Diagnoses and timing of 30-day readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia

A proposed method for identifying Interfacility transfers in Medicare claims data

OBJECTIVE

To develop a method of consistently identifying interfacility transfers (IFTs) in Medicare Claims using patients with ST-Elevation Myocardial Infarction (STEMI) as an example.

DATA SOURCES/STUDY SETTING

100% Medicare inpatient and outpatient Standard Analytic Files and 5% Carrier Files, 2011-2020.

STUDY DESIGN

Observational, cross-sectional comparison of patient characteristics between proposed and existing methods.

DATA COLLECTION/EXTRACTION METHODS

We limited to patients aged 65+ with STEMI diagnosis using both proposed and existing methods.

PRINCIPAL FINDINGS

We identified 62,668 more IFTs using the proposed method (86,128 versus 23,460). A separately billable interfacility ambulance trip was found for more IFTs using the proposed than existing method (86% vs. 79%). Compared with the existing method, transferred patients under the proposed method were more likely to live in rural (p < 0.001) and lower income (p < 0.001) counties and were located farther away from emergency departments, trauma centers, and intensive care units (p < 0.001).

CONCLUSIONS

Identifying transferred patients based on two consecutive inpatient claims results in an undercount of IFTs and under-represents rural and low-income patients.

Machine learning-based model for worsening heart failure risk in Chinese chronic heart failure patients

AIMS

This study aims to develop and validate an optimal model for predicting worsening heart failure (WHF). Multiple machine learning (ML) algorithms were compared, and the results were interpreted using SHapley Additive exPlanations (SHAP). A clinical risk calculation tool was subsequently developed based on these findings.

METHODS AND RESULTS

This nested case-control study included 200 patients with chronic heart failure (CHF) from the China-Japan Friendship Hospital (September 2019 to December 2022). Sixty-five variables were collected, including basic information, physical and chemical examinations, and quality of life assessments. WHF occurrence within a 3-month follow-up was the outcome event. Variables were screened using LASSO regression, univariate analysis, and comparison of key variables in multiple ML models. Eighty per cent of the data was used for training and 20% for testing. The best models were identified by integrating nine ML algorithms and interpreted using SHAP, and to develop a final risk calculation tool. Among participants, 68 (34.0%) were female, with a mean age (standard deviation, SD) of 68.57 (12.80) years. During the follow-up, 60 participants (30%) developed WHF. N-terminal pro-brain natriuretic peptide (NT-proBNP), creatinine (Cr), uric acid (UA), haemoglobin (Hb), and emotional area score on the Minnesota Heart Failure Quality of Life Questionnaire were critical predictors of WHF occurrence. The random forest (RF) model was the best model to predict WHF with an area under the curve (AUC) (95% confidence interval, CI) of 0.842 (0.675-1.000), accuracy of 0.775, sensitivity of 0.900, specificity of 0.833, negative predictive value of 0.800, and positive predictive value of 0.600 for the test set. SHAP analysis highlighted NT-proBNP, UA, and Cr as significant predictors. An online risk predictor based on the RF model was developed for personalized WHF risk assessment.

CONCLUSIONS

This study identifies NT-proBNP, Cr, UA, Hb, and emotional area scores as crucial predictors of WHF in CHF patients. Among the nine ML algorithms assessed, the RF model showed the highest predictive accuracy. SHAP analysis further emphasized NT-proBNP, UA, and Cr as the most significant predictors. An online risk prediction tool based on the RF model was subsequently developed to enhance early and personalized WHF risk assessment in clinical settings.

Knowing the Patient: Understanding Readmission Reasons in Complex Heart Failure

BACKGROUND

Heart failure (HF) is a complex problem characterized by frequent hospitalizations and high 30-day readmission rates. Researchers studying HF readmission report that patients and clinicians have different perspectives on readmission and preventability when unadjusted for disease severity.

OBJECTIVE

The aim of this study was to gather patient, caregiver, nurse, and physician subjective reason(s) for 30-day HF readmission and perceptions of preventability with contextual factors to evaluate differences.

METHODS

A convergent, parallel, mixed-methods design was used with interviews and chart reviews to evaluate contextual factors from the current and index hospital stay. Adults readmitted within 30 days of a previous inpatient stay with a coded HF diagnosis were enrolled and interviewed, followed by interviews with associated caregivers, attending physicians, and assigned nurses.

RESULTS

Interviews were conducted with patients (n = 44), caregivers (n = 6), physicians (n = 24), and nurses (n = 44). Readmissions were emergent/urgent (95%) and occurred within 14.9 days (SD, 8.1; 2-28 days) on average after discharge. Index stay coding revealed that most patients (73%) had a high severity of illness (73%) and risk of mortality (68%). Heart failure stage was inconsistently documented. Patients reported acute symptomatic reasons, with only 32% describing readmission as preventable. Physicians reported diagnostic reasons, 38% of which were preventable. Nurses reported behavioral reasons, with 59% being preventable. Patient/clinician agreement on readmission reason was low (30%).

CONCLUSIONS

Patient/clinician perspectives on readmission varied among the patients with complex HF. Care planning based on HF stage and other contextual factors is needed to ensure a shared understanding of disease severity and a tailored symptom management approach to prevent readmission.

After ACS, telemedicine-based care with remote patient monitoring vs. usual care reduced hospital readmissions at 6 mo

SOURCE CITATION

Alshahrani NS, Hartley A, Howard J, et al. Randomized trial of remote assessment of patients after an acute coronary syndrome. J Am Coll Cardiol. 2024;83:2250-2259. 38588928.

Burden and predictors of thirty-day readmission in patients with NSTEMI: a retrospective analysis of the 2020 NRD database

BACKGROUND

Non-ST-segment elevation myocardial infarction (NSTEMI) is an entity which was defined as a type of a coronary syndrome with positive cardiac biomarker of myocardial necrosis with no ST-segment elevation in ECG. Currently, the centers for Medicare and Medicaid services (CMS) Hospital readmission reduction program assistance risk-adjusted 30-day readmission rates for five major clinical entities which includes acute myocardial infarction.

METHODS

We performed this retrospective study to look into the current burden and predictors of NSTEMI readmission. Data were obtained from the Nationwide Readmission Database for the year 2020. We analyzed data on hospital readmission of 336 620 adults who were admitted for NSTEMI.

RESULTS

The 30-day readmission rate was 13.5% with NSTEMI being the most common cause of readmission. Mortality was higher in readmitted patients compared to index admission (5.4 vs 3.6%, P = 0.000). Higher risk of readmission was associated with female sex, higher Charlson comorbidity index, and longer length of stay. Lower risk of admission was seen in patients from smaller communities, patients who underwent percutaneous coronary intervention, and discharged to rehabilitation facilities.

CONCLUSION

Although we found an improvement in readmission rates compared to prior studies, about 13% of patients continue to get readmitted within 30 days causing significant cost to the healthcare system and often these patients have worse outcomes. We need continuing large-scale studies to identify quality measures to prevent readmission, improve mortality during readmission, and make better use of financial resources.

Causes and predictors of recurrent unplanned hospital admissions in heart failure patients: a cohort study

Despite progress in therapy, heart failure (HF) inflicts a heavy burden of hospital admissions. In this study, we identified among 1360 community-dwelling HF patients (mean age 70.7 ± 11.3 years, 72.5% men) subgroups sharing similar profiles of unplanned hospital admissions, based on the admission causes and frequency of each cause. Hospital discharge summaries were reviewed for the main admission cause. Patient subgroups were identified via cluster analysis. We investigated baseline predictors associated with these subgroups, using multinomial logistic models. During 3421 patient-years, there were 5192 hospital admissions, of which 4252 (82%) were unplanned. We identified five patient subgroups (clusters 1-5) with distinctive hospitalization profiles. HF accounted for approximately one-third of admissions in the first patient cluster (23% of the patient sample). In contrast, patients in the second cluster (39% of the patient sample) were hospitalized for various reasons, with no single prominent admission cause identified. The other three clusters, comprising 16% of the patient sample, accounted for 42% of all unplanned hospitalizations. While patients in the third cluster were hospitalized mainly due to ischemic heart disease and arrhythmia, patients in the fourth and fifth clusters shared a high burden of recurrent HF admissions. The five patient clusters differed by baseline predictors, including age, functional capacity, comorbidity burden, hemoglobin, and cause of HF. HF patients differ significantly in the causes and overall burden of unplanned hospitalizations. The patient subgroups identified and predictors for these subgroups may guide personalized interventions to reduce the burden of unplanned hospitalizations among HF patients. Trial registration: ClinicalTrials.gov, NCT00533013. Registered 20 September 2007. https://clinicaltrials.gov/study/NCT00533013 .

An emergency department transitional care team prevents unnecessary hospitalization of older adults: a mixed methods study

INTRODUCTION

Older adults with acute functional decline may visit emergency departments (EDs) for medical support despite a lack of strict medical urgency. The introduction of transitional care teams (TCT) at the ED has shown promise in reducing avoidable admittances. However, the optimal composition and implementation of TCTs are still poorly defined. We evaluated the effect of TCTs consisting of an elderly care physician (ECP) and transfer nurse versus a transfer nurse only on reducing hospital admissions, as well as the experience of patients and caregivers regarding quality of care.

