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Patients’ Utilization and Perception of an Artificial Intelligence–Based Symptom Assessment and Advice Technology in a British Primary Care Waiting Room: Exploratory Pilot Study

机译:患者利用与对英国初级保健候诊室中的人工智能症状评估和咨询技术的利用和认识性:探索性试验研究

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摘要

BackgroundWhen someone needs to know whether and when to seek medical attention, there are a range of options to consider. Each will have consequences for the individual (primarily considering trust, convenience, usefulness, and opportunity costs) and for the wider health system (affecting clinical throughput, cost, and system efficiency). Digital symptom assessment technologies that leverage artificial intelligence may help patients navigate to the right type of care with the correct degree of urgency. However, a recent review highlighted a gap in the literature on the real-world usability of these technologies. ObjectiveWe sought to explore the usability, acceptability, and utility of one such symptom assessment technology, Ada, in a primary care setting. MethodsPatients with a new complaint attending a primary care clinic in South London were invited to use a custom version of the Ada symptom assessment mobile app. This exploratory pilot study was conducted between November 2017 and January 2018 in a practice with 20,000 registered patients. Participants were asked to complete an Ada self-assessment about their presenting complaint on a study smartphone, with assistance provided if required. Perceptions on the app and its utility were collected through a self-completed study questionnaire following completion of the Ada self-assessment. ResultsOver a 3-month period, 523 patients participated. Most were female (n=325, 62.1%), mean age 39.79 years (SD 17.7 years), with a larger proportion (413/506, 81.6%) of working-age individuals (aged 15-64) than the general population (66.0%). Participants rated Ada’s ease of use highly, with most (511/522, 97.8%) reporting it was very or quite easy. Most would use Ada again (443/503, 88.1%) and agreed they would recommend it to a friend or relative (444/520, 85.3%). We identified a number of age-related trends among respondents, with a directional trend for more young respondents to report Ada had provided helpful advice (50/54, 93%, 18-24-year olds reported helpful) than older respondents (19/32, 59%, adults aged 70+ reported helpful). We found no sex differences on any of the usability questions fielded. While most respondents reported that using the symptom checker would not have made a difference in their care-seeking behavior (425/494, 86.0%), a sizable minority (63/494, 12.8%) reported they would have used lower-intensity care such as self-care, pharmacy, or delaying their appointment. The proportion was higher for patients aged 18-24 (11/50, 22%) than aged 70+ (0/28, 0%). ConclusionsIn this exploratory pilot study, the digital symptom checker was rated as highly usable and acceptable by patients in a primary care setting. Further research is needed to confirm whether the app might appropriately direct patients to timely care, and understand how this might save resources for the health system. More work is also needed to ensure the benefits accrue equally to older age groups.
机译:背景,有人需要知道是否以及何时寻求医疗注意,有一系列选项需要考虑。每个人都会对个人(主要考虑信任,便利,有用和机会成本)和更广泛的健康系统(影响临床吞吐量,成本和系统效率)。利用人工智能的数字症状评估技术可能有助于患者以正确的紧迫程度地向正确的护理导航。然而,最近的综述突出了这些技术的真实可用性的文献中的差距。目标我们试图探讨一种如此症状评估技术,ADA在初级保健环境中的可用性,可接受性和效用。邀请参加南伦敦初级保健诊所的新投诉的方法分流使用ADA症状评估移动应用程序的自定义版本。该探索性试验研究是在2017年11月至2018年1月在20,000名注册患者的实践中进行的。要求参与者在需要提供关于学习智能手机上的关于他们的申诉,如果需要提供援助。在完成ADA自我评估后,通过自我完成的研究问卷收集对应用的看法及其效用。结果为期3个月,523名患者参加。大多数是女性(n = 325,62.1%),平均年龄为39.79岁(SD 17.7岁),比例增加(413/506,81.6%)的工作年龄个体(15-64岁),而不是一般人群( 66.0%)。参与者评估ADA的易用性高,大多数(511/522,97.8%)报告这是非常或非常容易的。大多数人将再次使用ADA(443/503,88.1%)并同意他们会向朋友或相对推荐(444/520,85.3%)。我们在受访者中确定了许多年龄相关的趋势,为更多年轻受访者报告ADA提供了有用的建议(50/54,93%,18-24岁,据报道有用)的定向趋势,而不是旧的受访者(19 / 32,59%,70岁以上的成年人报告有用)。我们发现任何有可能性问题的性别差异都没有。虽然大多数受访者报告说,使用症状检查者的追求行为没有差异(425/494,86.0%),但少数少数群体(63/494,12.8%)报告他们将使用低强度护理如自我护理,药房或延迟预约。对于18-24岁(11/50,22%)的患者比70 +(0/28,0%)较高。结论这项探索性试验研究,数字症状检查器被评为初级保健环境中的患者高度可用性,可接受。需要进一步的研究来确认该应用程序是否可能适当地指导患者及时关心,并了解这可能会为卫生系统节省资源。还需要更多的工作来确保效益同样地累积给旧年龄组。

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