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与计算机协商:新前沿。

Consulting with a computer: New frontiers.

机构信息

PhD, MFM, MBBS, Grad Dip Pain Med, FRACGP, FACRRM, FAIDH, FAICD, Director of Research, Outcome Health, Vic; Adjunct Associate Professor in Health Informatics, Centre for the Digital Transformation of Health, The University of Melbourne, Vic.

MD, Associate Professor of Medicine, Robert Larner College of Medicine, The University of Vermont, VT; Medical Director, Adult Primary Care, South Burlington, The University of Vermont Medical Center, VT.

出版信息

Aust J Gen Pract. 2020 Sep;49(9):612-614. doi: 10.31128/AJGP-05-20-5400.

DOI:10.31128/AJGP-05-20-5400
PMID:32864673
Abstract

BACKGROUND

General practice is now completely computerised yet still largely reflects the habits and culture of the paper records that these computer programs have replaced. Technology is advancing rapidly, and computers are poised to start interacting (or intruding) in the consultation in new ways that practitioners (GPs) will once again need to understand and integrate.

OBJECTIVE

The aim of this article is to describe the developing trends in computing, data and intelligence, and demonstrate to GPs how to best use the examination room computer to enhance care of patients, prepare for upcoming revolutionary changes and continue to connect with patients.

DISCUSSION

Using two real-world examples, this article explains the complexity of the changing environment and implications for the patient-doctor relationship, and offers guidance for change.

摘要

背景

全科医学现在已经完全实现了计算机化,但仍在很大程度上反映了这些计算机程序所取代的纸质记录的习惯和文化。技术正在迅速发展,计算机即将开始以新的方式在咨询中进行交互(或干扰),而医生(全科医生)将再次需要理解和整合这些方式。

目的

本文的目的是描述计算、数据和智能的发展趋势,并向全科医生展示如何最好地利用诊室计算机来增强对患者的护理,为即将到来的革命性变化做准备,并继续与患者保持联系。

讨论

本文通过两个现实世界的例子解释了不断变化的环境的复杂性及其对医患关系的影响,并提供了变革的指导。

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引用本文的文献

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Physicians' and Patients' Expectations From Digital Agents for Consultations: Interview Study Among Physicians and Patients.医生和患者对数字代理咨询的期望:对医生和患者的访谈研究。
JMIR Hum Factors. 2024 Mar 18;11:e49647. doi: 10.2196/49647.
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Diachronic and synchronic variation in the performance of adaptive machine learning systems: the ethical challenges.自适应机器学习系统表现的历时与共时变化:伦理挑战。
J Am Med Inform Assoc. 2023 Jan 18;30(2):361-366. doi: 10.1093/jamia/ocac218.