METHODS

We assessed older adults (≥ 65 years) at the ED with acute functional decline but no medical indication for admission. Data were collected on type and post-ED care, and re-visits were evaluated over a 30-day follow-up period. Semi-structured interviews with stakeholders were based on the Consolidated-Framework-for-Implementation-Research, while patient and caregiver experiences were collected through open-ended interviews.

RESULTS

Among older adults (N = 821) evaluated by the TCT, ECP and transfer nurse prevented unnecessary hospitalization at the same rate (81.2%) versus a transfer nurse alone (79.5%). ED re-visits were 15.6% (ECP and transfer nurse) versus 13.5%. The interviews highlighted the added value of an ECP, which consisted of better staff awareness, knowledge transfer and networking with external organizations. The TCT intervention in general was broadly supported, but adaptability was regarded as an important prerequisite.

CONCLUSION

Regardless of composition, a TCT can prevent unnecessary hospitalization of older adults without increasing ED re-visiting rates, while the addition of an ECP has a favourable impact on patient and professional experiences.

Characteristics and Factors of 30-Day Readmissions after Hospitalization for Acute Heart Failure in China

Background

Patients with acute heart failure (HF) are at high risk of 30-day readmission. Little is known about the characteristics and associated factors of 30-day readmissions among patients with acute HF in China.

Methods

We enrolled consecutive patients hospitalized for acute HF and discharged from 52 hospitals in China from August 2016 to May 2018. We describe the rate of 30-day readmission, the time interval from discharge to readmission, and the causes of readmission. We also analyzed the factors associated with readmission risk by fitting multivariate Cox proportional hazards models.

Results

We included 4875 patients with a median age of 67 years (interquartile range, 57-75), 3045 (62.5%) of whom were male. Within 30 days after discharge, 613 (12.6%) patients were readmitted for all causes, with a median from discharge to readmission of 12 (6-21) days. Most readmissions were attributed to cardiovascular causes (71.1%) and 60.0% to HF-related causes. Readmission occurred within 14 days of discharge in more than half of the patients (56.4%). Diabetes (hazard ratio [HR]: 1.25, 95% confidence interval [95% CI]: 1.06-1.50), anemia (HR: 1.26, 95% CI: 1.03-1.53), high New York Heart Association classification (HR: 1.48, 95% CI: 1.08-2.01), elevated N-terminal pro-B type natriuretic peptide (HR: 1.67, 95% CI: 1.24-2.25), and high-sensitivity cardiac troponin T (HR: 1.26, 95% CI: 1.01-1.58) were associated with increased risks of readmission. High systolic blood pressure (HR: 0.56, 95% CI: 0.38-0.81) and Kansas City Cardiomyopathy Questionnaire-12 scores (HR: 0.64, 95% CI: 0.44-0.94) were associated with decreased risk of readmission.

Conclusions

In China, almost one in eight patients with acute HF were readmitted within 30 days after discharge, mainly due to cardiovascular reasons, and approximately three-fifths of the readmissions occurred in the first 14 days. Both clinical and patient-centered characteristics were associated with readmission.

Thirty-day hospital readmission in females with acute heart failure and breast cancer: A retrospective cohort study from national readmission database

BACKGROUND

Breast Cancer and cardiovascular diseases are amongst the two leading causes of mortality in the United States, and the two conditions are connected in part because of recognized cardiotoxicity of cancer treatments. The aim of this study is to investigate the predictors risk factors for thirty-day readmission in female breast cancer survivors presenting with acute heart failure.

METHODS

This is a retrospective cohort study of acute heart failure (AHF) hospitalization in female patients with breast cancer in 2019 using the National Readmission Database (NRD), which is the largest publicly available all-payer inpatient readmission database in the United States. Our study sample included adult female patients aged 18 years and older. The primary outcome of interest was the rate of 30- day readmission.

RESULTS

In 2019, there were 8332 total index admissions for AHF in females with breast cancer and 7776 patients were discharged alive. The mean age was 74.4 years (95% CI: 74, 74.7). The percentage of readmission at 30 days among those discharged alive was 21.8% (n = 1699). Hypertensive heart disease with chronic kidney disease accounted for the majority of readmission in AHF with breast cancer followed by sepsis, acute kidney injury, respiratory failure, pneumonia, and atrial fibrillation. Demographic factors including higher burden of comorbidities predict readmission. The total in-hospital mortality in index admission was 6.67% (n = 556) and for readmitted patients was 8.77% (n = 149). The mean length of stay for index admission was 7.5 days (95% CI: 7.25, 7.75).

CONCLUSIONS

Readmission of female breast cancer survivors presenting with AHF is common and largely be attributed to high burden of comorbidities including hypertension, and chronic kidney disease. A focus on close outpatient follow-up will be beneficial in lowering readmissions.

Explainable machine learning for predicting 30-day readmission in acute heart failure patients

We aimed to develop a machine-learning based predictive model to identify 30-day readmission risk in Acute heart failure (AHF) patients. In this study 2232 patients hospitalized with AHF were included. The variance inflation factor value and 5-fold cross-validation were used to select vital clinical variables. Five machine learning algorithms with good performance were applied to develop models, and the discrimination ability was comprehensively evaluated by sensitivity, specificity, and area under the ROC curve (AUC). Prediction results were illustrated by SHapley Additive exPlanations (SHAP) values. Finally, the XGBoost model performs optimally: the greatest AUC of 0.763 (0.703-0.824), highest sensitivity of 0.660, and high accuracy of 0.709. This study developed an optimal XGBoost model to predict the risk of 30-day unplanned readmission for AHF patients, which showed more significant performance compared with traditional logistic regression (LR) model.

Wireless and Battery-Free Sensor for Interstitial Fluid Pressure Monitoring

Congestive heart failure (CHF) is a fatal disease with progressive severity and no cure; the heart's inability to adequately pump blood leads to fluid accumulation and frequent hospital readmissions after initial treatments. Therefore, it is imperative to continuously monitor CHF patients during its early stages to slow its progression and enable timely medical interventions for optimal treatment. An increase in interstitial fluid pressure (IFP) is indicative of acute CHF exacerbation, making IFP a viable biomarker for predicting upcoming CHF if continuously monitored. In this paper, we present an inductor-capacitor (LC) sensor for subcutaneous wireless and continuous IFP monitoring. The sensor is composed of inexpensive planar copper coils defined by a simple craft cutter, which serves as both the inductor and capacitor. Because of its sensing mechanism, the sensor does not require batteries and can wirelessly transmit pressure information. The sensor has a low-profile form factor for subcutaneous implantation and can communicate with a readout device through 4 layers of skin (12.7 mm thick in total). With a soft silicone rubber as the dielectric material between the copper coils, the sensor demonstrates an average sensitivity as high as -8.03 MHz/mmHg during in vitro simulations.

Intensive therapeutic education strategy for patients with acute heart failure (EduStra-HF): Design of a randomized controlled trial

BACKGROUND

Heart failure is associated with reduced quality of life, hospitalizations, death and high healthcare costs. Despite care improvements, the rehospitalization rate after an acute heart failure episode, especially for acute heart failure, remains high.

METHODS

The Education Strategy for patients with acute Heart Failure (EduStra-HF; ClinicalTrials.gov Identifier NCT03035123) study will randomize patients admitted for acute heart failure in six French hospitals to usual care (control) or therapeutic education (intervention). All patients will be evaluated at baseline and will meet with a therapeutic education nurse before discharge. Those in the usual care arm will have standard appointments with their cardiologist and general practitioner. Those in the intervention arm will have an intensive follow-up schedule of phone calls, home visits and text messages from the therapeutic education nurses, plus cardiologist visits. Patients will be stratified by discharge location (home or cardiac rehabilitation centre) before randomization, and will be followed up for 1 year. The primary outcome will be the readmission rates for acute heart failure during 1 year in the two groups. Secondary outcomes will include: quality of life; time from inclusion to first readmission for acute heart failure; non-heart failure cardiovascular rehospitalization rates; length of stay for heart failure; cardiovascular and all-cause death; rates of patients receiving optimal medical therapies; evolution of knowledge about heart failure; and cost-effectiveness.

CONCLUSIONS

This study will assess the efficacy and feasibility of a standardized management strategy for the care and follow-up of patients discharged after hospitalization for acute heart failure. The EduStra-HF strategy will combine various nurse care methods to help prevent rehospitalization.

App-based telerehabilitation program for older adults on waiting list for physiotherapy after hospital discharge: a feasibility pragmatic randomized trial

BACKGROUND

Inactivity while waiting for outpatient physiotherapy worsens the physical deconditioning of older adults after hospital discharge. Exercise programs can minimize the progression of deconditioning. In developing countries, telerehabilitation for older adults on the waiting list is still in the early stages. This study aimed to evaluate the feasibility of the study procedures of a telerehabilitation program for older adults waiting for outpatient physiotherapy after hospital discharge.

METHODS

This pragmatic randomized controlled trial recruited older adults (≥ 60 years) with several clinical diagnoses on the waiting list for outpatient physiotherapy in the Brazilian public health system after hospital discharge. The telerehabilitation group (n = 17) received a personalized program of multicomponent remote exercises using a smartphone app. The control group (n = 17) followed the usual waiting list. We assessed recruitment and dropout rates, safety, adherence, and satisfaction. The preliminary effects were verified on clinical outcomes.

