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Use of mHealth Devices to Screen for Atrial Fibrillation: Cost-Effectiveness Analysis
BACKGROUND: With an estimated prevalence of around 3% and an about 2.5-fold increased risk of stroke, atrial fibrillation (AF) is a serious threat for patients and a high economic burden for health care systems all over the world. Patients with AF could benefit from screening through mobile health (...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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JMIR Publications
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576464/ https://www.ncbi.nlm.nih.gov/pubmed/33021489 http://dx.doi.org/10.2196/20496 |
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author | Giebel, Godwin D |
author_facet | Giebel, Godwin D |
author_sort | Giebel, Godwin D |
collection | PubMed |
description | BACKGROUND: With an estimated prevalence of around 3% and an about 2.5-fold increased risk of stroke, atrial fibrillation (AF) is a serious threat for patients and a high economic burden for health care systems all over the world. Patients with AF could benefit from screening through mobile health (mHealth) devices. Thus, an early diagnosis is possible with mHealth devices, and the risk for stroke can be markedly reduced by using anticoagulation therapy. OBJECTIVE: The aim of this work was to assess the cost-effectiveness of algorithm-based screening for AF with the aid of photoplethysmography wrist-worn mHealth devices. Even if prevented strokes and prevented deaths from stroke are the most relevant patient outcomes, direct costs were defined as the primary outcome. METHODS: A Monte Carlo simulation was conducted based on a developed state-transition model; 30,000 patients for each CHA(2)DS(2)-VASc (Congestive heart failure, Hypertension, Age≥75 years, Diabetes mellitus, Stroke, Vascular disease, Age 65-74 years, Sex category [female]) score from 1 to 9 were simulated. The first simulation served to estimate the economic burden of AF without the use of mHealth devices. The second simulation served to simulate the economic burden of AF with the use of mHealth devices. Afterwards, the groups were compared in terms of costs, prevented strokes, and deaths from strokes. RESULTS: The CHA(2)DS(2)-VASc score as well as the electrocardiography (ECG) confirmation rate had the biggest impact on costs as well as number of strokes. The higher the risk score, the lower were the costs per prevented stroke. Higher ECG confirmation rates intensified this effect. The effect was not seen in groups with lower risk scores. Over 10 years, the use of mHealth (assuming a 75% ECG confirmation rate) resulted in additional costs (€1=US $1.12) of €441, €567, €536, €520, €606, €625, €623, €692, and €847 per patient for a CHA(2)DS(2)-VASc score of 1 to 9, respectively. The number of prevented strokes tended to be higher in groups with high risk for stroke. Higher ECG confirmation rates led to higher numbers of prevented strokes. The use of mHealth (assuming a 75% ECG confirmation rate) resulted in 25 (7), –68 (–54), 98 (–5), 266 (182), 346 (271), 642 (440), 722 (599), 1111 (815), and 1116 (928) prevented strokes (fatal) for CHA(2)DS(2)-VASc score of 1 to 9, respectively. Higher device accuracy in terms of sensitivity led to even more prevented fatal strokes. CONCLUSIONS: The use of mHealth devices to screen for AF leads to increased costs but also a reduction in the incidence of stroke. In particular, in patients with high CHA(2)DS(2)-VASc scores, the risk for stroke and death from stroke can be markedly reduced. |
format | Online Article Text |
id | pubmed-7576464 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-75764642020-10-27 Use of mHealth Devices to Screen for Atrial Fibrillation: Cost-Effectiveness Analysis Giebel, Godwin D JMIR Mhealth Uhealth Original Paper BACKGROUND: With an estimated prevalence of around 3% and an about 2.5-fold increased risk of stroke, atrial fibrillation (AF) is a serious threat for patients and a high economic burden for health care systems all over the world. Patients with AF could benefit from screening through mobile health (mHealth) devices. Thus, an early diagnosis is possible with mHealth devices, and the risk for stroke can be markedly reduced by using anticoagulation therapy. OBJECTIVE: The aim of this work was to assess the cost-effectiveness of algorithm-based screening for AF with the aid of photoplethysmography wrist-worn mHealth devices. Even if prevented strokes and prevented deaths from stroke are the most relevant patient outcomes, direct costs were defined as the primary outcome. METHODS: A Monte Carlo simulation was conducted based on a developed state-transition model; 30,000 patients for each CHA(2)DS(2)-VASc (Congestive heart failure, Hypertension, Age≥75 years, Diabetes mellitus, Stroke, Vascular disease, Age 65-74 years, Sex category [female]) score from 1 to 9 were simulated. The first simulation served to estimate the economic burden of AF without the use of mHealth devices. The second simulation served to simulate the economic burden of AF with the use of mHealth devices. Afterwards, the groups were compared in terms of costs, prevented strokes, and deaths from strokes. RESULTS: The CHA(2)DS(2)-VASc score as well as the electrocardiography (ECG) confirmation rate had the biggest impact on costs as well as number of strokes. The higher the risk score, the lower were the costs per prevented stroke. Higher ECG confirmation rates intensified this effect. The effect was not seen in groups with lower risk scores. Over 10 years, the use of mHealth (assuming a 75% ECG confirmation rate) resulted in additional costs (€1=US $1.12) of €441, €567, €536, €520, €606, €625, €623, €692, and €847 per patient for a CHA(2)DS(2)-VASc score of 1 to 9, respectively. The number of prevented strokes tended to be higher in groups with high risk for stroke. Higher ECG confirmation rates led to higher numbers of prevented strokes. The use of mHealth (assuming a 75% ECG confirmation rate) resulted in 25 (7), –68 (–54), 98 (–5), 266 (182), 346 (271), 642 (440), 722 (599), 1111 (815), and 1116 (928) prevented strokes (fatal) for CHA(2)DS(2)-VASc score of 1 to 9, respectively. Higher device accuracy in terms of sensitivity led to even more prevented fatal strokes. CONCLUSIONS: The use of mHealth devices to screen for AF leads to increased costs but also a reduction in the incidence of stroke. In particular, in patients with high CHA(2)DS(2)-VASc scores, the risk for stroke and death from stroke can be markedly reduced. JMIR Publications 2020-10-06 /pmc/articles/PMC7576464/ /pubmed/33021489 http://dx.doi.org/10.2196/20496 Text en ©Godwin D Giebel. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 06.10.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Giebel, Godwin D Use of mHealth Devices to Screen for Atrial Fibrillation: Cost-Effectiveness Analysis |
title | Use of mHealth Devices to Screen for Atrial Fibrillation: Cost-Effectiveness Analysis |
title_full | Use of mHealth Devices to Screen for Atrial Fibrillation: Cost-Effectiveness Analysis |
title_fullStr | Use of mHealth Devices to Screen for Atrial Fibrillation: Cost-Effectiveness Analysis |
title_full_unstemmed | Use of mHealth Devices to Screen for Atrial Fibrillation: Cost-Effectiveness Analysis |
title_short | Use of mHealth Devices to Screen for Atrial Fibrillation: Cost-Effectiveness Analysis |
title_sort | use of mhealth devices to screen for atrial fibrillation: cost-effectiveness analysis |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576464/ https://www.ncbi.nlm.nih.gov/pubmed/33021489 http://dx.doi.org/10.2196/20496 |
work_keys_str_mv | AT giebelgodwind useofmhealthdevicestoscreenforatrialfibrillationcosteffectivenessanalysis |