Suppr超能文献

居家血液透析慢性病患者的远程监测系统:共现增强设计的现场测试

Remote Monitoring Systems for Chronic Patients on Home Hemodialysis: Field Test of a Copresence-Enhanced Design.

作者信息

Liu Na, Kim Jinman, Jung Younhyun, Arisy Adani, Nicdao Mary Ann, Mikaheal Mary, Baldacchino Tanya, Khadra Mohamed, Sud Kamal

机构信息

School of Information Technologies, Sydney, Australia.

Biomedical and Multimedia Information Technology (BMIT) Group, School of Information Technologies, Sydney, Australia.

出版信息

JMIR Hum Factors. 2017 Aug 29;4(3):e21. doi: 10.2196/humanfactors.7078.

Abstract

BACKGROUND

Patients undertaking long-term and chronic home hemodialysis (HHD) are subject to feelings of isolation and anxiety due to the absence of physical contact with their health care professionals and lack of feedback in regards to their dialysis treatments. Therefore, it is important for these patients to feel the "presence" of the health care professionals remotely while on hemodialysis at home for better compliance with the dialysis regime and to feel connected with health care professionals.

OBJECTIVE

This study presents an HHD system design for hemodialysis patients with features to enhance patient's perceived "copresence" with their health care professionals. Various mechanisms to enhance this perception were designed and implemented, including digital logbooks, emotion sharing, and feedback tools. The mechanism in our HHD system aims to address the limitations associated with existing self-monitoring tools for HHD patients.

METHODS

A field trial involving 3 nurses and 74 patients was conducted to test the pilot implementation of the copresence design in our HHD system. Mixed method research was conducted to evaluate the system, including surveys, interviews, and analysis of system data.

RESULTS

Patients created 2757 entries of dialysis cases during the period of study. Altogether there were 492 entries submitted with "Very Happy" as the emotional status, 2167 entries with a "Happy" status, 56 entries with a "Neutral" status, 18 entries with an "Unhappy" status, and 24 entries with a "Very unhappy" status. Patients felt assured to share their emotions with health care professionals. Health care professionals were able to prioritize the review of the entries based on the emotional status and also felt assured to see patients' change in mood. There were 989 entries sent with short notes. Entries with negative emotions had a higher percentage of supplementary notes entered compared to the entries with positive and neutral emotions. The qualitative data further showed that the HHD system was able to improve patients' feelings of being connected with their health care professionals and thus enhance their self-care on HHD. The health care professionals felt better assured with patients' status with the use of the system and reported improved productivity and satisfaction with the copresence enhancement mechanism. The survey on the system usability indicated a high level of satisfaction among patients and nurses.

CONCLUSIONS

The copresence enhancement design complements the conventional use of a digitized HHD logbook and will further benefit the design of future telehealth systems.

摘要

背景

进行长期慢性家庭血液透析(HHD)的患者,由于与医护人员缺乏身体接触,且在透析治疗方面缺乏反馈,容易产生孤独感和焦虑情绪。因此,对于这些患者来说,在家进行血液透析时能远程感受到医护人员的“在场”非常重要,这有助于他们更好地遵守透析方案,并感觉与医护人员保持联系。

目的

本研究提出一种针对血液透析患者的HHD系统设计,其特点是能增强患者对医护人员的“共同在场感”。设计并实施了多种增强这种感受的机制,包括数字日志、情感分享和反馈工具。我们HHD系统中的机制旨在解决现有HHD患者自我监测工具的局限性。

方法

进行了一项涉及3名护士和74名患者的现场试验,以测试我们HHD系统中共同在场设计的试点实施情况。采用混合方法研究对系统进行评估,包括调查、访谈和系统数据分析。

结果

在研究期间,患者创建了2757条透析病例记录。其中,共有492条记录的情绪状态为“非常开心”,2167条为“开心”,56条为“中性”,18条为“不开心”,24条为“非常不开心”。患者放心地与医护人员分享他们的情绪。医护人员能够根据情绪状态对记录的查看进行优先级排序,并且看到患者情绪的变化也感到放心。有989条记录附带了简短说明。与积极和中性情绪的记录相比,消极情绪记录中输入补充说明的百分比更高。定性数据进一步表明,HHD系统能够改善患者与医护人员保持联系的感觉,从而增强他们在家庭血液透析中的自我护理能力。医护人员通过使用该系统对患者的状态更放心,并报告说共同在场增强机制提高了工作效率和满意度。关于系统可用性的调查表明患者和护士的满意度很高。

结论

共同在场增强设计补充了数字化HHD日志的传统用途,并将进一步有利于未来远程医疗系统的设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/5596297/747922f54c21/humanfactors_v4i3e21_fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验