RESULTS

We recruited 5.6 older adults monthly; dropouts were 12%. No serious adverse events were associated with the telerehabilitation program. The weekly adherence was 2.85 (1.43) days, and in 63.3% of the weeks the participants were enrolled, they performed the exercise program at least twice a week. Participants rated the telerehabilitation program as 9.71 (0.21), and the safety of remote exercises without professional supervision as 8.6 (2.2) on a 0-10 scale.

CONCLUSIONS

The telerehabilitation program using a smartphone app was safe and presented high participants' satisfaction and adequate adherence, recruitment, and dropout rates. Therefore, the definitive study can be conducted with few modifications.

TRIAL REGISTRATION

Brazilian Registry of Clinical Trials (ReBEC), RBR-9243v7. Registered on 24 August 2020. https://ensaiosclinicos.gov.br/rg/RBR-9243v7 .

Candent issues in pneumonia. Reflections from the Fifth Annual Meeting of Spanish Experts 2023

Pneumonia is a multifaceted illness with a wide range of clinical manifestations, degree of severity and multiple potential causing microorganisms. Despite the intensive research of recent decades, community-acquired pneumonia remains the third-highest cause of mortality in developed countries and the first due to infections; and hospital-acquired pneumonia is the main cause of death from nosocomial infection in critically ill patients. Guidelines for management of this disease are available world wide, but there are questions which generate controversy, and the latest advances make it difficult to stay them up to date. A multidisciplinary approach can overcome these limitations and can also aid to improve clinical results. Spanish medical societies involved in diagnosis and treatment of pneumonia have made a collaborative effort to actualize and integrate last expertise about this infection. The aim of this paper is to reflect this knowledge, communicated in Fifth Pneumonia Day in Spain. It reviews the most important questions about this disorder, such as microbiological diagnosis, advances in antibiotic and sequential therapy, management of beta-lactam allergic patient, preventive measures, management of unusual or multi-resistant microorganisms and adjuvant or advanced therapies in Intensive Care Unit.

Prevalence of Healthcare Barriers Among US Adults With Chronic Liver Disease Compared to Other Chronic Diseases

Background and Aims

The extent of healthcare barriers and its association with acute care use among adults with chronic liver disease (CLD) relative to other chronic conditions remains understudied. We compared the probability of barriers and recurrent acute care use among persons with CLD and persons with chronic obstructive pulmonary disease (COPD) and/or cardiovascular disease (CVD).

Methods

We assembled a population-based, cross-sectional study using pooled self-reported National Health Interview Survey data (2011-2017) among community-dwelling persons. Probability of barriers by disease group (CLD vs COPD/CVD) was assessed using hurdle negative binomial regression.

Results

The sample included 47,037 adults (5062 with CLD, 41,975 with COPD/CVD). The CLD group was younger (median age 55 vs 62 years) and included more Hispanics (17.5% vs 8.6%) and persons with poverty (20.1% vs 15.3%) than the COPD/CVD group. More respondents with CLD vs COPD/CVD reported barriers (44.7% vs 34.4%), including unaffordability (27.5% vs 18.8%), transportation-related (6.1% vs 4.1%), and organizational barriers at entry to (17.6% vs 13.0%) and within healthcare (19.5% vs 14.2%). While adults with CLD were more likely to experience at least 1 barrier (adjusted incident rate ratio, 1.12 [1.01-1.24], P = .03), they were not associated with more (1.05 [1.00-2.71], P = .06). Probability of recurrent acute care use was associated with more healthcare barriers.

Conclusion

Findings from this nationally representative sample of over 43 million US adults reveal that persons with CLD have increased probability of healthcare barriers, likely related to their higher prevalence of socioeconomic vulnerabilities compared to persons with COPD/CVD. CLD warrants attention as a priority condition in public policies that direct resources towards high-risk populations.

Machine learning-based analysis of non-invasive measurements for predicting intracardiac pressures

Aims

Early detection of congestion has demonstrated to improve outcomes in heart failure (HF) patients. However, there is limited access to invasively haemodynamic parameters to guide treatment. This study aims to develop a model to estimate the invasively measured pulmonary capillary wedge pressure (PCWP) using non-invasive measurements with both traditional statistics and machine learning (ML) techniques.

Methods and results

The study involved patients undergoing right-sided heart catheterization at Erasmus MC, Rotterdam, from 2017 to 2022. Invasively measured PCWP served as outcomes. Model features included non-invasive measurements of arterial blood pressure, saturation, heart rate (variability), weight, and temperature. Various traditional and ML techniques were used, and performance was assessed using R2 and area under the curve (AUC) for regression and classification models, respectively. A total of 853 procedures were included, of which 31% had HF as primary diagnosis and 49% had a PCWP of 12 mmHg or higher. The mean age of the cohort was 59 ± 14 years, and 52% were male. The heart rate variability had the highest correlation with the PCWP with a correlation of 0.16. All the regression models resulted in low R2 values of up to 0.04, and the classification models resulted in AUC values of up to 0.59.

Conclusion

In this study, non-invasive methods, both traditional and ML-based, showed limited correlation to PCWP. This highlights the weak correlation between traditional HF monitoring and haemodynamic parameters, also emphasizing the limitations of single non-invasive measurements. Future research should explore trend analysis and additional features to improve non-invasive haemodynamic monitoring, as there is a clear demand for further advancements in this field.

Effects of transitional care interventions on quality of life in people with lung cancer: A systematic review and meta-analysis

AIM

To identify and appraise the quality of evidence of transitional care interventions on quality of life in lung cancer patients.

BACKGROUND

Quality of life is a strong predictor of survival. The transition from hospital to home is a high-risk period for patients' readmission and death, which seriously affect their quality of life.

DESIGN

Systematic review and meta-analysis.

METHODS

The PubMed, Embase, Cochrane Library, Web of Science and CINAHL databases were searched from inception to 22 October 2022. The primary outcome was quality of life. Statistical analysis was conducted using Review Manager 5.4, results were expressed as standard mean difference (SMD) with a 95% confidence interval (CI). The risk of bias of the included studies was assessed using the Cochrane risk of bias assessment tool. This study was complied with PRISMA guidelines and previously registered in PROSPERO (CRD42023429464).

RESULTS

Fourteen randomized controlled trials were included consisting of a total of 1700 participants, and 12 studies were included in the meta-analysis. It was found that transitional care interventions significantly improved quality of life (SMD = 0.21, 95% CI: 0.02 to 0.40, p = .03) and helped reduce symptoms (SMD = -0.65, 95% CI: -1.13 to -0.18, p = .007) in lung cancer patients, but did not significantly reduce anxiety and depression, and the effect on self-efficacy was unclear.

CONCLUSIONS

This study shows that transitional care interventions can improve quality of life and reduce symptoms in patients, and that primarily educational interventions based on symptom management theory appeared to be more effective. But, there was no statistically significant effect on anxiety and depression.

RELEVANCE TO CLINICAL PRACTICE

This study provides references for the application of transitional care interventions in the field of lung cancer care, and encourages nurses and physicians to apply transitional care plans to facilitate patients' safe transition from hospital to home.

PATIENT OR PUBLIC CONTRIBUTION

No Patient or Public Contribution.

Vulnerability to functional decline is associated with noncardiovascular cause of 90-day readmission in hospitalized patients with heart failure

BACKGROUND

Hospital readmission is common among patients with heart failure. Vulnerability to decline in physical function may increase the risk of noncardiovascular readmission for these patients, but the association between vulnerability and the cause of unplanned readmission is poorly understood, inhibiting the development of effective interventions.

OBJECTIVES

We examined the association of vulnerability with the cause of readmission (cardiovascular vs. noncardiovascular) among hospitalized patients with acute decompensated heart failure.

DESIGNS, SETTINGS, AND PARTICIPANTS

This prospective longitudinal study is part of the Vanderbilt Inpatient Cohort Study.

MAIN OUTCOME AND MEASURES

The primary outcome was the cause of unplanned readmission (cardiovascular vs. noncardiovascular). The primary independent variable was vulnerability, measured using the Vulnerable Elders Survey (VES-13).

RESULTS

Among 804 hospitalized patients with acute decompensated heart failure, 315 (39.2%) experienced an unplanned readmission within 90 days of discharge. In a multinomial logistic model with no readmission as the reference category, higher vulnerability was associated with readmission for noncardiovascular causes (relative risk ratio [RRR] = 1.36, 95% confidence interval [CI]: 1.06-1.75) in the first 90 days after discharge. The VES-13 score was not associated with readmission for cardiovascular causes (RRR = 0.94, 95% CI: 0.75-1.17).

CONCLUSIONS

Vulnerability to functional decline predicted noncardiovascular readmission risk among hospitalized patients with heart failure. The VES-13 is a brief, validated, and freely available tool that should be considered in planning care transitions. Additional work is needed to examine the efficacy of interventions to monitor and mitigate noncardiovascular concerns among vulnerable patients with heart failure being discharged from the hospital.

Unplanned Rehospitalisation due to Medication Harm following an Acute Myocardial Infarction

INTRODUCTION

The contribution of medication harm to rehospitalisation and adverse patient outcomes after an acute myocardial infarction (AMI) needs exploration. Rehospitalisation is costly to both patients and the healthcare facility. Following an AMI, patients are at risk of medication harm as they are often older and have multiple comorbidities and polypharmacy. This study aimed to quantify and evaluate medication harm causing unplanned rehospitalisation after an AMI.

