Key result
Screening for atrial fibrillation using mHealth devices increased costs by €441 to €847 per patient over 10 years but reduced the incidence of stroke, particularly in patients with high risk scores.
Why the study?
Atrial fibrillation poses a serious stroke risk and economic burden, prompting the need to assess the cost-effectiveness of algorithm-based screening using wrist-worn mHealth devices.
Does algorithm-based screening for AF with mHealth devices reduce costs and prevent strokes in patients at risk for atrial fibrillation?
Does algorithm-based screening for AF with mHealth devices reduce costs and prevent strokes in patients at risk for atrial fibrillation?
Screening for atrial fibrillation using mHealth devices increases direct costs but substantially reduces the incidence of stroke and stroke-related death, particularly in patients with high CHA2DS2-VASc scores.
May support targeted mHealth AF screening in high-risk patients despite added costs; hypothesis-generating pending prospective validation.
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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Godwin Denk Giebel (2020) studied Atrial fibrillation (n=270,000). mHealth devices to screen for atrial fibrillation vs. No mHealth devices was evaluated on Direct costs. Screening for atrial fibrillation using mHealth devices increased costs by €441 to €847 per patient over 10 years but reduced the incidence of stroke, particularly in patients with high risk scores.
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