Chi Zhang1,2,3, Mang-Mang Pan1, Na Wang4, Wei-Wei Wang5, Zheng Li6, Zhi-Chun Gu7,8, Hou-Wen Lin1,2,3. 1. Department of Pharmacy, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China. 2. School of Medicine, Tongji University, Shanghai, 200092, China. 3. Shanghai Pharmaceutical Association, Shanghai Anticoagulation Pharmacist Alliance, Shanghai, 200040, China. 4. Department of Pharmacy, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China. 5. Department of S/4HANA Research & Development, SAP (China) Co., Ltd, Shanghai, 201203, China. 6. Department of Cardiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China. 7. Department of Pharmacy, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China. guzhichun213@163.com. 8. Shanghai Pharmaceutical Association, Shanghai Anticoagulation Pharmacist Alliance, Shanghai, 200040, China. guzhichun213@163.com.
Abstract
PURPOSE: Appropriate prescription of oral anticoagulants (OACs) and good patient adherence are essential to ensure optimal anticoagulation in patients with atrial fibrillation (AF). The aim of this study is to develop a mobile health tool to aid both clinicians and patients with AF in anticoagulation therapy. METHODS: In this study, a novel anticoagulation management model integrating decision support and patient follow-up, the I-Anticoagulation, was developed based on a WeChat Mini Program. With this tool, the risks of stroke and bleeding in AF patients can automatically be calculated according to their characteristics. Anticoagulation regimens were recommended based on a trade-off analysis that balances stroke and bleeding risks according to recent clinical guidelines. A shared decision can be made with full communication between medical professionals and patients. Moreover, follow-up was also conducted using I-Anticoagulation. RESULTS: A total of 120 AF patients receiving anticoagulants (40 received warfarin and 80 received non-vitamin K antagonist oral anticoagulants [NOACs]) were included in the pilot study. The incidence of thromboembolic events was 2.5% and 1.3%, and the rates of bleeding events were 22.5% and 13.8% in the warfarin and NOAC groups, respectively. Generally, self-reported adherence was high, and the satisfaction with anticoagulation was good in all patients with AF. CONCLUSION: Overall, the anticoagulation management model developed in this study could be involved in the full process of anticoagulation therapy in AF patients to improve rationality, adherence, and satisfaction in both medical professionals and patients. However, the usability, feasibility, and acceptability of the I-Anticoagulant-based anticoagulation management model need to be further assessed through well-designed random clinical trials.
PURPOSE: Appropriate prescription of oral anticoagulants (OACs) and good patient adherence are essential to ensure optimal anticoagulation in patients with atrial fibrillation (AF). The aim of this study is to develop a mobile health tool to aid both clinicians and patients with AF in anticoagulation therapy. METHODS: In this study, a novel anticoagulation management model integrating decision support and patient follow-up, the I-Anticoagulation, was developed based on a WeChat Mini Program. With this tool, the risks of stroke and bleeding in AF patients can automatically be calculated according to their characteristics. Anticoagulation regimens were recommended based on a trade-off analysis that balances stroke and bleeding risks according to recent clinical guidelines. A shared decision can be made with full communication between medical professionals and patients. Moreover, follow-up was also conducted using I-Anticoagulation. RESULTS: A total of 120 AF patients receiving anticoagulants (40 received warfarin and 80 received non-vitamin K antagonist oral anticoagulants [NOACs]) were included in the pilot study. The incidence of thromboembolic events was 2.5% and 1.3%, and the rates of bleeding events were 22.5% and 13.8% in the warfarin and NOAC groups, respectively. Generally, self-reported adherence was high, and the satisfaction with anticoagulation was good in all patients with AF. CONCLUSION: Overall, the anticoagulation management model developed in this study could be involved in the full process of anticoagulation therapy in AF patients to improve rationality, adherence, and satisfaction in both medical professionals and patients. However, the usability, feasibility, and acceptability of the I-Anticoagulant-based anticoagulation management model need to be further assessed through well-designed random clinical trials.
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