METHODS

This was a retrospective cohort study of patients discharged from a quaternary hospital post-AMI. All rehospitalisations within 18 months were identified using medical record review and coding data. The primary outcome measure was medication harm rehospitalisation. Preventability, causality, and severity assessments of medication harm were conducted.

RESULTS

A total of 1,564 patients experienced an AMI, and 415 (26.5%) were rehospitalised. Eighty-nine patients (5.7% of total population; 6.0% of those discharged) experienced a total of 101 medication harm events. Those with medication harm were older (p = 0.007) and had higher rates of heart failure (p = 0.005), chronic kidney disease (p = 0.046), chronic obstructive pulmonary disease (p = 0.037), and a prior history of ischaemic heart disease (p = 0.005). Gastrointestinal bleeding, acute kidney injury, and hypotension were the most common medication harm events. Forty percent of events were avoidable, and 84% were classed as "serious." Furosemide, antiplatelets, and angiotensin-converting enzyme inhibitors were the most commonly implicated medications. The median time to medication harm rehospitalisation was 79 days (interquartile range: 16-200 days).

CONCLUSION

Medication harm causes unplanned rehospitalisation in 5.7% of all AMI patients (1 in 17 patients; 6.0% of those discharged). The majority of harm was serious and occurred within the first 200 days of discharge. This study highlights that measures to attenuate the risk of medication harm rehospitalisation are essential, including post-discharge medication management.

Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial

OBJECTIVES

We conducted an implementation planning process during the pilot phase of a pragmatic trial, which tests an intervention guided by artificial intelligence (AI) analytics sourced from noninvasive monitoring data in heart failure patients (LINK-HF2).

MATERIALS AND METHODS

A mixed-method analysis was conducted at 2 pilot sites. Interviews were conducted with 12 of 27 enrolled patients and with 13 participating clinicians. iPARIHS constructs were used for interview construction to identify workflow, communication patterns, and clinician's beliefs. Interviews were transcribed and analyzed using inductive coding protocols to identify key themes. Behavioral response data from the AI-generated notifications were collected.

RESULTS

Clinicians responded to notifications within 24 hours in 95% of instances, with 26.7% resulting in clinical action. Four implementation themes emerged: (1) High anticipatory expectations for reliable patient communications, reduced patient burden, and less proactive provider monitoring. (2) The AI notifications required a differential and tailored balance of trust and action advice related to role. (3) Clinic experience with other home-based programs influenced utilization. (4) Responding to notifications involved significant effort, including electronic health record (EHR) review, patient contact, and consultation with other clinicians.

DISCUSSION

Clinician's use of AI data is a function of beliefs regarding the trustworthiness and usefulness of the data, the degree of autonomy in professional roles, and the cognitive effort involved.

CONCLUSION

The implementation planning analysis guided development of strategies that addressed communication technology, patient education, and EHR integration to reduce clinician and patient burden in the subsequent main randomized phase of the trial. Our results provide important insights into the unique implications of implementing AI analytics into clinical workflow.

Pre-emptive treatment of heart failure exacerbations in patients managed with the HeartLogic™ algorithm

AIMS

Heart failure (HF) is a chronic disease affecting 64 million people worldwide and places a severe burden on society because of its mortality, numerous re-hospitalizations and associated costs. HeartLogic™ is an algorithm programmed into implanted devices incorporating several biometric parameters which aims to predict HF episodes. It provides an index which can be monitored remotely, allowing pre-emptive treatment of congestion to prevent acute decompensation. We aim to assess the impact and security of pre-emptive HF management, guided by the HeartLogic™ index.

METHODS AND RESULTS

The HeartLogic™ France Cohort Study is an investigator-initiated, prospective, multi-centre, non-randomized study. Three hundred ten patients with a history of HF (left ventricular ejection fraction ≤40%; or at least one episode of clinical HF with elevated NT-proBNP ≥450 ng/L) and implanted with a cardioverter defibrillator enabling HeartLogic™ index calculation will be included across 10 French centres. The HeartLogic™ index will be monitored remotely for 12 months and in the event of a HeartLogic™ index ≥16, the local investigator will contact the patient for assessment and adjust HF treatment as necessary. The primary endpoint is unscheduled hospitalization for HF. Secondary endpoints are all-cause mortality, cardiovascular death, HF-related death, unscheduled hospitalizations for ventricular or atrial arrhythmia and HeartLogic™ index evolution over time. Blood samples will be collected for biobanking, and quality of life will be assessed. Finally, the safety of a HeartLogic™-triggered strategy for initiating or increasing diuretic therapy will be assessed. A blind and independent committee will adjudicate the events.

CONCLUSIONS

The HeartLogic™ France Cohort Study will provide robust real-world data in a cohort of HF patients managed with the HeartLogic™ algorithm allowing pre-emptive treatment of heart failure exacerbations.

Clinical burden and predictors of non-cardiovascular mortality and morbidity in advanced heart failure

BACKGROUND

The changing demographic of heart failure (HF) increases the exposure to non-cardiovascular (non-CV) events. We investigated the distribution of non-CV mortality/morbidity and the characteristics associated with higher risk of non-CV events in patients with advanced HF.

METHODS

Patients from the HELP-HF registry were stratified according to the number of 2018 HFA-ESC criteria for advanced HF. Endpoints were non-CV mortality and non-CV hospitalization. Competing risk analyses were performed assessing the association between HFA-ESC criteria and study outcomes and the additional predictors of non-CV endpoints.

RESULTS

One thousand one hundred and forty-nine patients were included (median age 77 years-IQR 69-83). At 6, 12, 18 and 22 months, cumulative incidence of CV vs non-CV mortality was 13% vs 5%, 17% vs 8%, 20% vs 12%, 23% vs 12%, and of CV vs non-CV hospitalization was 26% vs 11%, 38% vs 17%, 45% vs 20%, 50% vs 21%. HFA-ESC criteria were associated with increasing adjusted risk of CV death, whereas no association was observed for CV hospitalization, non-CV death and non-CV hospitalization. Predictors of non-CV death were age, chronic obstructive pulmonary disease, dementia, preserved ejection fraction, >1 HF hospitalization and hemoglobin.

CONCLUSIONS

Patients with advanced HF are exposed to high, even though not predominant, burden of non-CV outcomes. HFA-ESC criteria aid to stratify the risk of CV death, but are not associated with lower competing risk of non-CV outcomes. Alternative factors can be useful to define the patients with advanced HF at risk of non-CV events in order to better select patients for treatments specifically reducing CV risk.

Estimated Incidence of Hospitalizations and Deaths Attributable to Respiratory Syncytial Virus Infections Among Adults in Germany Between 2015 and 2019

INTRODUCTION

Respiratory syncytial virus (RSV) burden in adults is underestimated mainly due to unspecific symptoms and limited standard-of-care testing. We estimated the population-based incidence of hospitalization and mortality attributable to RSV among adults with and without risk factors in Germany.

METHODS

Weekly counts of hospitalizations and deaths for respiratory, cardiovascular, and cardiorespiratory diseases were obtained (Statutory Health Insurance database, 2015-2019). A quasi-Poisson regression model was fitted to estimate the number of hospitalizations and deaths attributable to RSV as a function of periodic and aperiodic time trends, and viral activity while allowing for potential overdispersion. Weekly counts of RSV and influenza hospitalizations in children < 2 years and adults ≥ 60 years, respectively, were used as viral activity indicators. Models were stratified by age group and risk status (defined as presence of selected comorbidities).

RESULTS

Population-based RSV-attributable hospitalization incidence rates were high among adults ≥ 60 years: respiratory hospitalizations (236-363 per 100,000 person-years) and cardiorespiratory hospitalizations (584-912 per 100,000 person-years). RSV accounted for 2-3% of all cardiorespiratory hospitalizations in this age group. The increase in cardiorespiratory hospitalization risk associated with underlying risk factors was greater in 18-44 year old persons (five to sixfold higher) than in ≥ 75 year old persons (two to threefold higher).

CONCLUSIONS

This is a first model-based study to comprehensively assess adult RSV burden in Germany. Estimated cardiorespiratory RSV hospitalization rates increased with age and were substantially higher in people with risk factors compared to those without risk factors. Our study indicates that RSV, like other respiratory viruses, contributes to both respiratory and cardiovascular hospitalizations. Effective prevention strategies are needed, especially among older adults ≥ 60 years and among adults with underlying risk factors.

Systematic Review and Critical Appraisal of Prediction Models for Readmission in Coronary Artery Disease Patients: Assessing Current Efficacy and Future Directions

Purpose

Coronary artery disease (CAD) patients frequently face readmissions due to suboptimal disease management. Prediction models are pivotal for detecting early unplanned readmissions. This review offers a unified assessment, aiming to lay the groundwork for enhancing prediction models and informing prevention strategies.

Methods

A search through five databases (PubMed, Web of Science, EBSCOhost, Embase, China National Knowledge Infrastructure) up to September 2023 identified studies on prediction models for coronary artery disease patient readmissions for this review. Two independent reviewers used the CHARMS checklist for data extraction and the PROBAST tool for bias assessment.

Results

From 12,457 records, 15 studies were selected, contributing 30 models targeting various CAD patient groups (AMI, CABG, ACS) from primarily China, the USA, and Canada. Models utilized varied methods such as logistic regression and machine learning, with performance predominantly measured by the c-index. Key predictors included age, gender, and hospital stay duration. Readmission rates in the studies varied from 4.8% to 45.1%. Despite high bias risk across models, several showed notable accuracy and calibration.

