Multimorbidity and the Risk of All-Cause 30-Day Readmission in the Setting of Multidisciplinary Management of Chronic Heart Failure: A Retrospective Analysis of 830 Hospitalized Patients in Australia

Impact of nurse-led interprofessional work in older patients with heart failure and multimorbidity: A retrospective cohort study

Background

The number of patients with multimorbidity has increased due to the aging of the global population. Although the World Health Organization has indicated that multimorbidity will be a major medical problem in the future, the appropriate interventions for patients with multimorbidity are currently unknown. This study aimed to investigate whether nurse-led interprofessional work is associated with improved prognosis in heart failure patients with multimorbidity aged ≥65 years who were admitted in an acute care hospital.

Methods

Patients who were admitted to the cardiovascular medicine ward of an acute care hospital in Osaka, Japan, and underwent nurse-led interprofessional work from April 1, 2017 to March 31, 2020, and from April 1, 2014 to March 31, 2016, were included in this retrospective cohort study. The patients were matched by age, sex, and New York Heart Association classification. The nurse-led interprofessional work was based on a three-step model that incorporates recommendations from international guidelines for multimorbidity. The primary outcome was all-cause mortality.

Results

The mean age of the participants was 80 years, and 62 % were men. The nurse-led interprofessional work group showed a significant difference in all-cause mortality compared with the usual care group (hazard ratio, 0.45; 95 % confidence interval [CI], 0.29-0.69; P < 0.001). Compared with the usual care group, the nurse-led interprofessional work group exhibited a 7 % difference in mortality rate at 1-year post-discharge (P < 0.001).

Conclusions

Nurse-led interprofessional work may reduce the all-cause mortality in older patients with heart failure and multimorbidity.

Person-Centered Models for Cardiovascular Care: A Review of the Evidence: A Scientific Statement From the American Heart Association

Cardiovascular disease remains the leading cause of death and disability in the United States and globally. Disease burden continues to escalate despite technological advances associated with improved life expectancy and quality of life. As a result, longer life is associated with multiple chronic cardiovascular conditions. Clinical guidelines provide recommendations without considering prevalent scenarios of multimorbidity and health system complexities that affect practical adoption. The diversity of personal preferences, cultures, and lifestyles that make up one's social and environmental context is often overlooked in ongoing care planning for symptom management and health behavior support, hindering adoption and compromising patient outcomes, particularly in groups at high risk. The purpose of this scientific statement was to describe the characteristics and reported outcomes in existing person-centered care delivery models for selected cardiovascular conditions. We conducted a scoping review using Ovid MEDLINE, Embase.com, Web of Science, CINAHL Complete, Cochrane Central Register of Controlled Trials through Ovid, and ClinicalTrials.gov from 2010 to 2022. A range of study designs with a defined aim to systematically evaluate care delivery models for selected cardiovascular conditions were included. Models were selected on the basis of their stated use of evidence-based guidelines, clinical decision support tools, systematic evaluation processes, and inclusion of the patient's perspective in defining the plan of care. Findings reflected variation in methodological approach, outcome measures, and care processes used across models. Evidence to support optimal care delivery models remains limited by inconsistencies in approach, variation in reimbursement, and inability of health systems to meet the needs of patients with chronic, complex cardiovascular conditions.

Interaction effects between sleep disorders and depression on heart failure

BACKGROUND

Sleep disorders and depression were recognized as independent risk factors for heart failure, whether their interaction effects also correlated with the risk of heart failure remains elusive. This study was to explore the interaction effects between sleep disorders and depression on the risk of heart failure.

METHODS

This was a cross-sectional study that included data from 39,636 participants in the National Health and Nutritional Examination Survey (NHANES) database. Poisson regression model was applied to evaluate the associations of depression or sleep disorders with heart failure. The relative excess risk of interaction (RERI), attributable proportion of interaction (API) and synergy index (SI) were used to measure whether the interaction effects between depression and sleep disorders on heart failure was statistically significant.

