ArticleAmerican heart journal2015
Tools for Economic Analysis of Patient Management Interventions in Heart Failure Cost-Effectiveness Model: A Web-based program designed to evaluate the cost-effectiveness of disease management programs in heart failure.
Article in American heart journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 9 citations in OpenAlex.
- Physical rehabilitation for older patients with acute HFpEF (REHAB-HFpEF) trial: Design and rationale.American heart journal · 2026Article
- Strategies for cost-effectiveness analysis of rehabilitation for older patients with acute heart failure.Cost effectiveness and resource allocation : C/E · 2022Article
- Evaluation of a Heart Failure Telemonitoring Program Through a Microsimulation Model: Cost-Utility Analysis.Journal of medical Internet research · 2020Article
- Establishing a pragmatic framework to optimise health outcomes in heart failure and multimorbidity (ARISE-HF): A multidisciplinary position statement.International journal of cardiology · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 7 institutions in 2 countries.
Funding
Abstract
backgroundHeart failure disease management programs can influence medical resource use and quality-adjusted survival. Because projecting long-term costs and survival is challenging, a consistent and valid approach to extrapolating short-term outcomes would be valuable.
methodsWe developed the Tools for Economic Analysis of Patient Management Interventions in Heart Failure Cost-Effectiveness Model, a Web-based simulation tool designed to integrate data on demographic, clinical, and laboratory characteristics; use of evidence-based medications; and costs to generate predicted outcomes. Survival projections are based on a modified Seattle Heart Failure Model. Projections of resource use and quality of life are modeled using relationships with time-varying Seattle Heart Failure Model scores. The model can be used to evaluate parallel-group and single-cohort study designs and hypothetical programs. Simulations consist of 10,000 pairs of virtual cohorts used to generate estimates of resource use, costs, survival, and incremental cost-effectiveness ratios from user inputs.
resultsThe model demonstrated acceptable internal and external validity in replicating resource use, costs, and survival estimates from 3 clinical trials. Simulations to evaluate the cost-effectiveness of heart failure disease management programs across 3 scenarios demonstrate how the model can be used to design a program in which short-term improvements in functioning and use of evidence-based treatments are sufficient to demonstrate good long-term value to the health care system.
conclusionThe Tools for Economic Analysis of Patient Management Interventions in Heart Failure Cost-Effectiveness Model provides researchers and providers with a tool for conducting long-term cost-effectiveness analyses of disease management programs in heart failure.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.