基于网络的心血管疾病患者风险分层和优化应用:初步研究

Q2 Medicine JMIR Cardio Pub Date : 2023-08-03 DOI:10.2196/46533
Avinash Pandey, Marie Michelle D'Souza, Amritanshu Shekhar Pandey, Hassan Mir
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引用次数: 0

摘要

背景:除了阿司匹林、血管紧张素转换酶抑制剂、他汀类药物和生活方式改变干预外,新型药物已被证明可以降低动脉粥样硬化性心血管疾病患者的发病率和死亡率,包括新的抗血栓药、抗高血糖药和脂质调节疗法。尽管有这些益处,但采用这些指南导向的疗法仍然是一个挑战。有必要制定战略,以支持知识转化,以吸收二级预防疗法。目的:本研究的目的是测试心血管疾病患者分层和优化(STOP-CVD)的可行性和可用性,这是一个旨在通过提供个性化风险分层和优化指导来促进知识转化的护理点应用程序。方法:使用REACH(减少动脉粥样硬化血栓形成持续健康)注册试验和预测建模(包括67,888例患者),我们设计了一个免费的基于网络的二次风险计算器。基于人口统计学和共病概况,该应用程序用于预测个体20个月的心血管事件风险和心血管死亡率,并提供与年龄匹配的对照比较,优化心血管风险概况,以说明可修改的剩余风险。此外,该应用程序利用患者的风险概况,根据一种新的算法为可能的治疗干预提供具体指导。在最初3个月的采用阶段,通过电子邮件和电话向240名转介到地区心血管诊所的医生发送了一次邀请。3个月后,我们向所有用户发送了一份用户体验调查。在此之后,没有对应用程序进行进一步的营销。谷歌分析是在2021年1月至2021年12月实施后收集的。这些数据用于将不同用户的总数和应用程序每月使用的总数制成表格。结果:在为期1年的试验中,240名受邀临床医生中有47名使用了该应用程序1573次,平均每月131次,并随时间持续使用。所有24个实施后调查的应答者都确认应用程序是功能性的、易于使用的和有用的。结论:本试验提示STOP-CVD应用是可行和可用的,临床医生满意度高。该工具可以很容易地扩展,以支持指南导向的医学治疗,这可以改善临床结果。未来的研究将集中于评估该工具对临床医生管理和患者预后的影响。
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A Web-Based Application for Risk Stratification and Optimization in Patients With Cardiovascular Disease: Pilot Study.

Background: In addition to aspirin, angiotensin-converting enzyme inhibitors, statins, and lifestyle modification interventions, novel pharmacological agents have been shown to reduce morbidity and mortality in atherosclerotic cardiovascular disease patients, including new antithrombotics, antihyperglycemics, and lipid-modulating therapies. Despite their benefits, the uptake of these guideline-directed therapies remains a challenge. There is a need to develop strategies to support knowledge translation for the uptake of secondary prevention therapies.

Objective: The goal of this study was to test the feasibility and usability of Stratification and Optimization in Patients With Cardiovascular Disease (STOP-CVD), a point-of-care application that was designed to facilitate knowledge translation by providing individualized risk stratification and optimization guidance.

Methods: Using the REACH (Reduction of Atherothrombosis for Continued Health) Registry trial and predictive modeling (which included 67,888 patients), we designed a free web-based secondary risk calculator. Based on demographic and comorbidity profiles, the application was used to predict an individual's 20-month risk of cardiovascular events and cardiovascular mortality and provides a comparison to an age-matched control with an optimized cardiovascular risk profile to illustrate the modifiable residual risk. Additionally, the application used the patient's risk profile to provide specific guidance for possible therapeutic interventions based on a novel algorithm. During an initial 3-month adoption phase, 1-time invitations were sent through email and telephone to 240 physicians that refer to a regional cardiovascular clinic. After 3 months, a survey of user experience was sent to all users. Following this, no further marketing of the application was performed. Google Analytics was collected postimplementation from January 2021 to December 2021. These were used to tabulate the total number of distinct users and the total number of monthly uses of the application.

Results: During the 1-year pilot, 47 of the 240 invited clinicians used the application 1573 times, an average of 131 times per month, with sustained usage over time. All 24 postimplementation survey respondents confirmed that the application was functional, easy to use, and useful.

Conclusions: This pilot suggests that the STOP-CVD application is feasible and usable, with high clinician satisfaction. This tool can be easily scaled to support the uptake of guideline-directed medical therapy, which could improve clinical outcomes. Future research will be focused on evaluating the impact of this tool on clinician management and patient outcomes.

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来源期刊
JMIR Cardio
JMIR Cardio Computer Science-Computer Science Applications
CiteScore
3.50
自引率
0.00%
发文量
25
审稿时长
12 weeks
期刊最新文献
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