在直接面向消费者的紧急远程医疗会诊中,自我分诊应用程序转诊后的结果。

IF 2.8 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Telemedicine and e-Health Pub Date : 2024-08-01 Epub Date: 2024-05-28 DOI:10.1089/tmj.2024.0126
Tarso Augusto Duenhas Accorsi, Flavio Tocci Moreira, Anderson Aires Eduardo, Renata Albaladejo Morbeck, Karen Francine Köhler, Karine De Amicis Lima, Carlos Henrique Sartorato Pedrotti
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引用次数: 0

摘要

背景:在直接面向消费者的远程医疗(TM)紧急会诊中,需要对移动应用指导下的自我分诊效果进行量化,这需要进一步研究。本研究旨在评估在远程紧急护理评估中,基于症状的自我管理移动应用决策算法所提供的转诊指导结果。研究方法2022 年 5 月至 2023 年 12 月期间进行了一项观察性回顾性单中心研究。纳入标准包括年龄大于 18 岁的个人,以及通过 EINSTEIN CONECTA 应用程序自发寻求虚拟紧急护理的个人。不包括因连接问题而无法完成就诊的患者。主要结果包括患者同意算法建议寻求亲临现场急救护理的比率,以及通过 TM 评估的病例中转诊至面对面评估的比率。该应用程序的算法采用基于症状的科学证据,建议转诊至急诊科(ED)。结果显示在连接到 TM 中心的 88,834 名患者中,有 53,302 人(60%)通过自我分诊无需进行虚拟医生评估。共有 35,532 名患者接受了 316 名值班医生的远程评估,得出了 1,125 项 ICD 编码诊断。其中,21,722 名患者(61.1%)最初通过自我分诊被建议到急诊室就诊,6,354 名患者(29.3%)在随后的医疗评估中被建议到急诊室就诊。在自我分诊后被建议继续接受虚拟治疗的 13,810 名患者中,有 157 人(1.1%)被转诊接受现场评估。结论:在大约五分之三的 TM 咨询中,自我分诊有效减少了医生接诊的需求。尽管以科学证据为基础,但基于症状的转诊算法显示出较高的灵敏度,但与医生决策的相关性较差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Outcome After Self-Triage App Referral in Urgent Direct-to-Consumer Telemedicine Encounter.

Background: The quantification of self-triage effectiveness, guided by mobile applications, in urgent direct-to-consumer telemedicine (TM) encounters requires further investigation. The objective of this study was to evaluate the outcomes of referral guidance provided by a symptom-based self-management mobile application decision algorithm in the context of remote urgent care assessments. Methods: An observational retrospective single-center study was conducted from May 2022 to December 2023. The inclusion criteria encompassed individuals aged >18 years old, and those spontaneously seeking virtual emergency care through the EINSTEIN CONECTA application. Patients experiencing connectivity issues, preventing completion of the encounter, were excluded. The primary outcomes included the rate of patient concurrence with the algorithm's recommendation for seeking in-person emergency care and the referral rate to face-to-face assessment among cases evaluated through TM. The application's algorithm employs scientific evidence based on symptoms to recommend referrals to emergency departments (EDs). Results: Out of 88,834 patients connected to the TM Center, self-triage obviated the need for virtual physician assessment in 53,302 (60%) encounters. A total of 35,532 patients were remotely evaluated by 316 on-duty physicians, resulting in 1,125 ICD-coded diagnoses. Among these, 21,722 (61.1%) were initially advised by self-triage to visit the ED, with subsequent medical assessment leading to in-person referrals in 6,354 (29.3%) of the evaluations. Of the 13,810 patients recommended to continue with virtual care post-self-triage, 157 (1.1%) were referred for in-person assessment. Conclusions: Self-triage effectively reduced the need for physician encounters in approximately three-fifths of TM consultations. Despite being based on scientific evidence, symptom-based referral algorithms demonstrated high sensitivity but poor correlation with physician decision-making.

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来源期刊
Telemedicine and e-Health
Telemedicine and e-Health 医学-卫生保健
CiteScore
8.80
自引率
6.40%
发文量
270
审稿时长
2.3 months
期刊介绍: Telemedicine and e-Health is the leading peer-reviewed journal for cutting-edge telemedicine applications for achieving optimal patient care and outcomes. It places special emphasis on the impact of telemedicine on the quality, cost effectiveness, and access to healthcare. Telemedicine applications play an increasingly important role in health care. They offer indispensable tools for home healthcare, remote patient monitoring, and disease management, not only for rural health and battlefield care, but also for nursing home, assisted living facilities, and maritime and aviation settings. Telemedicine and e-Health offers timely coverage of the advances in technology that offer practitioners, medical centers, and hospitals new and innovative options for managing patient care, electronic records, and medical billing.
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