RESULTS

The risk of heart failure was increased in people with sleep disorders [risk ratio (RR) = 1.92, 95% confidence interval (CI): 1.68-2.19) after adjusting for confounders including age, gender, body mass index (BMI), race, marital status, education level, annual family income, drinking history, smoking history, diabetes, hypertension and stroke. The risk of heart failure was elevated in patients with depression after adjusting for confounders (RR = 1.96, 95%CI: 1.65-2.33). Patients with depression and sleep disorders were associated with increased risk of heart failure after adjusting for confounders (RR = 2.76, 95%CI: 2.23-3.42). The CIs of interactive indexes RERI was -0.42 (95%CI: -1.23-0.39), and API was -0.15 (95%CI: -0.46-0.16), which included 0. The CI of interactive indexes SI was 0.81 (95%CI: 0.54-1.21), which contained 1.

CONCLUSION

Depression and sleep disorders were independent risk factors for heart failure but the interaction effects between depression and sleep disorders on the occurrence of heart failure were not statistically different.

Mortality and Readmission Rates After Heart Failure: A Systematic Review and Meta-Analysis

Objective

The current work aimed to examine the rates of and risk factors for mortality and readmission after heart failure (HF).

Setting

A systematic search was carried out in PubMed, the Cochrane Library, and EMBASE to identify eligible reports. The random-effects model was utilized to evaluate the pooled results.

Participants

A total of 27 studies with 515,238 participants were finally meta-analysed. The HF patients had an average age of 76.3 years, with 51% of the sample being male, in the pooled analysis.

Primary and Secondary Outcome Measures

The outcome measures were 30-day and 1-year readmission rates, mortality, and risk factors for readmission and mortality.

Results

The effect sizes for readmission and mortality were estimated as the mean and 95% confidence interval (CI). The estimated 30-day and 1-year all-cause readmission rates were 0.19 (95% CI 0.14-0.23) and 0.53 (95% CI 0.46-0.59), respectively, while the all-cause mortality rates were 0.14 (95% CI 0.10-0.18) and 0.29 (95% CI 0.25-0.33), respectively. Comorbidities were highly prevalent in individuals with HF.

Conclusion

Heart failure hospitalization is followed by high readmission and mortality rates.

Multimorbidity in Patients With Acute Coronary Syndrome Is Associated With Greater Mortality, Higher Readmission Rates, and Increased Length of Stay: A Systematic Review

OBJECTIVE

The aims of this systematic review were to determine the magnitude and impact of multimorbidity (≥2 chronic conditions) on mortality, length of stay, and rates of coronary intervention in patients with acute coronary syndrome (ACS) and to compare the prevalence of cardiovascular versus noncardiovascular multimorbidities.

METHODS

MEDLINE, PubMed, MedlinePlus, EMBASE, OVID, and CINAHL databases were searched for studies published between 2009 and 2019. Eight original studies enrolling patients with ACS and assessing cardiovascular and noncardiovascular comorbid conditions met the inclusion criteria. Study quality was evaluated using the Crowe Critical Appraisal Tool.

RESULTS

The most frequently examined cardiovascular multimorbidities included hypertension, diabetes, heart failure, atrial fibrillation, stroke/transient ischemic attack, coronary heart disease, and peripheral vascular disease; the most frequently examined noncardiovascular multimorbidities included cancer, anemia, chronic obstructive pulmonary disease, renal disease, liver disease, and depression. The prevalence of multimorbidity in the population with ACS is high (25%-95%). Patients with multimorbidities receive fewer evidence-based treatments, including coronary intervention and high-dose statins. Patients with multimorbidities experience higher in-hospital mortality (5%-13.9% vs 2.6%-6.1%), greater average length of stay (5-9 vs 3-4 days), and lower rates of revascularization (9%-14% vs 39%-42%) than nonmultimorbid patients. Women, despite being the minority in all sample populations, exhibited greater levels of multimorbidity than men.

CONCLUSIONS

Multimorbid patients with ACS are at a greater risk for worse outcomes than their nonmultimorbid counterparts. Lack of consistent measurement makes interpretation of the impact of multimorbidity challenging and emphasizes the need for more research on multimorbidity's effects on postdischarge healthcare utilization.