Conclusion

The study highlights the need for thorough external validation and the use of the PROBAST tool to reduce bias in models predicting readmission for CAD patients.

National Estimates of Short- and Longer-Term Hospital Readmissions After Major Surgery Among Community-Living Older Adults

Importance

Nationally representative estimates of hospital readmissions within 30 and 180 days after major surgery, including both fee-for-service and Medicare Advantage beneficiaries, are lacking.

Objectives

To provide population-based estimates of hospital readmission within 30 and 180 days after major surgery in community-living older US residents and examine whether these estimates differ according to key demographic, surgical, and geriatric characteristics.

Design, Setting, and Participants

A prospective longitudinal cohort study of National Health and Aging Trends Study data (calendar years 2011-2018), linked to records from the Centers for Medicare & Medicaid Services (CMS). Data analysis was conducted from April to August 2023. Participants included community-living US residents of the contiguous US aged 65 years or older who had at least 1 major surgery from 2011 to 2018. Data analysis was conducted from April 10 to August 28, 2023.

Main Outcomes and Measures

Major operations and hospital readmissions within 30 and 180 days were identified through data linkages with CMS files that included both fee-for-service and Medicare Advantage beneficiaries. Data on frailty and dementia were obtained from the annual National Health and Aging Trends Study assessments.

Results

A total of 1780 major operations (representing 9 556 171 survey-weighted operations nationally) were identified from 1477 community-living participants; mean (SD) age was 79.5 (7.0) years, with 56% being female. The weighted rates of hospital readmission were 11.6% (95% CI, 9.8%-13.6%) for 30 days and 27.6% (95% CI, 24.7%-30.7%) for 180 days. The highest readmission rates within 180 days were observed among participants aged 90 years or older (36.8%; 95% CI, 28.3%-46.3%), those undergoing vascular surgery (45.8%; 95% CI, 37.7%-54.1%), and persons with frailty (36.9%; 95% CI, 30.8%-43.5%) or probable dementia (39.0%; 95% CI, 30.7%-48.1%). In age- and sex-adjusted models with death as a competing risk, the hazard ratios for hospital readmission within 180 days were 2.29 (95% CI, 1.70-3.09) for frailty and 1.58 (95% CI, 1.15-2.18) for probable dementia.

Conclusions and Relevance

In this nationally representative cohort study of community-living older US residents, the likelihood of hospital readmissions within 180 days after major surgery was increased among older persons who were frail or had probable dementia, highlighting the potential value of these geriatric conditions in identifying those at increased risk.

Discharge planning and resource utilization for minimizing readmissions in acute exacerbation of chronic heart failure: Insights from an observational study in a community hospital

This cross-sectional study analyzed discharge disposition in 1,584 readmitted patients aged 65 or older with acute exacerbation of chronic heart failure (AECHF) in a large community hospital from April 2021 to April 2022. The study aimed to explore the relationship between age (65-74, 75-85, and 85 or older) and gender (male, female) with discharge disposition. Results revealed that 55.6 % were discharged for home self-care, 27.3 % with external home health support, and 17.1 % to skilled nursing facilities. Logistic regression showed no significant differences in discharge between age groups. Gender also had no statistically significant effect on discharge disposition. Effective discharge planning emerged as a key factor in reducing readmissions for AECHF. Gender did not significantly impact disposition, suggesting other variables played a more pivotal role. Comprehensive discharge planning and resource allocation, tailored to patient needs, are recommended to enhance patient outcomes and lower AECHF readmission rates.

High incidence of immune-mediated inflammatory diseases in sepsis survivors: A nationwide exposed-nonexposed epidemiological study

OBJECTIVE

Sepsis is characterized by an excessive release of inflammatory cytokines. Cytokine dysregulation is pivotal to the pathophysiology of immune-mediated inflammatory diseases (IMIDs). We aimed to analyze the incidence of IMIDs in patients who survived sepsis.

METHODS

We performed a matched-cohort study using the National Medico-Administrative Hospital database in order to analyze the association between sepsis and incident IMIDs in 2020 in France. Sepsis was defined by the combination of at least one infection diagnosis code and one organ failure code. Patients with a first sepsis diagnosed in 2020 were randomly matched with patients admitted during the same period for acute myocardial infarction (AMI) with an exact matching procedure using age, gender, and comorbidities as matching variables. The main outcome was an IMID diagnosis in a 9-month follow-up period starting the first day of hospitalization for sepsis or AMI.

RESULTS

In France, the incidence rate of IMIDs after a sepsis in 2020-analyzed in 62,257 patients-was of 7956 (95% confidence interval [95% CI] 7392-8520) per 100,000 patient-years. As compared to the AMI population, we observed an increased risk for IMIDs of 2.80 (hazard ratio [HR]; 95% CI [2.22-3.54]) starting from day 16 after admission in the sepsis population. The risk of IMIDs onset in sepsis survivors depended on the type of IMIDs and was higher for immune thrombocytopenia (5.51 [1.97-15.4]), autoimmune hemolytic anemia (HR 4.83 [1.45-16.1]), and antineutrophil cytoplasmic antibody-associated vasculitis (4.66 [2.05-10.6]). Association between sepsis and IMIDs onset appeared well balanced across pathogen categories.

CONCLUSION

Our study shows a high incidence of IMIDs among sepsis survivors.

Heart Failure Readmission in Patients With ST-Segment Elevation Myocardial Infarction and Active Cancer

Background

Although numerous studies have examined readmission with heart failure (HF) after acute myocardial infarction (AMI), limited data are available on HF readmission in cancer patients post-AMI.

Objectives

This study aimed to assess the rates and factors associated with HF readmission in cancer patients presenting with ST-segment elevation myocardial infarction (STEMI).

Methods

A nationally linked cohort of STEMI patients between January 2005 and March 2019 were obtained from the UK Myocardial Infarction National Audit Project registry and the UK national Hospital Episode Statistics Admitted Patient Care registry. Multivariable Fine-Gray competing risk models were used to evaluate HF readmission at 30 days and 1 year.

Results

A total of 326,551 STEMI indexed admissions were included, with 7,090 (2.2%) patients having active cancer. The cancer group was less likely to be admitted under the care of a cardiologist (74.5% vs 81.9%) and had lower rates of invasive coronary angiography (62.2% vs 72.7%; P < 0.001) and percutaneous coronary intervention (58.4% vs. 69.5%). There was a significant prescription gap in the administration of post-AMI medications upon discharge such as an angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (49.5% vs 71.1%) and beta-blockers (58.4% vs 68.0%) in cancer patients. The cancer group had a higher rate of HF readmission at 30 days (3.2% vs 2.3%) and 1 year (9.4% vs 7.3%). However, after adjustment, cancer was not independently associated with HF readmission at 30 days (subdistribution HR: 1.05; 95% CI: 0.86-1.28) or 1 year (subdistribution HR: 1.03; 95% CI: 0.92-1.16). The opportunity-based quality indicator was associated with higher rates of HF readmission independent of cancer diagnosis.

Conclusions

Cancer patients receive care that differs in important ways from patients without cancer. Greater implementation of evidence-based care may reduce HF readmissions, including in cancer patients.

In-Hospital influenza vaccination to prevent cardiorespiratory events in the first 45 days after acute coronary syndrome: A prespecified analysis of the VIP-ACS trial

BACKGROUND

Influenza vaccination prevents major cardiovascular events in individuals presenting a recent acute coronary syndrome (ACS), however the early effect of an in-hospital double-dose vaccination strategy remains uncertain.

METHODS

The VIP-ACS was a randomized, pragmatic, multicenter, open-label trial with a blinded-adjudication endpoint. Patients with ACS ≤ 7 days of hospitalization were randomized to an in-hospital double-dose quadrivalent inactivated influenza vaccine (double-dose) or a standard-dose influenza vaccine at 30 days post-randomization. The primary endpoint was a hierarchical composite of death, myocardial infarction, stroke, hospitalization for unstable angina, hospitalization for heart failure, urgent coronary revascularization, and hospitalization for respiratory infections, analyzed with the win ratio (WR) method in short-term follow-up (45-days after randomization).

RESULTS

The trial enrolled 1,801 patients (≥18 years old). Median participant age was 57 years, 70 % were male. There were no significant differences between groups on the primary hierarchical endpoint: there were 5.7 % wins in the double-dose in-hospital group and 5.5 % wins in the standard-dose delayed vaccination group (WR: 1.03; 95 % CI: 0.70---1.53; P = 0.85). In a sensitivity analysis including COVID-19 infection in the hospitalizations for respiratory infections endpoint, overall results were maintained (WR: 1.03; 95 % CI 0.71---1.51; P = 0.87). Results were consistent for major cardiovascular events only (WR: 0.82; 95 % CI: 0.48---1.39; P = 0.46). No serious adverse events were observed.

CONCLUSION

In patients with recent ACS, in-hospital double-dose influenza vaccination did not significantly reduce cardiorespiratory events at 45 days compared with standard-dose vaccination at 30 days post-randomization.

