Evidence map›Paper›PMID 39469059›Full record

ArticleAmerican journal of medicine open2024

Coaching People with Cardiovascular Disease to Close Their "Treatment Gaps" Reduces Hospital Utilization, Saves Lives, and Delivers Net Cost Savings Over 10 Years.

Joshua Byrnes, Margarite J Vale, Clifford Afoakwah, Pippa Grant, Sharmani Barnard

Abstract read
In one paragraph

Article in American journal of medicine open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Joshua ByrnesCentre for Applied Health Economics, School of Medicine and Dentistry, Griffith University, Nathan, Australia.
Margarite J ValeDepartment of Medicine, The University of Melbourne, Melbourne, Australia.
Clifford AfoakwahCentre for Applied Health Economics, School of Medicine and Dentistry, Griffith University, Nathan, Australia.
Pippa GrantHBF Health Fund, Perth, Western Australia, Australia.
Sharmani BarnardSchool of Population Health, Curtin University, Perth, Western Australia, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Disease management programs are an essential tool in the fight against rising prevalence and costs associated with cardiovascular disease (CVD). However, there is a lack of evidence on the long-term impact of these programs on clinical outcomes, healthcare utilization, and cost. This study presents a long-term follow up of clinical, healthcare utilization and cost, and mortality consequences of The COACH Program, a 6-month telephone delivered CVD prevention program. Methods: We conducted 10-year retrospective propensity score matched cohort study of potentially eligible participants comparing individuals that participated to those that did not receive the Program. Primary outcomes of interest were differences in mortality, private healthcare utilization and cost of private healthcare utilization sourced from private health insurance claims data. Results: Of the 24,932 potentially eligible participants, 11,988 were invited to participate in The COACH Program between July 1, 2010, and December 31, 2020. The COACH Program participants ( Conclusions: A structured 6-month telephone delivered coaching program focused on closing "treatment gaps" in people with a history of CVD saves lives and reduces hospital utilization, health care costs over 10-years follow-up.

Indexed as

Cardiovascular diseaseDisease managementEvidence-practice gapsHealth coachingTreatment gaps

Identifiers

PMID39469059
PMCPMC11513497

What OpenQuestion holds

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Registered trials

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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.