Evaluation of a Clinical Pharmacist Specialist Transition of Care Pathway to Manage Heart Failure Readmissions During a Provider Shortage

BACKGROUND

Evidence supports scheduling early follow-up after heart failure (HF) hospitalization with a provider capable of managing hypervolemia. Often this service is provided by cardiologists or specialty nurse practitioners. Continuity or "familiar" providers may be better positioned to identify decompensating HF in patients who have advanced HF and/or multiple complicating medical problems. The objective of this study was to evaluate whether a clinical pharmacy specialist (CPS) service, covering the role of a "familiar" provider in an advanced HF specialty clinic (AHFC) during a staffing shortage, may prevent readmission metrics from worsening.

METHODS

We evaluated the entire, eligible concurrent cohorts, representing 175 AHFC-CPS and 273 control patient-admissions, respectively. Study- and disease-specific predictors for readmission were assessed. A matched cohort of 202 patient-admissions (101 AHFC-CPS:101 NO-CPS) were evaluated.

RESULTS

Subjects were predominantly white, elderly males. While overall "clinic [performance] profiling" outcomes for readmissions (p = 0.43) and mortality (p = 0.66) did not statistically differ between the AHFC-CPS and NO-CPS groups, an imbalance in severity of illness persisted. A survival curve and analysis were constructed, and the hazard ratio for all-cause mortality was 0.69 (p = 0.033).

CONCLUSIONS

This retrospective project supports the premise that AHFC-CPS intervention may be a suitable alternative to maintain the volume status for AHFC patients during a staffing short-fall. More work needs to be done to determine intervention effect size, predictors for readmission, specifically in advanced cardiovascular disease, and to evaluate CPS opportunities in the provision of independent HF care, particularly for patients with advanced HF.

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

BACKGROUND AND OBJECTIVE

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

METHODS AND RESULTS

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

CONCLUSION

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

The Joint Effect of Physical Multimorbidity and Mental Health Conditions Among Adults in Australia

Introduction

The prevalence of chronic physical and mental health conditions is rising globally. Little evidence exists on the joint effect of physical and mental health conditions on health care use, work productivity, and health-related quality of life in Australia.

Methods

We analyzed data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey, waves 9 (2009), 13 (2013), and 17 (2017). Economic effects associated with multimorbidity were measured through health service use, work productivity loss, and health-related quality of life. We used generalized estimating equations to assess the effect of the association between physical multimorbidity and mental health conditions and economic outcomes.

Results

From 2009 through 2017 the prevalence of physical multimorbidity increased from 15.1% to 16.2%, and the prevalence of mental health conditions increased from 11.2% to 17.3%. The number of physical health conditions was associated with the number of health services used (general practitioner visits, incidence rate ratio = 1.41), work productivity loss (labor force participation, adjusted odds ratio = 0.71), and reduced health-related quality of life (SF-6D score: Coefficient = −0.03). These effects were exacerbated by the presence of mental health conditions and low socioeconomic status.

Conclusion

Having multiple physical health conditions (physical multimorbidity) creates substantial health and financial burdens on individuals, the health system, and society, including increased use of health services, loss of work productivity, and decreased health-related quality of life. The adverse effects of multimorbidity on health, quality of life, and economic well-being are exacerbated by the co-occurrence of mental health conditions and low socioeconomic status.

Persistent Heart Failure Symptoms at Hospital Discharge Predicts 30-Day Clinical Events

Background

The relationship between heart failure (HF) symptoms at hospital discharge and 30-day clinical events is unknown. Variability in HF symptom assessment may affect ability to predict readmission risk.

Objective

The aim of this study was to describe HF symptom profiles and burden at hospital discharge. A secondary aim was to examine the relationship between symptom burden at discharge and 30-day clinical events.

