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Use of mHealth Devices to Screen for Atrial Fibrillation: Cost-Effectiveness Analysis
1E-Government/E-Health, Department of Business Information Systems, Baden-Wuerttemberg Cooperative State University Mannheim, Mannheim, Germany.
Insights
Screening for atrial fibrillation (AF) using mobile health (mHealth) devices increases costs but significantly reduces stroke risk, especially in high-risk patients. Early AF diagnosis via mHealth enables timely anticoagulation therapy, preventing strokes and improving outcomes.
Area of Science:
- Cardiology
- Health Economics
- Digital Health
Background:
- Atrial fibrillation (AF) affects ~3% of the population, increasing stroke risk 2.5-fold.
- AF poses a significant health threat and economic burden globally.
- Mobile health (mHealth) devices offer potential for early AF diagnosis and stroke prevention through anticoagulation.
Purpose of the Study:
- To evaluate the cost-effectiveness of algorithm-based AF screening using photoplethysmography (PPG) wrist-worn mHealth devices.
- To determine direct costs as the primary outcome, alongside prevented strokes and stroke deaths.
- To assess the economic impact of mHealth-based AF screening compared to standard care.
Main Methods:
- A Monte Carlo simulation using a state-transition model.
- Simulated 30,000 patients for each CHA 2 DS 2 -VASc score (1-9) to compare AF economic burden with and without mHealth.
- Analyzed costs, prevented strokes, and stroke deaths based on CHA 2 DS 2 -VASc scores and electrocardiography (ECG) confirmation rates.
Main Results:
- CHA 2 DS 2 -VASc score and ECG confirmation rate significantly impacted costs and stroke prevention.
- Higher risk scores correlated with lower costs per prevented stroke; higher ECG confirmation rates amplified this effect.
- mHealth screening (75% ECG confirmation) showed increased costs but higher numbers of prevented strokes, particularly in high-risk groups.
Conclusions:
- mHealth screening for AF increases healthcare costs but effectively reduces stroke incidence.
- The risk of stroke and stroke-related mortality can be substantially decreased in patients with high CHA 2 DS 2 -VASc scores.
- Algorithm-based AF screening with mHealth devices is a promising strategy for stroke risk reduction in at-risk populations.
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 CHA2DS2-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 CHA2DS2-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 CHA2DS2-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 CHA2DS2-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 CHA2DS2-VASc scores, the risk for stroke and death from stroke can be markedly reduced.
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