Structured Telephone Support for Heart Failure Patients: A Literature Review

More than 5 million people in the United States suffer from heart failure. The impact of this chronic disease on costs, morbidity, and mortality is staggering. There is a critical need to improve heart failure management to reduce costs and improve quality of life. One strategy is structured telephone support, which consists of a healthcare provider calling the patient after hospital discharge at scheduled intervals to conduct symptom screening and disease management education. The purpose of this literature review is to analyze the quality and strength of studies that examined the effect of structured telephone support on heart failure outcomes. Eleven articles met the inclusion criteria. Beneficial outcomes were noted in hospital readmission rates, mortality, quality of life, and heart failure symptoms. Given the propensity of structured telephone support to improve quality of life while decreasing readmission and mortality rates, home healthcare agencies should consider implementing this low-cost intervention.

Effectiveness of Transitional Care Program among High-Risk Discharged Patients: A Quasi-Experimental Study on Saving Costs, Post-Discharge Readmissions and Emergency Department Visits

Transitional care programs (TCPs), where hospital care team members repeatedly follow up with discharged patients, aim to reduce post-discharge hospital or emergency department (ED) utilization and healthcare costs. We examined the effectiveness of TCPs at reducing healthcare costs, hospital readmissions, and ED visits. Centers for Medicare and Medicaid Services Bundled Payments for Care Improvement (BPCI) program adjudicated claims files and electronic health records from Greenville Memorial Hospital, Greenville, SC, were accessed. Data on post-discharge 30- and 90-day ED visits and readmissions, total costs, and episodes with costs over BPCI target prices were extracted from November 2017 to July 2020 and compared between the "TCP-Graduates" (N = 85) and "Did Not Graduate" (DNG) (N = 1310) groups. As compared to the DNG group, the TCP-Graduates group had significantly fewer 30-day (7.1% vs. 14.9%, p = 0.046) and 90-day (15.5% vs. 26.3%, p = 0.025) readmissions, episodes with total costs over target prices (25.9% vs. 36.6%, p = 0.031), and lower total cost/episode (USD 22,439 vs. USD 28,633, p = 0.018), but differences in 30-day (9.4% vs. 11.2%, p = 0.607) and 90-day (20.0% vs. 21.9%, p = 0.680) ED visits were not significant. TCP was associated with reduced post-discharge hospital readmissions, total care costs, and episodes exceeding target prices. Further studies with rigorous designs and individual-level data should test these findings.

Readmission following hospital admission for community-acquired pneumonia in England

INTRODUCTION

Readmission rates following hospital admission with community-acquired pneumonia (CAP) have increased in the UK over the past decade. The aim of this work was to describe the cohort of patients with emergency 30-day readmission following hospitalisation for CAP in England and explore the reasons for this.

METHODS

A retrospective analysis of cases from the British Thoracic Society national adult CAP audit admitted to hospitals in England with CAP between 1 December 2018 and 31 January 2019 was performed. Cases were linked with corresponding patient level data from Hospital Episode statistics, providing data on the primary diagnosis treated during readmission and mortality. Analyses were performed describing the cohort of patients readmitted within 30 days, reasons for readmission and comparing those readmitted and primarily treated for pneumonia with other diagnoses.

RESULTS

Of 8136 cases who survived an index admission with CAP, 1304 (15.7%) were readmitted as an emergency within 30 days of discharge. The main problems treated on readmission were pneumonia in 516 (39.6%) patients and other respiratory disorders in 284 (21.8%). Readmission with pneumonia compared with all other diagnoses was associated with significant inpatient mortality (15.9% vs 6.5%; aOR 2.76, 95% CI 1.86 to 4.09, p<0.001). A diagnosis of hospital-acquired infection was more frequent in readmissions treated for pneumonia than other diagnoses (22.1% vs 3.9%, p<0.001).

CONCLUSION

Pneumonia is the most common condition treated on readmission following hospitalisation with CAP and carries a higher mortality than both the index admission or readmission due to other diagnoses. Strategies to reduce readmissions due to pneumonia are required.

Evaluation of a Transitional Care Strategy Implemented in Adults With High-Risk and Multimorbidity in Chile

OBJECTIVES

Fragmentation of continuity of care impacts the health system's efficiency and increases inequity. It severely affects high-risk patients with multimorbidity, requiring coordinated care to avoid preventable complications. The Centro de Innovación en Salud ANCORA UC, together with the Servicio de Salud Metropolitano Sur Oriente, and the National Health Fund, implemented a transitional care strategy for high-risk adults with multimorbidity at 3 hospitals in the southeast of Santiago. The study aimed to evaluate the impact on length of hospital stay, consultations with primary care physicians and contacts after discharge, and also to describe the implementation process of the transition nurse activities.

METHODS

A cohort study was performed between 2017 and 2019, with 137 hospitalizations from exposed patients and 167 hospitalizations from unexposed patients. The results of the study showed a significant decrease in the length of hospital stays and an increase in consultations with physicians.

RESULTS

The results of the implementation process showed that the transition nurse followed-up in a mean of 24 hospitalizations monthly, and 91% of the discharged patients were contacted via the telephone within 7 days. The implementation process showed that the transition nurse's tasks merged with the daily clinical activities in which training on case management, transition care, and continuous support were key aspects of success.

CONCLUSION

We conclude that transitional care intervention has a strong potential in addressing fragmentation of care and is feasible to install and sustain over time in the Chilean context. Finally, this study provides a detailed description of the intervention strategy contributing to its spread and scale-up.

Ten Issues for Updating in Community-Acquired Pneumonia: An Expert Review

Community-acquired pneumonia represents the third-highest cause of mortality in industrialized countries and the first due to infection. Although guidelines for the approach to this infection model are widely implemented in international health schemes, information continually emerges that generates controversy or requires updating its management. This paper reviews the most important issues in the approach to this process, such as an aetiologic update using new molecular platforms or imaging techniques, including the diagnostic stewardship in different clinical settings. It also reviews both the Intensive Care Unit admission criteria and those of clinical stability to discharge. An update in antibiotic, in oxygen, or steroidal therapy is presented. It also analyzes the management out-of-hospital in CAP requiring hospitalization, the main factors for readmission, and an approach to therapeutic failure or rescue. Finally, the main strategies for prevention and vaccination in both immunocompetent and immunocompromised hosts are reviewed.

Predictive Strategies to Reduce the Risk of Rehospitalization with a Focus on Frail Older Adults: A Narrative Review

Frailty is a geriatric syndrome that has physical, cognitive, psychological, social, and environmental components and is characterized by a decrease in physiological reserves. Frailty is associated with several adverse health outcomes such as an increase in rehospitalization rates, falls, delirium, incontinence, dependency on daily living activities, morbidity, and mortality. Older adults may become frailer with each hospitalization; thus, it is beneficial to develop and implement preventive strategies. The present review aims to highlight the epidemiological importance of frailty in rehospitalization and to compile predictive strategies and related interventions to prevent hospitalizations. Firstly, it is important to identify pre-frail and frail older adults using an instrument with high validity and reliability, which can be a practically applicable screening tool. Comprehensive geriatric assessment-based care is an important strategy known to reduce morbidity, mortality, and rehospitalization in older adults and aims to meet the needs of frail patients with a multidisciplinary approach and intervention that includes physiological, psychological, and social domains. Moreover, effective multimorbidity management, physical activity, nutritional support, preventing cognitive frailty, avoiding polypharmacy and anticholinergic drug burden, immunization, social support, and reducing the caregiver burden are other recommended predictive strategies to prevent post-discharge rehospitalization in frail older adults.

Association Between Frailty, 30-day Unplanned Readmission and Mortality After Hospitalization for Heart Failure: Results From the Nationwide Readmissions Database

Objectives: This study examined how frailty in traditional risk-adjusted models could improve the predictability of unplanned 30-day readmission and mortality among heart failure patients. Methods: This study was a retrospective analysis of Nationwide Readmissions Database data collected during the years 2010-2018. All patients ≥65 years who had a principal diagnosis of heart failure were included in the analysis. The Johns Hopkins Adjusted Clinical Groups frailty-defining diagnosis indicator was used to identify frail patients. Results: There was a total of 819,854 patients admitted for heart failure during the study period. Among them, 63,302 (7.7%) were frail. In the regression analysis, the risk of all-cause 30-day readmission (OR, 1.18; 95% CI, 1.14-1.22) and in-hospital mortality (OR, 1.52; 95% CI, 1.40-1.66) were higher in patients with frailty. Discussion: Inclusion of frailty in comorbidity-based risk-prediction models significantly improved the predictability of unplanned 30-day readmission and in-hospital mortality.

A nationwide study of temporal trends of cause-specific hospital readmissions in patients with heart failure

AIMS

The impact of hospital readmissions on the outcomes of heart failure (HF) patients is well known. However, data on temporal trends of cause-specific hospital readmissions in these patients are limited.

METHODS AND RESULTS

From 1987 to 2014, we identified and followed up for 1 year 608 135 patients ≥18 years hospitalized with HF according to the International Classification of Diseases (ICD) 9 and 10 from the National Inpatient Register. Readmissions for cardiovascular (CVD) and non-CVD causes and co-morbidities were defined according to ICD-9 and ICD-10 codes. We analysed trends in the incidence rate of readmissions, the median time to the first rehospitalization, and the time to readmission, stratified by sex, age groups and cause of rehospitalization using linear regression. During our study, 1 year all-cause mortality decreased (β = -4.93, P < 0.0001), but the incidence rate of readmissions per 1000 person-years remained unchanged. The readmission rate for CVD causes decreased; in contrast, the readmission rate increased across all age and sex groups for non-CVD causes. Analysing the patients by study periods (1987-1997, 1998-2007 and 2008-2014), CVD and non-CVD co-morbidities had a statistically significant increasing trend (P < 0.001). The median time in hospital decreased and the median time to the first readmission were almost unchanged.

