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Related Concept Videos

Heart Failure IV: Classification and Diagnostic Evaluation01:30

Heart Failure IV: Classification and Diagnostic Evaluation

Heart failure can be classified in various ways, with the most common classifications based on physical activity limitations, disease progression, severity, and treatment strategies.The Functional Classification of Heart Failure divides patients into four categories based on physical activity limitation due to symptom burden.Class I: Patients in this class have cardiac disease but no physical activity limitations. Ordinary activities like walking, climbing stairs, or routine tasks do not cause...
Heart Failure V: Medical Management01:30

Heart Failure V: Medical Management

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...
Methods of Documentation VII: EMR01:30

Methods of Documentation VII: EMR

Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare settings,...
Heart Failure VI: Adjunct Therapies01:22

Heart Failure VI: Adjunct Therapies

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.
Heart Failure VII: Nursing Interventions01:30

Heart Failure VII: Nursing Interventions

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,...
Pathophysiology of Heart Failure01:17

Pathophysiology of Heart Failure

Heart failure (HF) is a progressive syndrome involving ventricles that leads to inadequate cardiac output. It can be classified based on location and output or ejection fraction. Ejection fraction (EF) is an essential measurement in the diagnosis and surveillance of HF. Reduced EF corresponds to systolic heart failure (HFrEF). However, HF with preserved ejection fraction (HFpEF) is becoming increasingly prevalent. Also known as diastolic HF, this form of HF is related to aging. The...

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Related Experiment Video

Updated: Jun 17, 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

Comparing methods for identifying patients with heart failure using electronic data sources.

Fadi Alqaisi1, L Keoki Williams, Edward L Peterson

  • 1Henry Ford Heart and Vascular Institute, Henry Ford Hospital, 2799 W, Grand Blvd,, Detroit, MI 48202, USA. falqais1@hfhs.org

BMC Health Services Research
|December 22, 2009
PubMed
Summary
This summary is machine-generated.

Identifying heart failure (HF) patients using administrative claims data can vary significantly. The best performing claims signature combined HF encounters, hospital diagnoses, or B-type Natriuretic Peptide (BNP) levels for accurate patient identification.

Related Experiment Videos

Last Updated: Jun 17, 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

Area of Science:

  • Cardiology
  • Health Informatics
  • Biostatistics

Background:

  • Accurate identification of heart failure (HF) patients from administrative claims data is crucial for research and quality improvement.
  • Limited comparisons exist for various claims data criteria (claims signatures) used to identify HF patients.

Purpose of the Study:

  • To compare the relative accuracy of different claims data signatures for identifying heart failure patients.
  • To determine the most effective claims signature for identifying HF patients in administrative data.

Main Methods:

  • Retrospective study of 4174 patients with HF encounters between 2004-2005.
  • Random sample of 400 patients underwent chart review against Framingham HF criteria.
  • Sensitivity, specificity, and AUC were calculated for various claims signatures, with top performers validated.

Main Results:

  • 65% of sampled patients met Framingham HF criteria; 56% had B-type Natriuretic Peptide (BNP) measurements.
  • Claims signatures showed wide variation in sensitivity (15%-77%) and specificity (69%-100%).
  • The best signature (>=2 HF encounters, HF hospital diagnosis, or BNP >=200 pg/ml) achieved 76% sensitivity, 75% specificity, and 0.754 AUC.

Conclusions:

  • Claims signatures for identifying heart failure patients exhibit significant variability in accuracy.
  • The developed claims signature demonstrates reliable performance for identifying HF patients in administrative data.
  • Findings support improved patient identification for HF research and quality initiatives.