Methods

An exploratory descriptive design was used. Patients with HF (n = 186) were enrolled 24 to 48 hours pre hospital discharge. The HF Somatic Perception Scale quantified 18 HF physical signs and symptoms. Scores were divided into tertiles (0-10, 11-19, and 20 and higher). The Patient Health Questionnaire-9 quantified depressive symptoms. Self-assessed health, comorbid illnesses, and 30-day clinical events were documented. Chi-square and logistic regression were used to examine clinical events.

Results

The sample (n = 186) was predominantly White (87.6%), male (59.1%), elderly (mean [SD], 74.2 [12.5]), and symptomatic (92.5%) at discharge. Heart Failure Somatic Perception Scale scores ranged from 0 to 53, with a mean (SD) of 13.7 (10.1). Symptoms reported most frequently were fatigue (67%), nocturia (62%), need to rest (53%), and inability to do usual activities due to shortness of breath (52%). Thirty-day event rate was 28%, with significant differences between Heart Failure Somatic Perception Scale tertiles (9.4% vs 37.7% in the second and third tertiles, respectively; [chi]22(N = 186) = 16.73, P < .001). Heart Failure Somatic Perception Scale tertile 2 or 3 (odds ratio [OR], 5.7; P = .003; and OR, 4.3; P = .021), self-assessed health (OR, 2.6; P = .029), and being in a relationship predicted clinical events.

Conclusions

Heart failure symptom burden at discharge predicted 30-day clinical events. Comprehensive symptom assessment is important when determining readmission risk.

Multimorbidity and healthcare resource utilization in Switzerland: a multicentre cohort study

BACKGROUND

Multimorbidity is associated with higher healthcare resource utilization, but we lack data on the association of specific combinations of comorbidities with healthcare resource utilization. We aimed to identify the combinations of comorbidities associated with high healthcare resource utilization among multimorbid medical inpatients.

METHODS

We performed a multicentre retrospective cohort study including 33,871 multimorbid (≥2 chronic diseases) medical inpatients discharged from three Swiss hospitals in 2010-2011. Healthcare resource utilization was measured as 30-day potentially avoidable readmission (PAR), prolonged length of stay (LOS) and difference in median LOS. We identified the combinations of chronic comorbidities associated with the highest healthcare resource utilization and quantified this association using regression techniques.

RESULTS

Three-fourths of the combinations with the strongest association with PAR included chronic kidney disease. Acute and unspecified renal failure combined with solid malignancy was most strongly associated with PAR (OR 2.64, 95%CI 1.79;3.90). Miscellaneous mental health disorders combined with mood disorders was the most strongly associated with LOS (difference in median LOS: 17 days) and prolonged LOS (OR 10.77, 95%CI 8.38;13.84). The number of chronic diseases was strongly associated with prolonged LOS (OR 9.07, 95%CI 8.04;10.24 for ≥10 chronic diseases), and to a lesser extent with PAR (OR 2.16, 95%CI 1.75;2.65 for ≥10 chronic diseases).

CONCLUSIONS

Multimorbidity appears to have a higher impact on LOS than on PAR. Combinations of comorbidities most strongly associated with healthcare utilization included kidney disorders for PAR, and mental health disorders for LOS.

Patterns of multimorbidity associated with 30-day readmission: a multinational study

BACKGROUND

Multimorbidity is associated with higher healthcare utilization; however, data exploring its association with readmission are scarce. We aimed to investigate which most important patterns of multimorbidity are associated with 30-day readmission.

METHODS

We used a multinational retrospective cohort of 126,828 medical inpatients with multimorbidity defined as ≥2 chronic diseases. The primary and secondary outcomes were 30-day potentially avoidable readmission (PAR) and 30-day all-cause readmission (ACR), respectively. Only chronic diseases were included in the analyses. We presented the OR for readmission according to the number of diseases or body systems involved, and the combinations of diseases categories with the highest OR for readmission.

RESULTS

Multimorbidity severity, assessed as number of chronic diseases or body systems involved, was strongly associated with PAR, and to a lesser extend with ACR. The strength of association steadily and linearly increased with each additional disease or body system involved. Patients with four body systems involved or nine diseases already had a more than doubled odds for PAR (OR 2.35, 95%CI 2.15-2.57, and OR 2.25, 95%CI 2.05-2.48, respectively). The combinations of diseases categories that were most strongly associated with PAR and ACR were chronic kidney disease with liver disease or chronic ulcer of skin, and hematological malignancy with esophageal disorders or mood disorders, respectively.

