Usability and effectiveness of a telehealth artificial-intelligence powered platform: perspectives from patients and providers in a mixed-methods study.

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES JMIR Formative Research Pub Date : 2024-10-15 DOI:10.2196/62742
Ekta Jain, Srishti Gupta, Vandana Yadav, Stan Kachnowski
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Abstract

Background: Telemedicine has revolutionized healthcare by significantly enhancing accessibility. However, the acceptability and uptake of tele-medicine is prone to various hindering factors. Studies have shown that both patients and healthcare providers appreciate the aspect of convenience. However, healthcare providers' limited understanding of or inability to leverage the technology involved can be a barrier. With advancements in telemedicine technologies, understanding the viewpoints of patients and providers is crucial for an effective and acceptable telemedicine service. This study reports findings from a usability study of HelixVM™, a telemedicine platform that uses an Artificial Intelligence (AI)-powered triage for healthcare delivery. We discuss aspects of asynchronous medicine, healthcare accessibility, saving time, productivity, data exchange, security, privacy, AI-powered triage and quality of care.

Objective: To assess the usability and effectiveness of the HelixVM marketplace platform.

Methods: We recruited 102 patients and 12 providers in a mixed-methods study design involving surveys, and in-depth structured interviews with a subset of the providers only. The survey questionnaires are a modified version of the telehealth utility questionnaire. We analyzed the patient's data using descriptive statistics and factor analysis to identify latent demographic patterns. For the providers data, we used a deductive thematic analysis approach to identify key themes from the interviews and interpreted overall sentiments of the providers for negative, neutral or positive. We also calculated percentages of different responses for the providers from the surveys and interviews, where applicable.

Results: Patients: Overall, 86% of patients are satisfied with HelixVM and 89% will use the services again. More than 90% of patients agreed that HelixVM improves access to healthcare, saves time and that the platform is an acceptable way to receive healthcare. Chi-square tests demonstrate statistical significance for all the survey questions (p-value <.001). Results from factor analysis show a higher propensity of female gender in middle age groups whose encounter type is fast-track, self-report medium level of tech-savviness and residing in the South regions of US rate the platform more positively. Providers: Thematic analysis identified themes of asynchronous medicine in terms of accessibility and quality of care, time and productivity, integration within the workflow, data exchange and AI-triage. Certain challenges of incomplete data in patient chart and its impact on provider time are cited. Suggestions for improvements include options to ensure completeness of patient questionnaires and better screening to ensure that only asynchronous 'qualified' patients get through to the provider.

Conclusions: Overall, our study findings indicate a positive experience for patients and providers. The use of fast-track prescription is favorable as compared to traditional telemedicine. Some concerns on data completeness, gaps and accuracy exist. Suggestions are provided for improvement. This study adds to the knowledgebase of existing literature and provides for a detailed analysis into the real-world implementation of a telemedicine market-place platform.

Clinicaltrial:

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远程医疗人工智能平台的可用性和有效性:一项混合方法研究中患者和医疗服务提供者的观点。
背景:远程医疗大大提高了医疗服务的可及性,从而彻底改变了医疗服务。然而,远程医疗的可接受性和使用率容易受到各种因素的阻碍。研究表明,患者和医疗服务提供者都对远程医疗的便利性表示赞赏。然而,医疗服务提供者对相关技术的了解有限或无法利用这些技术可能会成为障碍。随着远程医疗技术的发展,了解患者和医疗服务提供者的观点对于提供有效、可接受的远程医疗服务至关重要。本研究报告了对 HelixVM™ 的可用性研究结果,HelixVM™ 是一个远程医疗平台,使用人工智能(AI)驱动的分诊技术提供医疗服务。我们讨论了异步医疗、医疗可及性、节省时间、生产率、数据交换、安全性、隐私、人工智能驱动的分诊和医疗质量等方面的问题:评估 HelixVM 市场平台的可用性和有效性:我们采用混合方法研究设计,招募了 102 名患者和 12 名医疗服务提供者,其中包括调查问卷和对部分医疗服务提供者的深入结构性访谈。调查问卷是远程医疗效用问卷的修订版。我们使用描述性统计和因素分析法对患者数据进行了分析,以确定潜在的人口统计模式。对于医疗服务提供者的数据,我们采用了演绎式主题分析方法,从访谈中找出关键主题,并将医疗服务提供者的总体情绪解释为负面、中性或正面。我们还酌情计算了调查和访谈中医疗服务提供者不同回答的百分比:患者:总体而言,86% 的患者对 HelixVM 表示满意,89% 的患者将再次使用该服务。超过 90% 的患者认为 HelixVM 提高了医疗服务的可及性,节省了时间,并且该平台是一种可接受的医疗服务方式。卡方检验表明,所有调查问题均具有统计学意义(P 值结论):总体而言,我们的研究结果表明,患者和医疗服务提供者都获得了积极的体验。与传统远程医疗相比,快速处方的使用是有利的。在数据完整性、差距和准确性方面存在一些问题。研究提出了改进建议。本研究补充了现有文献的知识库,并对远程医疗市场平台的实际实施情况进行了详细分析:
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来源期刊
JMIR Formative Research
JMIR Formative Research Medicine-Medicine (miscellaneous)
CiteScore
2.70
自引率
9.10%
发文量
579
审稿时长
12 weeks
期刊最新文献
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