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数字表型分析与患者生成的健康数据在外科护理结局测量中的应用:一项范围综述

Digital Phenotyping and Patient-Generated Health Data for Outcome Measurement in Surgical Care: A Scoping Review.

作者信息

Jayakumar Prakash, Lin Eugenia, Galea Vincent, Mathew Abraham J, Panda Nikhil, Vetter Imelda, Haynes Alex B

机构信息

Department of Surgery and Perioperative Care, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA.

School of Medicine, New York Medical College, Valhalla, NY 10595, USA.

出版信息

J Pers Med. 2020 Dec 15;10(4):282. doi: 10.3390/jpm10040282.

Abstract

Digital phenotyping-the moment-by-moment quantification of human phenotypes in situ using data related to activity, behavior, and communications, from personal digital devices, such as smart phones and wearables-has been gaining interest. Personalized health information captured within free-living settings using such technologies may better enable the application of patient-generated health data (PGHD) to provide patient-centered care. The primary objective of this scoping review is to characterize the application of digital phenotyping and digitally captured active and passive PGHD for outcome measurement in surgical care. Secondarily, we synthesize the body of evidence to define specific areas for further work. We performed a systematic search of four bibliographic databases using terms related to "digital phenotyping and PGHD," "outcome measurement," and "surgical care" with no date limits. We registered the study (Open Science Framework), followed strict inclusion/exclusion criteria, performed screening, extraction, and synthesis of results in line with the PRISMA Extension for Scoping Reviews. A total of 224 studies were included. Published studies have accelerated in the last 5 years, originating in 29 countries (mostly from the USA, = 74, 33%), featuring original prospective work ( = 149, 66%). Studies spanned 14 specialties, most commonly orthopedic surgery ( = 129, 58%), and had a postoperative focus ( = 210, 94%). Most of the work involved research-grade wearables ( = 130, 58%), prioritizing the capture of activity ( = 165, 74%) and biometric data ( = 100, 45%), with a view to providing a tracking/monitoring function ( = 115, 51%) for the management of surgical patients. Opportunities exist for further work across surgical specialties involving smartphones, communications data, comparison with patient-reported outcome measures (PROMs), applications focusing on prediction of outcomes, monitoring, risk profiling, shared decision making, and surgical optimization. The rapidly evolving state of the art in digital phenotyping and capture of PGHD offers exciting prospects for outcome measurement in surgical care pending further work and consideration related to clinical care, technology, and implementation.

摘要

数字表型分析——利用来自智能手机和可穿戴设备等个人数字设备的与活动、行为及通信相关的数据,对人类表型进行实时原位量化——已日益受到关注。使用此类技术在自由生活环境中获取的个性化健康信息,可能会更好地推动患者生成的健康数据(PGHD)的应用,以提供以患者为中心的护理。本范围综述的主要目的是描述数字表型分析以及通过数字方式获取的主动和被动PGHD在外科护理结局测量中的应用。其次,我们综合证据以确定进一步研究的具体领域。我们使用与“数字表型分析和PGHD”、“结局测量”及“外科护理”相关的术语,对四个文献数据库进行了无时间限制的系统检索。我们对该研究进行了注册(开放科学框架),遵循严格的纳入/排除标准,按照PRISMA范围综述扩展版进行筛选、提取和结果综合。共纳入224项研究。过去5年发表的研究数量有所增加,来自29个国家(大多来自美国,n = 74,占33%),以原创前瞻性研究为主(n = 149,占66%)。研究涵盖14个专科,最常见的是骨科手术(n = 129,占58%),且重点关注术后情况(n = 210,占94%)。大多数研究涉及研究级可穿戴设备(n = 130,占58%),优先获取活动数据(n = 165,占74%)和生物特征数据(n = 100,占45%),旨在为外科患者管理提供跟踪/监测功能(n = 115,占51%)。在涉及智能手机、通信数据、与患者报告结局测量(PROMs)进行比较、侧重于结局预测的应用、监测、风险评估、共同决策以及手术优化等方面,各外科专科仍有进一步研究的机会。数字表型分析和PGHD获取技术的快速发展,为外科护理结局测量带来了令人兴奋的前景,但仍有待进一步开展与临床护理、技术及实施相关工作并进行考量。

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