CONCLUSIONS

Contrary to a declining mortality rate, the incidence rate of readmissions saw no change, possibly because of divergent trends in cause-specific readmissions. An increasing rate of readmissions for non-CVD causes underscores the importance of optimising multimorbidity management to reduce the risk of readmissions in patients with HF.

Driving force of deteriorated cellular environment in heart failure: Metabolic remodeling

Heart Failure (HF) has been one of the leading causes of death worldwide. Though its latent mechanism and therapeutic manipulation are updated and developed ceaselessly, there remain great gaps in the cognition of heart failure. High morbidity and readmission rates among HF patients are waiting to be addressed. Recent studies have found that myocardial energy metabolism was closely related to heart failure, in which substrate utilization, as well as intermediate metabolism disorders, insulin resistance, oxidative stress, and mitochondrial dysfunction, might underlie systolic dysfunction and progression of HF. This article centers on the changes and counteraction of cardiac energy metabolism in the failing heart. Therefore, targeting impaired energy provision is of great potential in the treatment of HF. And shifting the objective from traditional neurohormones to improving the cellular environment is expected to further optimize the management of HF.

Rates and predictors of 30-day hospital readmissions in adults for drug-induced acute pancreatitis: A retrospective study from the United States National Readmission Database

BACKGROUND AND AIM

Drug-induced acute pancreatitis (DIAP) linked to several medications is a diagnosis of exclusion and is associated with significant morbidity and mortality, contributing to the US healthcare cost burden. Existing studies on DIAP focus on the drug classes that can cause acute pancreatitis. Hence, our retrospective study aims to determine the rates and predictors for 30-day readmissions (30-DR) in patients with index hospitalization for DIAP.

METHODS

From the Nationwide Readmissions Database, we followed adults admitted for DIAP who were discharged alive for 30 days. During 30-DR, we evaluated the rates, predictors, and outcomes of DIAP.

RESULTS

Of the 4457 DIAP patients surviving at discharge, 12.5% were readmitted at 30 days. During readmissions, the predictors of 30-DR for DIAP were young age, the Charlson-Deyo Comorbidity Index of 2 and 3, protein-energy malnutrition, and dyslipidemia. During 30-DR, DIAP had a higher mortality rate (2.4% vs. 0.7%; P < 0.020), extended hospital stays (5.6 days vs. 4 days, 0.000), and higher hospital charges ($12 983.6 vs. $8 255.6; P 0.000).

CONCLUSIONS

DIAP has high 30-DR rates and poorer outcomes.

Cardiovascular and renal effects of SGLT2 inhibitor initiation in acute heart failure: a meta-analysis of randomized controlled trials

BACKGROUND

We sought to compare cardiovascular outcomes, renal function, and diuresis in patients receiving standard diuretic therapy for acute heart failure (AHF) with or without the addition of SGLT2i.

METHODS AND RESULTS

Systematic search of three electronic databases identified nine eligible randomized controlled trials involving 2,824 patients. The addition of SGLT2i to conventional therapy for AHF reduced all-cause death (odds ratio [OR] 0.75; 95% CI 0.56-0.99; p = 0.049), readmissions for heart failure (HF) (OR 0.54; 95% CI 0.44-0.66; p < 0.001), and the composite of cardiovascular death and readmissions for HF (hazard ratio 0.71; 95% CI 0.60-0.84; p < 0.001). Furthermore, SGLT2i increased mean daily urinary output in liters (mean difference [MD] 0.45; 95% CI 0.03-0.87; p = 0.035) and decreased mean daily doses of loop diuretics in mg of furosemide equivalent (MD -34.90; 95% CI [- 52.58, - 17.21]; p < 0.001) without increasing the incidence worsening renal function (OR 0.75; 95% CI 0.43-1.29; p = 0.290).

CONCLUSION

SGLT2i addition to conventional diuretic therapy reduced all-cause death, readmissions for HF, and the composite of cardiovascular death or readmissions for HF. Moreover, SGLT2i was associated with a higher volume of diuresis with a lower dose of loop diuretics.

Community Paramedicine Intervention Reduces Hospital Readmission and Emergency Department Utilization for Patients with Cardiopulmonary Conditions

OBJECTIVE

Patients discharged from the hospital with diagnoses of myocardial infarction, congestive heart failure or acute exacerbation of chronic obstructive pulmonary disease (COPD) have high rates of readmission. We sought to quantify the impact of a community paramedicine (CP) intervention on hospital readmission and emergency department (ED) and clinic utilization for patients discharged with these conditions and to calculate the difference in healthcare costs.

METHODS

This was a prospective, observational cohort study with a matched historical control. The groups were matched for qualifying diagnosis, age, gender, and ZIP code. The intervention group received 1-2 home visits per week by a community paramedic for 30 days. We calculated the number of all-cause hospital readmissions and ED and clinic visits, and used descriptive statistics to compare cohorts.

RESULTS

Included in the study were 78 intervention patients and 78 controls. Compared to controls, fewer subjects in the CP cohort had experienced a readmission at 120 days (34.6% vs 64.1%, P < 0.001) and 210 days (43.6% vs 75.6%, P < 0.001) after discharge. At 210 days the CP cohort had 40.9% fewer total hospital admissions, saving 218 bed days and $410,428 in healthcare costs. The CP cohort had 40.7% fewer total ED visits.

CONCLUSION

Patients who received a post-hospital community paramedic intervention had fewer hospital readmissions and ED visits, which resulted in saving 218 bed days and decreasing healthcare costs by $410,428. Incorporation of a home CP intervention of 30 days in this patient population has the potential to benefit payors, hospitals, and patients.

Interventions to improve outcomes in community-acquired pneumonia

INTRODUCTION

Community-acquired pneumonia (CAP) is a common infection associated with high morbimortality and a highly deleterious impact on patients' quality of life and functionality. We comprehensively review the factors related to the host, the causative microorganism, the therapeutic approach and the organization of health systems (e.g. setting for care and systems for allocation) that might have an impact on CAP-associated outcomes. Our main aims are to discuss the most controversial points and to provide some recommendations that may guide further research and the management of patients with CAP, in order to improve their outcomes, beyond mortality.

AREA COVERED

In this review, we aim to provide a critical account of potential measures to improve outcomes of CAP and the supporting evidence from observational studies and clinical trials.

EXPERT OPINION

CAP is associated with high mortality and a highly deleterious impact on patients' quality of life. To improve CAP-associated outcomes, it is important to understand the factors related to the patient, etiology, therapeutics, and the organization of health systems.

Heart Failure Emergency Readmission Prediction Using Stacking Machine Learning Model

Heart failure is a devastating disease that has high mortality rates and a negative impact on quality of life. Heart failure patients often experience emergency readmission after an initial episode, often due to inadequate management. A timely diagnosis and treatment of underlying issues can significantly reduce the risk of emergency readmissions. The purpose of this project was to predict emergency readmissions of discharged heart failure patients using classical machine learning (ML) models based on Electronic Health Record (EHR) data. The dataset used for this study consisted of 166 clinical biomarkers from 2008 patient records. Three feature selection techniques were studied along with 13 classical ML models using five-fold cross-validation. A stacking ML model was trained using the predictions of the three best-performing models for final classification. The stacking ML model provided an accuracy, precision, recall, specificity, F1-score, and area under the curve (AUC) of 89.41%, 90.10%, 89.41%, 87.83%, 89.28%, and 0.881, respectively. This indicates the effectiveness of the proposed model in predicting emergency readmissions. The healthcare providers can intervene pro-actively to reduce emergency hospital readmission risk and improve patient outcomes and decrease healthcare costs using the proposed model.

Why do we evaluate 30-day readmissions in general medicine? A historical perspective and contemporary data

Reducing preventable readmissions is important to help manage current strains on healthcare systems. The metric of 30-day readmissions is commonly cited in discussions regarding this topic. While such thresholds have contemporary funding implications, the rationale for individual cut-off points is partially historical in nature. Through the examination of the basis for the analysis of 30-day readmissions, greater insight into the possible benefits and limitations of such a metric may be obtained.

Recurrent myocardial infarction and emergency department visits: a retrospective study on the Stockholm Area Chest Pain Cohort

BACKGROUND

Patients who experience acute myocardial infarction (AMI) are at risk of recurrent AMI. Contemporary data on recurrent AMI and its association with return emergency department (ED) visits for chest pain are needed.

METHODS

This Swedish retrospective cohort study linked patient-level data from six participating hospitals to four national registers to construct the Stockholm Area Chest Pain Cohort (SACPC). The AMI cohort included SACPC participants visiting the ED for chest pain diagnosed with AMI and discharged alive (first primary diagnosis of AMI during the study period not necessarily the patient's first AMI). The rate and timing of recurrent AMI events, return ED visits for chest pain and all-cause mortality were determined during the year following index AMI discharge.

