Use of mHealth Devices to Screen for Atrial Fibrillation: Cost-Effectiveness Analysis

Abstract

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.

Impact of Mobile Health Devices for the Detection of Atrial Fibrillation: Systematic Review

“…However, the number needed to screen varies between age groups and is found to be lowest, 83, in patients aged older than 65 years, against 926 for ages 60 to 64 years and 1089 for patients aged younger than 60 years, and therefore screening might be most opportune in people aged older than 65 years [ 39 ]. A very recent study using a Monte Carlo simulation to assess the cost-effectiveness of screening for AF with mHealth devices using 30,000 patients per CHA 2 DS 2 -VASc score (1-9) has found this type of screening to cause increased health care costs but a reduction in the incidence of stroke [ 40 ]. Several mHealth studies have used a systematic opportunistic screening approach such as screening for AF with handheld devices in individuals who visit pharmacies or those who visit their general practitioner for a flu vaccination [ 41 - 45 ].…”

Health Economic Research Assessing the Value of Early Detection of Cardiovascular Disease: A Systematic Review

“… Probabilistic analysis performed? Atrial fibrillation Aronsson et al, 2017 [ 40 ] 2016 EUR 3 3 Markov 12 Yes Yes Birkemeyer et al, 2020 [ 21 ] EUR b 3 3 Markov NR Yes Yes Giebel, 2020 [ 41 ] EUR b 3 3 Markov 12 No No Hill et al, 2020 [ 42 ] 2017 GBP 3.5 3.5 DT-Markov NR Yes No Jacobs et al, 2018 [ 22 ] EUR b 4 1.5 DT-Markov 3 Yes Yes Jacobs et al, 2021 [ 43 ] 2018 USD 4 4 DT-Markov 6 Yes Yes McIntyre et al, 2020 [ 44 ] 2014 USD 1.5 1.5 Markov NR …”

Cost-Effectiveness of Atrial Fibrillation Screening Strategies: A Systematic Review

“…Moreover, the highest value of this index is equal to 70864.31 for performing ECG monitoring for more than 60 d for Canadians over 80 yr without AF history referred to outpatient clinics ( 32 ). The measurement of results in a study was expressed with the YLG measure ( 22 ). In a study, the measurement of results was expressed with YLG together with QALY ( 18 ).…”