Digitizing clinical trials

数字健康 临床试验 计算机科学 数据科学 心理干预 分析 自动识别和数据采集 医疗保健 医学 护理部 病理 经济 语音识别 经济增长
作者
Omer T. Inan,Pamela Tenaerts,Sheila A. Prindiville,Harmony R. Reynolds,Don S. Dizon,Katharine Cooper‐Arnold,Mintu P. Turakhia,Mark J. Pletcher,Kenzie L. Preston,Harlan M. Krumholz,Benjamin M. Marlin,Kenneth D. Mandl,Predrag Klasnja,Bonnie Spring,Erin Iturriaga,Rebecca Campo,Patrice Desvigne‐Nickens,Yves Rosenberg,Steven R. Steinhubl,Robert M. Califf
出处
期刊:npj digital medicine [Nature Portfolio]
卷期号:3 (1) 被引量:239
标识
DOI:10.1038/s41746-020-0302-y
摘要

Abstract Clinical trials are a fundamental tool used to evaluate the efficacy and safety of new drugs and medical devices and other health system interventions. The traditional clinical trials system acts as a quality funnel for the development and implementation of new drugs, devices and health system interventions. The concept of a “digital clinical trial” involves leveraging digital technology to improve participant access, engagement, trial-related measurements, and/or interventions, enable concealed randomized intervention allocation, and has the potential to transform clinical trials and to lower their cost. In April 2019, the US National Institutes of Health (NIH) and the National Science Foundation (NSF) held a workshop bringing together experts in clinical trials, digital technology, and digital analytics to discuss strategies to implement the use of digital technologies in clinical trials while considering potential challenges. This position paper builds on this workshop to describe the current state of the art for digital clinical trials including (1) defining and outlining the composition and elements of digital trials; (2) describing recruitment and retention using digital technology; (3) outlining data collection elements including mobile health, wearable technologies, application programming interfaces (APIs), digital transmission of data, and consideration of regulatory oversight and guidance for data security, privacy, and remotely provided informed consent; (4) elucidating digital analytics and data science approaches leveraging artificial intelligence and machine learning algorithms; and (5) setting future priorities and strategies that should be addressed to successfully harness digital methods and the myriad benefits of such technologies for clinical research.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
董星辰完成签到 ,获得积分10
刚刚
Moudexiao完成签到 ,获得积分10
刚刚
大个应助胡自律采纳,获得10
1秒前
朴素凡阳完成签到,获得积分10
2秒前
xiuxiu发布了新的文献求助10
2秒前
nanhu完成签到,获得积分10
2秒前
2秒前
2秒前
dd发布了新的文献求助10
3秒前
大个应助潘岩采纳,获得10
3秒前
sevenlalala完成签到,获得积分10
3秒前
chenkui完成签到,获得积分10
3秒前
3秒前
yuxiaohua发布了新的文献求助10
3秒前
4秒前
4秒前
4秒前
4秒前
tutu27发布了新的文献求助10
4秒前
lq完成签到,获得积分10
4秒前
4秒前
小石完成签到,获得积分10
4秒前
天天快乐应助糊涂的天思采纳,获得10
5秒前
Ya完成签到 ,获得积分10
5秒前
5秒前
5秒前
果心纯完成签到,获得积分10
5秒前
6秒前
6秒前
fhghhhjh完成签到,获得积分10
7秒前
苹果山芙完成签到,获得积分10
7秒前
yingji完成签到,获得积分10
7秒前
ww发布了新的文献求助10
7秒前
科研小白完成签到,获得积分10
8秒前
于鹏完成签到,获得积分10
8秒前
茶茶发布了新的文献求助10
9秒前
ALinaLi完成签到,获得积分10
9秒前
义气的惜霜完成签到 ,获得积分10
9秒前
欧阳小枫完成签到 ,获得积分10
9秒前
俊逸棒球发布了新的文献求助10
9秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
AnnualResearch andConsultation Report of Panorama survey and Investment strategy onChinaIndustry 1000
卤化钙钛矿人工突触的研究 1000
Engineering for calcareous sediments : proceedings of the International Conference on Calcareous Sediments, Perth 15-18 March 1988 / edited by R.J. Jewell, D.C. Andrews 1000
Continuing Syntax 1000
Signals, Systems, and Signal Processing 610
2026 Hospital Accreditation Standards 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6263269
求助须知:如何正确求助?哪些是违规求助? 8085195
关于积分的说明 16894147
捐赠科研通 5333760
什么是DOI,文献DOI怎么找? 2839074
邀请新用户注册赠送积分活动 1816542
关于科研通互助平台的介绍 1670273