Hospital Is Not the Home: Lessons From Implementing Remote Technology to Support Acute Inpatient and Transitional Care in the Home in the United States and United Kingdom.

IF 5.8 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Matt Wilkes, Annabel Kramer, Juliana Pugmire, Christopher Pilkington, Benjamin Zaniello, Nicole Zahradka
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Abstract

The COVID-19 pandemic, patient preference, and economic opportunity are shifting acute care from the hospital to the home, supported by the transformation in remote monitoring technology. Monitoring patients with digital medical devices gives unprecedented insight into their physiology. However, this technology does not exist in a vacuum. Distinguishing pathology from physiological variability, user error, or device limitations is challenging. In a hospital, patients are monitored in a contrived environment. Monitoring at home instead captures activities of daily living alongside patients' trajectory of disease and recovery. Both settings make for "noisy" data. However, we are familiar with hospital noise, accounting for it in our practice and perceptions of normal. Home monitoring as a diagnostic intervention introduces a new set of downstream consequences, dependent on device, cadence of collection, adherence, duration, alarm thresholds, and escalation criteria. We must accept greater ambiguity and contextualize vital signs. All devices balance accuracy with acceptability, so compromises are inevitable and perfect data should not be expected. Alarms must be specific as well as sensitive, balancing clinical risk with capacity for response. By setting expectations around data from the home, we can smooth the adoption of remote monitoring and accelerate the transition of acute care.

医院不是家:美国和英国实施远程技术支持急性住院病人和家庭过渡护理的经验教训。
非结构化:在远程监控技术变革的支持下,大流行病、患者偏好和经济机遇正在将急症护理从医院转向家庭。通过数字医疗设备对患者进行监测,可以前所未有地深入了解他们的生理状况。然而,这项技术并非存在于真空中。将病理学与生理变化、用户错误或设备限制区分开来具有挑战性。在医院里,病人是在一个人为的环境中接受监控的。而在家中进行的监测则能捕捉到患者的日常生活活动以及疾病和康复的轨迹。这两种环境都会产生 "噪音 "数据。然而,我们对医院的噪音并不陌生,在我们的实践和对正常情况的认识中都会考虑到这一点。家庭监测作为一种诊断干预措施,会带来一系列新的下游后果,这些后果取决于设备、收集的节奏、坚持程度、持续时间、警报阈值和升级标准。我们必须接受更大的模糊性,并将生命体征情景化。所有设备都要在准确性和可接受性之间取得平衡,妥协在所难免,不应期望数据完美无缺。警报必须具体而敏感,在临床风险与响应能力之间取得平衡。通过设定对家庭数据的期望值,我们可以顺利采用远程监控并加快急症护理的过渡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
14.40
自引率
5.40%
发文量
654
审稿时长
1 months
期刊介绍: The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.
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