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Healthcare Cost Savings Estimator Tool for Chronic Disease Self-Management Program: A New Tool for Program Administrators and Decision Makers

Overview of attention for article published in Frontiers in Public Health, April 2015
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Title
Healthcare Cost Savings Estimator Tool for Chronic Disease Self-Management Program: A New Tool for Program Administrators and Decision Makers
Published in
Frontiers in Public Health, April 2015
DOI 10.3389/fpubh.2015.00042
Pubmed ID
Authors

SangNam Ahn, Matthew Lee Smith, Mary Altpeter, Lindsey Post, Marcia G. Ory

Abstract

Chronic disease self-management education (CDSME) programs have been delivered to more than 100,000 older Americans with chronic conditions. As one of the Stanford suite of evidence-based CDSME programs, the chronic disease self-management program (CDSMP) has been disseminated in diverse populations and settings. The objective of this paper is to introduce a practical, universally applicable tool to assist program administrators and decision makers plan implementation efforts and make the case for continued program delivery. This tool was developed utilizing data from a recent National Study of CDSMP to estimate national savings associated with program participation. Potential annual healthcare savings per CDSMP participant were calculated based on averted emergency room visits and hospitalizations. While national data can be utilized to estimate cost savings, the tool has built-in features allowing users to tailor calculations based on their site-specific data. Building upon the National Study of CDSMP's documented potential savings of $3.3 billion in healthcare costs by reaching 5% of adults with one or more chronic conditions, two heuristic case examples were also explored based on different population projections. The case examples show how a small county and large metropolitan city were not only able to estimate healthcare savings ($38,803 for the small county; $732,290 for the large metropolitan city) for their existing participant populations but also to project significant healthcare savings if they plan to reach higher proportions of middle-aged and older adults. Having a tool to demonstrate the monetary value of CDSMP can contribute to the ongoing dissemination and sustainability of such community-based interventions. Next steps will be creating a user-friendly, internet-based version of Healthcare Cost Savings Estimator Tool: CDSMP, followed by broadening the tool to consider cost savings for other evidence-based programs.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 23%
Student > Doctoral Student 4 13%
Other 4 13%
Student > Postgraduate 4 13%
Researcher 2 6%
Other 3 10%
Unknown 7 23%
Readers by discipline Count As %
Medicine and Dentistry 7 23%
Social Sciences 6 19%
Agricultural and Biological Sciences 3 10%
Nursing and Health Professions 2 6%
Environmental Science 2 6%
Other 4 13%
Unknown 7 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 October 2019.
All research outputs
#15,480,316
of 23,003,906 outputs
Outputs from Frontiers in Public Health
#4,644
of 10,231 outputs
Outputs of similar age
#158,250
of 265,638 outputs
Outputs of similar age from Frontiers in Public Health
#40
of 74 outputs
Altmetric has tracked 23,003,906 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,231 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 10.0. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 265,638 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.