CONCLUSIONS

Readmission was associated with the number of chronic diseases or body systems involved and with specific combinations of diseases categories. The number of body systems involved may be a particularly interesting measure of the risk for readmission in multimorbid patients.

Have Traditional Heart Failure Management Programs Reached Their "Use by" Date? Time to Apply More Nuanced Care

PURPOSE OF REVIEW

To determine the current evidence supporting the otherwise proven heart failure management programs (HFMPs) in the setting of an increasingly older and more complex patient population.

RECENT FINDINGS

Attempts to replace proven face-to-face, multidisciplinary management of HF with remote management techniques (including telemedicine and implantable remote monitoring devices) have yielded mixed results. This may well reflect the clinical cascade effect of greater surveillance paradoxically leading to worse health outcomes as well as a narrow focus on HF alone in patients with clinically significant multimorbidity. Concurrently, there is preliminary evidence that the increasing phenomenon of HF and multimorbidity in older patients is undermining the otherwise positive impact of "traditional" HFMPs. A more nuanced approach to determining who would benefit from what form of HF management, including the integration of remote surveillance techniques, is required.

Predictive biomarkers for death and rehospitalization in comorbid frail elderly heart failure patients

Background

Heart failure (HF) is associated with a high rate of readmissions within 30 days post-discharge and in the following year, especially in frail elderly patients. Biomarker data are scarce in this high-risk population. This study assessed the value of early post-discharge circulating levels of ST2, NT-proBNP, CA125, and hs-TnI for predicting 30-day and 1-year outcomes in comorbid frail elderly patients with HF with mainly preserved ejection fraction (HFpEF).

Methods

Blood samples were obtained at the first visit shortly after discharge (4.9 ± 2 days). The primary endpoint was the composite of all-cause mortality or HF-related rehospitalization at 30 days and at 1 year. All-cause mortality alone at one year was also a major endpoint. HF-related rehospitalizations alone were secondary end-points.

Results

From February 2014 to November 2016, 522 consecutive patients attending the STOP-HF Clinic were included (57.1% women, age 82 ± 8.7 years, mean Barthel index 70 ± 25, mean Charlson comorbidity index 5.6 ± 2.2). The composite endpoint occurred in 8.6% patients at 30 days and in 38.5% at 1 year. In multivariable analysis, ST2 [hazard ratio (HR) 1.53; 95% CI 1.19–1.97; p = 0.001] was the only predictive biomarker at 30 days; at 1 year, both ST2 (HR 1.34; 95% CI 1.15–1.56; p < 0.001) and NT-proBNP (HR 1.19; 95% CI 1.02–1.40; p = 0.03) remained significant. The addition of ST2 and NT-proBNP into a clinical predictive model increased the AUC from 0.70 to 0.75 at 30 days (p = 0.02) and from 0.71 to 0.74 at 1 year (p < 0.05). For all-cause death at 1 year, ST2 (HR 1.50; 95% CI 1.26–1.80; p < 0.001), and CA125 (HR 1.41; 95% CI 1.21–1.63; p < 0.001) remained independent predictors in multivariable analysis. The addition of ST2 and CA125 into a clinical predictive model increased the AUC from 0.74 to 0.78 (p = 0.03). For HF-related hospitalizations, ST2 was the only predictive biomarker in multivariable analyses, both at 30 days and at 1 year.

Conclusions

In a comorbid frail elderly population with HFpEF, ST2 outperformed NT-proBNP for predicting the risk of all-cause mortality or HF-related rehospitalization. ST2, a surrogate marker of inflammation and fibrosis, may be a better predictive marker in high-risk HFpEF.

Electronic supplementary material

The online version of this article (10.1186/s12877-018-0807-2) contains supplementary material, which is available to authorized users.