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使用集成电子健康记录的 COVID-19 症状检查器后的患者体验与反馈:调查研究

Patient Experience and Feedback After Using an Electronic Health Record-Integrated COVID-19 Symptom Checker: Survey Study.

作者信息

Liu Andrew W, Odisho Anobel Y, Brown Iii William, Gonzales Ralph, Neinstein Aaron B, Judson Timothy J

机构信息

Center for Digital Health Innovation, University of California, San Francisco, San Francisco, CA, United States.

Department of Urology, University of California, San Francisco, San Francisco, CA, United States.

出版信息

JMIR Hum Factors. 2022 Sep 13;9(3):e40064. doi: 10.2196/40064.

DOI:10.2196/40064
PMID:35960593
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9472505/
Abstract

BACKGROUND

Symptom checkers have been widely used during the COVID-19 pandemic to alleviate strain on health systems and offer patients a 24-7 self-service triage option. Although studies suggest that users may positively perceive web-based symptom checkers, no studies have quantified user feedback after use of an electronic health record-integrated COVID-19 symptom checker with self-scheduling functionality.

OBJECTIVE

In this paper, we aimed to understand user experience, user satisfaction, and user-reported alternatives to the use of a COVID-19 symptom checker with self-triage and self-scheduling functionality.

METHODS

We launched a patient-portal-based self-triage and self-scheduling tool in March 2020 for patients with COVID-19 symptoms, exposures, or questions. We made an optional, anonymous Qualtrics survey available to patients immediately after they completed the symptom checker.

RESULTS

Between December 16, 2021, and March 28, 2022, there were 395 unique responses to the survey. Overall, the respondents reported high satisfaction across all demographics, with a median rating of 8 out of 10 and 288/395 (47.6%) of the respondents giving a rating of 9 or 10 out of 10. User satisfaction scores were not associated with any demographic factors. The most common user-reported alternatives had the web-based tool not been available were calling the COVID-19 telephone hotline and sending a patient-portal message to their physician for advice. The ability to schedule a test online was the most important symptom checker feature for the respondents. The most common categories of user feedback were regarding other COVID-19 services (eg, telephone hotline), policies, or procedures, and requesting additional features or functionality.

CONCLUSIONS

This analysis suggests that COVID-19 symptom checkers with self-triage and self-scheduling functionality may have high overall user satisfaction, regardless of user demographics. By allowing users to self-triage and self-schedule tests and visits, tools such as this may prevent unnecessary calls and messages to clinicians. Individual feedback suggested that the user experience for this type of tool is highly dependent on the organization's operational workflows for COVID-19 testing and care. This study provides insight for the implementation and improvement of COVID-19 symptom checkers to ensure high user satisfaction.

摘要

背景

在新冠疫情期间,症状检查器被广泛使用,以减轻卫生系统的压力,并为患者提供全天候的自助分诊选项。尽管研究表明用户可能对基于网络的症状检查器有积极的看法,但尚无研究对使用具有自助预约功能的电子健康记录集成新冠症状检查器后的用户反馈进行量化。

目的

在本文中,我们旨在了解用户对具有自我分诊和自我预约功能的新冠症状检查器的使用体验、满意度以及用户报告的替代使用方式。

方法

2020年3月,我们为有新冠症状、接触史或疑问的患者推出了一个基于患者门户的自我分诊和自我预约工具。患者完成症状检查器后,我们立即向他们提供了一份可选的匿名Qualtrics调查问卷。

结果

在2021年12月16日至2022年3月28日期间,该调查共收到395份独特回复。总体而言,所有人口统计学特征的受访者满意度都很高,中位数评分为8分(满分10分),395名受访者中有288人(47.6%)给出了9分或10分的评分。用户满意度得分与任何人口统计学因素均无关联。用户报告的最常见的替代使用方式(即没有该基于网络的工具时)是拨打新冠热线电话以及通过患者门户向医生发送信息寻求建议。对受访者来说,能够在线预约检测是症状检查器最重要的功能。用户反馈最常见的类别涉及其他新冠服务(如电话热线)、政策或程序,以及请求增加功能。

结论

该分析表明,具有自我分诊和自我预约功能的新冠症状检查器总体用户满意度可能较高,与用户人口统计学特征无关。通过允许用户自我分诊和自我预约检测及就诊,此类工具可以避免不必要地给临床医生打电话和发信息。个人反馈表明,这类工具的用户体验高度依赖于组织针对新冠检测和护理的操作流程。本研究为新冠症状检查器的实施和改进提供了见解,以确保较高的用户满意度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f1c/9472505/d0cd48b5e07a/humanfactors_v9i3e40064_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f1c/9472505/9d57b7edb5fa/humanfactors_v9i3e40064_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f1c/9472505/2d4b552e5e6e/humanfactors_v9i3e40064_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f1c/9472505/3aff1ac45f4b/humanfactors_v9i3e40064_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f1c/9472505/d0cd48b5e07a/humanfactors_v9i3e40064_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f1c/9472505/9d57b7edb5fa/humanfactors_v9i3e40064_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f1c/9472505/2d4b552e5e6e/humanfactors_v9i3e40064_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f1c/9472505/3aff1ac45f4b/humanfactors_v9i3e40064_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f1c/9472505/d0cd48b5e07a/humanfactors_v9i3e40064_fig4.jpg

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