RESULTS

Among 1 37 706 patients presenting to the ED with chest pain as principal complaint from 2011 to 2016, 5.5% (7579/137 706) were hospitalised with AMI. In total, 98.5% (7467/7579) of patients were discharged alive. In the year following index AMI discharge, 5.8% (432/7467) of AMI patients experienced ≥1 recurrent AMI event. Return ED visits for chest pain occurred in 27.0% (2017/7467) of index AMI survivors. During a return ED visit, recurrent AMI was diagnosed in 13.6% (274/2017) of patients. One-year all-cause mortality was 3.1% in the AMI cohort and 11.6% in the recurrent AMI cohort.

CONCLUSIONS

In this AMI population, 3 in 10 AMI survivors returned to the ED for chest pain in the year following AMI discharge. Furthermore, over 10% of patients with return ED visits were diagnosed with recurrent AMI during that visit. This study confirms the high residual ischaemic risk and associated mortality among AMI survivors.

Suboptimal Cardiology Follow-Up Among Patients With and Without Cancer Hospitalized for Heart Failure

Many patients hospitalized for heart failure (HF) do not receive recommended follow-up cardiology care, and non-White patients are less likely to receive follow-up than White patients. Poor HF management may be particularly problematic in patients with cancer because cardiovascular co-morbidity can delay cancer treatments. Therefore, we sought to describe outpatient cardiology care patterns in patients with cancer hospitalized for HF and to determine if receipt of follow-up varied by race/ethnicity. SEER (Surveillance, Epidemiology, and End Results) data from 2007 to 2013 linked to Medicare claims from 2006 to 2014 were used. We included patients aged 66+ years with breast, prostate, or colorectal cancer, and preexisting HF. Patients with cancer were matched to patients in a noncancer cohort that included individuals with HF and no cancer. The primary outcome was receipt of an outpatient, face-to-face cardiologist visit within 30 days of HF hospitalization. We compared follow-up rates between cancer and noncancer cohorts, and stratified analyses by race/ethnicity. A total of 2,356 patients with cancer and 2,362 patients without cancer were included. Overall, 43% of patients with cancer and 42% of patients without cancer received cardiologist follow-up (p = 0.30). After multivariable adjustment, White patients were 15% more likely to receive cardiology follow-up than Black patients (95% confidence interval [CI] 1.02 to 1.30). Black patients with cancer were 41% (95% CI 1.11 to 1.78) and Asian patients with cancer were 66% (95% CI 1.11 to 2.49) more likely to visit a cardiologist than their noncancer counterparts. In conclusion, less than half of patients with cancer hospitalized for HF received recommended follow-up with a cardiologist, and significant race-related differences in cardiology follow-up exist. Future studies should investigate the reasons for these differences.

Impact of early telemedicine follow-up on 30-Day hospital readmissions

INTRODUCTION

Telemedicine is increasing in popularity but the impact of this shift on patient outcomes has not been well described. Prior data has shown that early post-discharge office visits can reduce readmissions. However, it is unknown if routine use of telemedicine visits for this purpose is similarly beneficial.

MATERIALS AND METHODS

We conducted a retrospective observational study using electronic health records data to assess if the rate of 30-day hospital readmissions differed between modality of visit for primary care or cardiology post-discharge follow-up visits.

RESULTS

Compared to discharges with completed in-person follow-up visits, the adjusted odds of readmission for those with telemedicine follow-up visits was not significantly different (odds ratio [OR] 0.96, 95% confidence interval [CI] 0.61 to 1.51, P = 0.86).

CONCLUSIONS

Our study showed that 30-day readmission rate did not differ significantly according to the modality of visit. These results provide reassurance that telemedicine visits are a safe and viable alternative for primary care or cardiology post-hospitalization follow-up.

Sex Difference in Outcomes of Acute Myocardial Infarction in Young Patients

BACKGROUND

Younger women experience worse health status than men after their index episode of acute myocardial infarction (AMI). However, whether women have a higher risk for cardiovascular and noncardiovascular hospitalizations in the year after discharge is unknown.

OBJECTIVES

The aim of this study was to determine sex differences in causes and timing of 1-year outcomes after AMI in people aged 18 to 55 years.

METHODS

Data from the VIRGO (Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients) study, which enrolled young patients with AMI across 103 U.S. hospitals, were used. Sex differences in all-cause and cause-specific hospitalizations were compared by calculating incidence rates ([IRs] per 1,000 person-years) and IR ratios with 95% CIs. We then performed sequential modeling to evaluate the sex difference by calculating subdistribution HRs (SHRs) accounting for deaths.

RESULTS

Among 2,979 patients, at least 1 hospitalization occurred among 905 patients (30.4%) in the year after discharge. The leading causes of hospitalization were coronary related (IR: 171.8 [95% CI: 153.6-192.2] among women vs 117.8 [95% CI: 97.3-142.6] among men), followed by noncardiac hospitalization (IR: 145.8 [95% CI: 129.2-164.5] among women vs 69.6 [95% CI: 54.5-88.9] among men). Furthermore, a sex difference was present for coronary-related hospitalizations (SHR: 1.33; 95% CI: 1.04-1.70; P = 0.02) and noncardiac hospitalizations (SHR: 1.51; 95% CI: 1.13-2.07; P = 0.01).

CONCLUSIONS

Young women with AMI experience more adverse outcomes than men in the year after discharge. Coronary-related hospitalizations were most common, but noncardiac hospitalizations showed the most significant sex disparity.

Effects of a Multimodal Transitional Care Intervention in Patients at High Risk of Readmission: The TARGET-READ Randomized Clinical Trial

Importance

Hospital readmissions are frequent, costly, and sometimes preventable. Although these issues have been well publicized and incentives to reduce them introduced, the best interventions for reducing readmissions remain unclear.

Objectives

To evaluate the effects of a multimodal transitional care intervention targeting patients at high risk of hospital readmission on the composite outcome of 30-day unplanned readmission or death.

Design, Setting, and Participants

A single-blinded, multicenter randomized clinical trial was conducted from April 2018 to January 2020, with a 30-day follow-up in 4 medium-to-large-sized teaching hospitals in Switzerland. Participants were consecutive patients discharged from general internal medicine wards and at higher risk of unplanned readmission based on their simplified HOSPITAL score (≥4 points). Data were analyzed between April and September 2022.

Interventions

The intervention group underwent systematic medication reconciliation, a 15-minute patient education session with teach-back, a planned first follow-up visit with their primary care physician, and postdischarge follow-up telephone calls from the study team at 3 and 14 days. The control group received usual care from their hospitalist, plus a 1-page standard study information sheet.

Main Outcomes and Measures

Thirty-day postdischarge unplanned readmission or death.

Results

A total of 1386 patients were included with a mean (SD) age of 72 (14) years; 712 (51%) were male. The composite outcome of 30-day unplanned readmission or death was 21% (95% CI, 18% to 24%) in the intervention group and 19% (95% CI, 17% to 22%) in the control group. The intention-to-treat analysis risk difference was 1.7% (95% CI, -2.5% to 5.9%; P = .44). There was no evidence of any intervention effects on time to unplanned readmission or death, postdischarge health care use, patient satisfaction with the quality of their care transition, or readmission costs.

Conclusions and Relevance

In this randomized clinical trial, use of a standardized multimodal care transition intervention targeting higher-risk patients did not significantly decrease the risks of 30-day postdischarge unplanned readmission or death; it demonstrated the difficulties in preventing hospital readmissions, even when multimodal interventions specifically target higher-risk patients.

Trial Registration

ClinicalTrials.gov Identifier: NCT03496896.

Predictors of Thirty-Day Hospital Readmissions in Systemic Lupus Erythematosus in the United States: A Nationwide Study

OBJECTIVE

To evaluate independent risk factors for readmission and to determine the major reasons for readmission in a nationally representative sample of patients with systemic lupus erythematosus (SLE).

METHODS

We used the Nationwide Readmissions Database to identify adults with SLE who were discharged from hospital to home during January-November of 2016 and 2017. Thirty-day all-cause readmissions were identified. A multivariable adjusted survey-specific logistic regression model was used to identify factors associated with readmission.

RESULTS

A total of 132,400 hospitalized adults with SLE were discharged home during the study period; 88.3% were female, with a median age of 51.0 years (interquartile range 38.7-61.9 years). Of these, 18,973 individuals (14.3%) were readmitted within 30 days of discharge from their index hospitalization. In multivariable analyses, the factors associated with the highest odds for readmission were autoimmune hemolytic anemia (odds ratio [OR] 1.86 [95% confidence interval (95% CI) 1.51-2.29]), glomerular disease (OR 1.27 [95% CI 1.19-1.36]), pericarditis (OR 1.35 [95% CI 1.14-1.60]), heart failure (OR 1.34 [95% CI 1.24-1.44]), age 18-30 years (OR 1.28 [95% CI 1.17-1.41] versus age ≥​65 years), and Medicare (OR 1.20 [95% CI 1.13-1.28]) and Medicaid insurance (OR 1.26 [95% CI 1.18-1.34]). Sepsis (7.6%), SLE (7.4%), heart failure (3.5%), and pneumonia (3.2%) were among the most common causes for readmission.

CONCLUSION

In this nationally representative study of SLE readmissions, the strongest risk factors for 30-day readmission were younger age, SLE-related manifestations, and public insurance. These results identify patient groups with SLE that would benefit from postdischarge interventions designed to reduce hospitalizations and improve health outcomes.