Evidence map›Paper›PMID 34591888›Full record

ArticlePloS one2021

Gazing through time and beyond the health sector: Insights from a system dynamics model of cardiovascular disease in Australia.

Cindy Q Peng, Kenny D Lawson, Mark Heffernan, Geoff McDonnell, Danny Liew, Sean Lybrand, Sallie-Anne Pearson, Henry Cutler, Leonard Kritharides, Kathy Trieu and 3 more

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

13 authors.

Cindy Q PengDecision Analytics, The SAX Institute, Sydney, Australia.ORCID 0000-0002-6400-2350
Kenny D LawsonAdjunct, Western Sydney University, Sydney, Australia.
Mark HeffernanAdjunct, Western Sydney University, Sydney, Australia.ORCID 0000-0003-3316-7504
Geoff McDonnellAdaptive Care Systems, Sydney, Australia.
Danny LiewSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Sean LybrandAmgen Europe GmbH, Rotkreuz, Switzerland.ORCID 0000-0001-8293-7910
Sallie-Anne PearsonCentre for Big Data Research in Health, University of New South Wales, Sydney, Australia.
Henry CutlerCentre for the Health Economy, Macquarie University, Sydney, Australia.
Leonard KritharidesConcord Repatriation General Hospital, University of Sydney, Sydney, Australia.
Kathy TrieuThe George Institute for Global Health, University of New South Wales, Sydney, Australia.
Quan HuynhBaker Heart and Diabetes Institute, Melbourne, Australia.
Tim UsherwoodThe George Institute for Global Health, University of New South Wales, Sydney, Australia.
Jo-An OcchipintiDecision Analytics, The SAX Institute, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo construct a whole-of-system model to inform strategies that reduce the burden of cardiovascular disease (CVD) in Australia.

methodsA system dynamics model was developed with a multidisciplinary modelling consortium. The model population comprised Australians aged 40 years and over, and the scope encompassed acute and chronic CVD as well as primary and secondary prevention. Health outcomes were CVD-related deaths and hospitalisations, and economic outcomes were the net benefit from both the healthcare system and societal perspectives. The eight strategies broadly included creating social and physical environments supportive of a healthy lifestyle, increasing the use of preventive treatments, and improving systems response to acute CVD events. The effects of strategies were estimated as relative differences to the business-as-usual between 2019-2039. Probabilistic sensitivity analysis produced uncertainty intervals of interquartile ranges (IQR).

findingsThe greatest reduction in CVD-related deaths was seen in strategies that improve systems response to acute CVD events (8.9%, IQR: 7.7-10.2%), yet they resulted in an increase in CVD-related hospitalisations due to future recurrent admissions (1.6%, IQR: 0.1-2.3%). This flow-on effect highlighted the importance of addressing underlying CVD risks. On the other hand, strategies targeting the broad environment that supports a healthy lifestyle were effective in reducing both hospitalisations (7.1%; IQR: 5.0-9.5%) and deaths (8.1% reduction; IQR: 7.1-8.9%). They also produced an economic net benefit of AU$43.3 billion (IQR: 37.7-48.7) using a societal perspective, largely driven by productivity gains. Overall, strategic planning to reduce the burden of CVD should consider the varying effects of strategies over time and beyond the health sector.

Indexed as

AdultAustraliaCardiovascular DiseasesCost of IllnessDelphi TechniqueGlobal Burden of DiseaseHospitalizationHumansMaleMiddle AgedModels, Theoretical

Identifiers

PMID34591888
PMCPMC8483334

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.