems and collateral history from family or significant others).

RESULTS

The overall Mini-Cog covaried with age, various measures of CNS impairment, abnormal laboratory findings, and measures of preadmission "forgetfulness" per family and by in-hospital staff observation. Unique variance in predicting overall Mini-Cog scores included age, positive CNS scan, and behavioral history. Of 91 patients found to be "alert and oriented × 3," 76% were impaired in immediate memory, short-term memory, or clock drawing.

CONCLUSIONS

The Mini-Cog appears to be a brief, yet valid, measure of CNS dysfunction that significantly enhances sensitivity of evaluation at the bedside. Failure to evaluate patients with a formal examination like the Mini-Cog appears to miss up to 76% of patients with moderate cognitive impairment.

Psychiatric comorbidity and 30-day readmissions after hospitalization for heart failure, AMI, and pneumonia

OBJECTIVE

In 2012, the Centers for Medicare and Medicaid Services implemented a policy that penalizes hospitals for "excessive" all-cause hospital readmissions within 30 days after discharge from an index hospitalization for heart failure (HF), acute myocardial infarction (AMI), and pneumonia. The aim of this study was to investigate the influence of psychiatric comorbidities on 30-day all-cause readmissions following hospitalizations for HF, AMI, and pneumonia.

METHODS

Data from 2009-2011 were derived from the HMO Research Network Virtual Data Warehouse of 11 health systems affiliated with the Mental Health Research Network. All index inpatient hospitalizations for HF, AMI, and pneumonia were captured (N=160,169). Psychiatric diagnoses for the year prior to admission were measured. All-cause readmissions within 30 days of discharge were the outcome variable.

RESULTS

Approximately 18% of all individuals with index inpatient hospitalizations for HF, AMI, and pneumonia were readmitted within 30 days. The rate of readmission was 5% greater for individuals with a psychiatric comorbidity compared with those without a psychiatric comorbidity (21.7% and 16.5%, respectively, p<.001). Depression, anxiety, and dementia were associated with more readmissions of persons with index hospitalizations for each general medical condition and for all the conditions combined (p<.05). Substance use and bipolar disorders were linked with higher readmissions for those with initial hospitalizations for HF and pneumonia (p<.05). Readmission rates declined overall from 2009 to 2011.

CONCLUSIONS

Individuals with HF, AMI, and pneumonia experience high rates of readmission, but psychiatric comorbidities appear to increase that risk. Future interventions to reduce readmission should consider adding mental health components.

Successful electronic implementation of discharge referral decision support has a positive impact on 30- and 60-day readmissions

In a quasi-experimental study, decision support software was installed in three hospitals to study the ability to scale (spread) its use from one hospital on paper to three hospitals as software, and to examine the effect on 30- and 60-day readmissions. The Discharge Decision Support System (D2S2) software analyzes data collected by nurses on admission with a proprietary risk assessment tool, identifies patients in need of post-acute care, and alerts discharge planners. On six intervention units, with a concurrent comparison group of 76 units, we examined the implementation experience and compared readmission outcomes before and after implementation. The software implementation finished one month ahead of schedule, and the software performed reliably. High-risk patients admitted in the experimental phase after implementation of D2S2 decision support had significantly fewer 30-day readmissions (a decrease from 22.2% to 9.4%). When high- and low-risk patients were analyzed together, D2S2 achieved a 33% relative reduction in 30-day readmissions (13.1 to 8.8%) and sustained a 37% relative reduction at 60 days. The software, available commercially through RightCare Solutions, was adopted by the health system and remains in use after 22 months. The D2S2 risk assessment tool can be installed easily in existing EHR systems. Future research will focus on how the tool influences discharge decision-making and how its accuracy can be improved in specific settings.

A dynamic view of comorbid depression and generalized anxiety disorder symptom change in chronic heart failure: the discrete effects of cognitive behavioral therapy, exercise, and psychotropic medication

PURPOSE

No previous study has reported upon comorbid depression and anxiety disorders and their treatment in heart failure (HF), which the current study has sought to document.

MATERIALS AND METHODS

Total 29 HF patients under psychiatric management underwent primary depression cognitive behavioral therapy (CBT; n = 15) or primary generalized anxiety disorder (GAD) CBT (n = 14), and participated in a community exercise program and standard physician care. Repeated measures analysis of variance assessed Patient Health Questionnaire (PHQ-9) and GAD-7 symptom change pre- and post-CBT treatment, and assessed the interaction effects of treatment type, exercise, anti-depressant and anxiolytic.

RESULTS

There was a significant time and treatment interaction effect that favored the primary GAD CBT group for reduction in PHQ symptoms (F(1, 24) = 4.52, p = 0.04). Analysis of PHQ-somatic symptoms also showed a significant main effect for participation in the exercise program (F(1, 24) = 4.21, p = 0.05) and a significant time and anxiolytic interaction (F(1, 24) = 3.98, p = 0.05). The average number of cardiac hospital readmissions favored the primary GAD CBT group (p = 0.05).

CONCLUSION

The findings support the use of multifaceted interventions in the rehabilitation of HF patients with comorbid psychiatric needs. Implications for Rehabilitation Comorbid depression and anxiety disorders are a clinical and research focus that deserves more attention in the treatment of heart failure patients. Cognitive behavioral therapy, exercise, and anxiolytic use was associated with significant changes in depression and anxiety though discrete effects were evident. Multifaceted interventions are most likely to be successful in the rehabilitation of HF patients with psychiatric needs.

Reducing avoidable hospital readmissions effectively: a statewide campaign

BACKGROUND

The Reducing Avoidable Readmissions Effectively (RARE) Campaign was designed to engage hospitals and care providers in Minnesota across the continuum of care to prevent avoidable hospital readmissions within 30 days of hospital discharge.

METHODS

Support for hospitals was provided on a one-on-one basis by a RARE resource consultant, as well as through the campaign website and a monthly newsletter. Hospitals had the opportunity to participate in any of three learning collaboratives-Care Transitions Intervention, Project RED (ReEngineered Discharge), or SAFE Transitions of Care. The operating and supporting partners of the RARE Campaign offered monthly webinars for sharing of best practices, and hosted Action Learning Days and celebratory events. Potentially preventable readmissions (PPRs) were tracked over time, and a ratio of actual-to-expected PPRs (A/E PPRs) was calculated for each hospital and reported quarterly.

RESULTS

As of December 31, 2013, 82 hospitals were participating, with 58 (71%) taking part in at least one learning collaborative. More than 7,000 readmissions have been prevented, and patients have spent more than 28,000 nights of sleep in their own beds rather than in a hospital. By the end of September 2013, the A/E PPR ratio was reduced by 12%-from .98 to .86.

CONCLUSIONS

The peer-to-peer networking and collaboration between hospitals facing similar issues, coupled with statewide resources, collaborating Operating Partners, and support for system improvements, have led to improved discharge planning, better management of care transitions and medications, engaged patients and families, and lower readmission rates.