Literature DB >> 28340009

Designing an optimal screening program for unknown atrial fibrillation: a cost-effectiveness analysis.

Mattias Aronsson1, Emma Svennberg2, Mårten Rosenqvist2, Johan Engdahl2, Faris Al-Khalili2, Leif Friberg2, Viveka Frykman2, Lars-Åke Levin1.   

Abstract

AIMS: The primary objective of this study was to use computer simulations to suggest an optimal age for initiation of screening for unknown atrial fibrillation and to evaluate if repeated screening will add value. METHODS AND
RESULTS: In the absence of relevant clinical studies, this analysis was based on a simulation model. More than two billion different designs of screening programs for unknown atrial fibrillation were simulated and analysed. Data from the published scientific literature and registries were used to construct the model and estimate lifelong effects and costs. Costs and effects generated by 2 147 483 648 different screening designs were calculated and compared. Program designs that implied worse clinical outcome and were less cost-effective compared to other programs were excluded from the analysis. Seven program designs were identified, and considered to be cost effective depending on what the health-care decision makers are ready to pay for gaining a quality-adjusted life-year (QALY). Screening at the age of 75 implied the lowest cost per gained QALY (€4 800/QALY).
CONCLUSION: In conclusion, examining the results of more than two billion simulated screening program designs for unknown atrial fibrillation, seven designs were deemed cost-effective depending on how much we are prepared to pay for gaining QALYs. Our results showed that repeated screening for atrial fibrillation implied additional health benefits to a reasonable cost compared to one-off screening. Published on behalf of the European Society of Cardiology. All rights reserved.
© The Author 2017. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  Atrial fibrillation; Cost-utility analysis; Optimization analysis; Screening

Mesh:

Year:  2017        PMID: 28340009     DOI: 10.1093/europace/eux002

Source DB:  PubMed          Journal:  Europace        ISSN: 1099-5129            Impact factor:   5.214


  4 in total

Review 1.  Computational modeling: What does it tell us about atrial fibrillation therapy?

Authors:  Eleonora Grandi; Dobromir Dobrev; Jordi Heijman
Journal:  Int J Cardiol       Date:  2019-01-25       Impact factor: 4.164

2.  Screening for Atrial Fibrillation: Improving Efficiency of Manual Review of Handheld Electrocardiograms .

Authors:  Madhumitha Pandiaraja; James Brimicombe; Martin Cowie; Andrew Dymond; Hannah Clair Lindén; Gregory Y H Lip; Jonathan Mant; Kate Williams; Peter H Charlton
Journal:  Eng Proc       Date:  2020-11-14

3.  Cost-effectiveness of Screening for Atrial Fibrillation Using Wearable Devices.

Authors:  Wanyi Chen; Shaan Khurshid; Daniel E Singer; Steven J Atlas; Jeffrey M Ashburner; Patrick T Ellinor; David D McManus; Steven A Lubitz; Jagpreet Chhatwal
Journal:  JAMA Health Forum       Date:  2022-08-05

4.  Comparative Clinical Effectiveness of Population-Based Atrial Fibrillation Screening Using Contemporary Modalities: A Decision-Analytic Model.

Authors:  Shaan Khurshid; Wanyi Chen; Daniel E Singer; Steven J Atlas; Jeffrey M Ashburner; Jin G Choi; Chin Hur; Patrick T Ellinor; David D McManus; Jagpreet Chhatwal; Steven A Lubitz
Journal:  J Am Heart Assoc       Date:  2021-09-03       Impact factor: 5.501

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.