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基于人工智能技术的高血压患者电话随访:可靠性研究。

Telephone follow-up based on artificial intelligence technology among hypertension patients: Reliability study.

机构信息

Division of Chronic Non-communicable Disease and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.

Product Department, Yicheng Information Technology Limited Corporation, Shanghai, China.

出版信息

J Clin Hypertens (Greenwich). 2024 Jun;26(6):656-664. doi: 10.1111/jch.14823. Epub 2024 May 22.

DOI:10.1111/jch.14823
PMID:38778548
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11180679/
Abstract

Artificial intelligence (AI) telephone is reliable for the follow-up and management of hypertensives. It takes less time and is equivalent to manual follow-up to a high degree. We conducted a reliability study to evaluate the efficiency of AI telephone follow-up in the management of hypertension. During May 18 and June 30, 2020, 350 hypertensives managed by the Pengpu Community Health Service Center in Shanghai were recruited for follow-up, once by AI and once by a human. The second follow-up was conducted within 3-7 days (mean 5.5 days). The mean length time of two calls were compared by paired t-test, and Cohen's Kappa coefficient was used to evaluate the reliability of the results between the two follow-up visits. The mean length time of AI calls was shorter (4.15 min) than that of manual calls (5.24 min, P < .001). The answers related to the symptoms showed moderate to substantial consistency (κ:.465-.624, P < .001), and those related to the complications showed fair consistency (κ:.349, P < .001). In terms of lifestyle, the answer related to smoking showed a very high consistency (κ:.915, P < .001), while those addressing salt consumption, alcohol consumption, and exercise showed moderate to substantial consistency (κ:.402-.645, P < .001). There was moderate consistency in regular usage of medication (κ:.484, P < .001).

摘要

人工智能(AI)电话在高血压患者的随访和管理中是可靠的。它需要的时间更少,并且在很大程度上等同于手动随访。我们进行了一项可靠性研究,以评估 AI 电话随访在高血压管理中的效率。2020 年 5 月 18 日至 6 月 30 日,上海彭浦社区卫生服务中心共招募了 350 名高血压患者进行随访,一次通过 AI,一次通过人工。第二次随访在 3-7 天内进行(平均 5.5 天)。通过配对 t 检验比较两次电话随访的平均时间长度,并使用 Cohen's Kappa 系数评估两次随访结果的可靠性。AI 电话的平均时间长度(4.15 分钟)短于人工电话(5.24 分钟,P<.001)。与症状相关的答案显示出中等至较大的一致性(κ:.465-.624,P<.001),与并发症相关的答案显示出适度一致性(κ:.349,P<.001)。在生活方式方面,与吸烟有关的答案显示出非常高的一致性(κ:.915,P<.001),而与盐摄入量、饮酒量和运动有关的答案则显示出中等至较大的一致性(κ:.402-.645,P<.001)。规律用药的一致性也适中(κ:.484,P<.001)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8018/11180679/61f4d05b9394/JCH-26-656-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8018/11180679/7e54e884b530/JCH-26-656-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8018/11180679/61f4d05b9394/JCH-26-656-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8018/11180679/7e54e884b530/JCH-26-656-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8018/11180679/61f4d05b9394/JCH-26-656-g002.jpg

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[Study on community health management and control of hypertension in patients aged 35 years and above in China, 2015].
[2015年中国35岁及以上人群高血压社区健康管理与控制研究]
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6
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