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Related Concept Videos

Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic illness...
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Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Methods Of Healthcare Delivery System01:26

Methods Of Healthcare Delivery System

At the different levels of the healthcare system, we see varying methods of healthcare used. These methods include managed care systems, case management, and primary healthcare.
Managed Care System:
The managed care system is designed to control the cost while maintaining the quality of care. The patient's care from admission to discharge is planned by the primary care provider or the case manager, also known as the gatekeeper. In a managed care system, the number of care providers is limited...
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions01:15

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).
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Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...

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Related Experiment Video

Updated: Jun 16, 2026

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
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Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Published on: August 9, 2024

Estimating clinical and economic impact in case management programs.

Donald Fetterolf1, Albert E Holt, Travis Tucker

  • 1Fetterolf Consulting, McDonald, Pennsylvania, USA. donfetterolf@cs.com <donfetterolf@cs.com>

Population Health Management
|January 28, 2010
PubMed
Summary
This summary is machine-generated.

Case management programs serve patients with complex conditions, often increasing costs. Developing performance guarantees is challenging due to patient variability, necessitating alternative evaluation methods.

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Last Updated: Jun 16, 2026

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
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Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Area of Science:

  • Healthcare Management
  • Health Economics
  • Clinical Operations

Background:

  • Case management programs are widely utilized by various healthcare entities.
  • These programs differ significantly from standard medical or disease management.
  • Patients in case management often have complex conditions, leading to higher costs and utilization patterns.

Purpose of the Study:

  • To outline challenges in analyzing the financial impact of case management.
  • To differentiate case management from other clinical programs in financial impact assessments.
  • To propose a framework for dialogue between case management suppliers and purchasers regarding program value.

Main Methods:

  • Review of existing methodologies for financial impact analysis in clinical programs.
  • Identification of inherent challenges in case management population characteristics.
  • Exploration of alternative statistical approaches for performance evaluation.

Main Results:

  • High variability in clinical and cost data of case management populations complicates ROI guarantees.
  • Standard performance guarantees are difficult to establish due to patient heterogeneity.
  • Alternative statistical methods are available for evaluating program performance.

Conclusions:

  • Financial impact analysis for case management faces unique challenges compared to other clinical programs.
  • A collaborative framework is needed to establish a clear value proposition between service providers and purchasers.
  • Developing effective performance metrics requires acknowledging and addressing population variability.