Siyuan Wang BM, Yan Shi MPH, Mengyun Sui PhD, Jing Shen BM, Chen Chen BM, Lin Zhang BM, Xin Zhang MD, Dongsheng Ren MD, Yuheng Wang MPH, Qinping Yang MPH, Junling Gao PhD, Minna Cheng MPH
{"title":"基于人工智能技术的高血压患者电话随访:可靠性研究","authors":"Siyuan Wang BM, Yan Shi MPH, Mengyun Sui PhD, Jing Shen BM, Chen Chen BM, Lin Zhang BM, Xin Zhang MD, Dongsheng Ren MD, Yuheng Wang MPH, Qinping Yang MPH, Junling Gao PhD, Minna Cheng MPH","doi":"10.1111/jch.14823","DOIUrl":null,"url":null,"abstract":"<p>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 <i>t</i>-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, <i>P </i>< .001). The answers related to the symptoms showed moderate to substantial consistency (<i>κ</i>:.465–.624, <i>P </i>< .001), and those related to the complications showed fair consistency (<i>κ</i>:.349, <i>P </i>< .001). In terms of lifestyle, the answer related to smoking showed a very high consistency (<i>κ</i>:.915, <i>P </i>< .001), while those addressing salt consumption, alcohol consumption, and exercise showed moderate to substantial consistency (<i>κ</i>:.402–.645, <i>P </i>< .001). There was moderate consistency in regular usage of medication (<i>κ</i>:.484, <i>P </i>< .001).</p>","PeriodicalId":50237,"journal":{"name":"Journal of Clinical Hypertension","volume":"26 6","pages":"656-664"},"PeriodicalIF":2.7000,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11180679/pdf/","citationCount":"0","resultStr":"{\"title\":\"Telephone follow-up based on artificial intelligence technology among hypertension patients: Reliability study\",\"authors\":\"Siyuan Wang BM, Yan Shi MPH, Mengyun Sui PhD, Jing Shen BM, Chen Chen BM, Lin Zhang BM, Xin Zhang MD, Dongsheng Ren MD, Yuheng Wang MPH, Qinping Yang MPH, Junling Gao PhD, Minna Cheng MPH\",\"doi\":\"10.1111/jch.14823\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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 <i>t</i>-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, <i>P </i>< .001). The answers related to the symptoms showed moderate to substantial consistency (<i>κ</i>:.465–.624, <i>P </i>< .001), and those related to the complications showed fair consistency (<i>κ</i>:.349, <i>P </i>< .001). In terms of lifestyle, the answer related to smoking showed a very high consistency (<i>κ</i>:.915, <i>P </i>< .001), while those addressing salt consumption, alcohol consumption, and exercise showed moderate to substantial consistency (<i>κ</i>:.402–.645, <i>P </i>< .001). 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Telephone follow-up based on artificial intelligence technology among hypertension patients: Reliability study
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).
期刊介绍:
The Journal of Clinical Hypertension is a peer-reviewed, monthly publication that serves internists, cardiologists, nephrologists, endocrinologists, hypertension specialists, primary care practitioners, pharmacists and all professionals interested in hypertension by providing objective, up-to-date information and practical recommendations on the full range of clinical aspects of hypertension. Commentaries and columns by experts in the field provide further insights into our original research articles as well as on major articles published elsewhere. Major guidelines for the management of hypertension are also an important feature of the Journal. Through its partnership with the World Hypertension League, JCH will include a new focus on hypertension and public health, including major policy issues, that features research and reviews related to disease characteristics and management at the population level.