Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Heart Failure V: Medical Management01:30

Heart Failure V: Medical Management

606
Medical Management of Acute Decompensated Heart Failure (ADHF)The primary goals of therapy for patients hospitalized with acute decompensated heart failure (ADHF) include:Relieving symptomsOptimizing volume statusSupporting oxygenation and ventilationMaintaining cardiac output (CO) and end-organ perfusionIdentifying and addressing the cause of ADHFPreventing complicationsProviding patient education on factors precipitating HF exacerbationPlanning for dischargeOngoing monitoring and assessment...
606
Heart Failure VI: Adjunct Therapies01:22

Heart Failure VI: Adjunct Therapies

624
Additional therapies for treating patients with heart failure (HF) may include procedural interventions, supplemental oxygen, the management of sleep disorders, and nutritional therapy.Procedural InterventionsImplantable Cardioverter-Defibrillator: For patients at risk of life-threatening arrhythmias due to severe left ventricular dysfunction, an Implantable Cardioverter-Defibrillator (ICD) can detect and terminate these arrhythmias, preventing sudden cardiac death and improving survival rates.
624
Heart Failure VII: Nursing Interventions01:30

Heart Failure VII: Nursing Interventions

773
The first step in nursing management of a patient with heart failure involves thoroughly assessing the patient's medical history.Subjective Data: Obtain the patient's medical history of coronary artery disease, hypertension, myocardial infarction, and symptoms like dyspnea, orthopnea, and paroxysmal nocturnal dyspnea.Objective Data: Conduct a physical examination to identify findings such as jugular vein distention, pulmonary crackles, tachycardia, murmurs, peripheral edema, and vital signs,...
773
Heart Failure Drugs: Inhibitors of Renin-Angiotensin System01:26

Heart Failure Drugs: Inhibitors of Renin-Angiotensin System

1.5K
The activation of the sympathetic nervous system and the renin-angiotensin-aldosterone system (RAAS) contributes to cardiac remodeling, and inhibiting the RAAS is a pharmacological target in heart failure management. As a result, neurohumoral modulation is a crucial treatment principle for managing heart failure. This approach involves using medications like ACE inhibitors (ACEIs), angiotensin receptor blockers (ARBs), β-blockers, mineralocorticoid receptor antagonists (MRAs), and neutral...
1.5K
Heart Failure Drugs: Diuretics01:22

Heart Failure Drugs: Diuretics

1.3K
Heart failure and kidney perfusion are interconnected in a complex way. Reduced renal perfusion and venous congestion are two significant factors that contribute to renal dysfunction in heart failure. The kidneys, primarily responsible for fluid balance in the body, are adversely affected due to compromised cardiac output and increased venous pressure. In response to reduced renal perfusion, the kidneys activate neurohumoral mechanisms to restore balance. However, these mechanisms can be...
1.3K
Mitral Regurgitation IV: Nursing Management01:28

Mitral Regurgitation IV: Nursing Management

591
Mitral regurgitation (MR) is a condition where the mitral valve does not close properly, leading to the backward flow of blood from the left ventricle into the left atrium during systole. This condition can arise from various causes, including rheumatic fever, infective endocarditis, or degenerative valve disease. Effective nursing management is crucial to optimizing patient outcomes and involves comprehensive assessment and targeted interventions.Comprehensive Patient AssessmentA detailed...
591

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Evaluating the robustness and readiness of large frontier models in health AI applications.

Nature medicine·2026
Same author

AI, humanity, and the open world of health care: enduring imperatives for the next century.

Journal of the American Medical Informatics Association : JAMIA·2026
Same author

Blood pressure screening event at hispanic community organization yields positive screenings and links to primary care.

BMC public health·2026
Same author

Beyond the price tag: a scoping review of the determinants of informal payments in health systems and strategies for curbing them.

BMC health services research·2026
Same author

A narrowing window to understand AI.

Science (New York, N.Y.)·2026
Same author

Beyond sequence similarity: toward function-based screening of nucleic acid synthesis.

Frontiers in bioengineering and biotechnology·2026

Related Experiment Video

Updated: Apr 22, 2026

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
05:16

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure

Published on: June 10, 2025

777

Data-driven decisions for reducing readmissions for heart failure: general methodology and case study.

Mohsen Bayati1, Mark Braverman2, Michael Gillam3

  • 1Stanford University, Stanford, California, United States of America.

Plos One
|October 9, 2014
PubMed
Summary
This summary is machine-generated.

Predictive models can identify congestive heart failure patients at high risk for readmission. Combining these predictions with decision analysis optimizes post-discharge interventions, reducing hospital readmissions and healthcare costs.

More Related Videos

Author Spotlight: Workflow for Integrating POCUS Data into EHR for Managing Heart Failure Patients
03:47

Author Spotlight: Workflow for Integrating POCUS Data into EHR for Managing Heart Failure Patients

Published on: July 12, 2024

1.3K
A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
04:24

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

Published on: April 19, 2019

14.2K

Related Experiment Videos

Last Updated: Apr 22, 2026

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
05:16

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure

Published on: June 10, 2025

777
Author Spotlight: Workflow for Integrating POCUS Data into EHR for Managing Heart Failure Patients
03:47

Author Spotlight: Workflow for Integrating POCUS Data into EHR for Managing Heart Failure Patients

Published on: July 12, 2024

1.3K
A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
04:24

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

Published on: April 19, 2019

14.2K

Area of Science:

  • Healthcare Analytics
  • Clinical Decision Support

Background:

  • Patient readmission risk stratification is crucial for healthcare economics.
  • Existing predictive models for readmission have limitations in accuracy and clinical utility.
  • Congestive heart failure (CHF) readmissions incur significant costs and are a focus for intervention.

Purpose of the Study:

  • To develop a predictive model for 30-day readmissions in congestive heart failure (CHF) patients.
  • To integrate predictive modeling with decision analysis for patient-specific post-discharge interventions.
  • To assess the cost-effectiveness of this combined approach for resource allocation.

Main Methods:

  • A statistical classifier was built using a retrospective database of 793 CHF hospital visits.
  • Decision analysis guided post-discharge intervention decisions based on predicted readmission risk.
  • A cost-effectiveness analysis was conducted on 379 additional hospital visits.

Main Results:

  • The proposed methodology demonstrated an 18.2% reduction in 30-day rehospitalizations.
  • Implementing the post-discharge plan, costing $1,300, reduced readmissions by 35%.
  • This approach resulted in a 3.8% overall cost saving.

Conclusions:

  • Automated patient data classifiers integrated with decision analysis effectively guide post-discharge support for CHF patients.
  • This methodology is particularly valuable for optimizing interventions when universal program provision is not economically feasible.
  • Combining prediction with decision analysis is key to improving patient outcomes and managing healthcare expenditures.