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在线症状检查器的分诊和诊断准确性:系统评价。

Triage and Diagnostic Accuracy of Online Symptom Checkers: Systematic Review.

机构信息

Self-Care Academic Research Unit (SCARU), Department of Primary Care and Public Health, Imperial College London, London, United Kingdom.

出版信息

J Med Internet Res. 2023 Jun 2;25:e43803. doi: 10.2196/43803.

Abstract

BACKGROUND

In the context of a deepening global shortage of health workers and, in particular, the COVID-19 pandemic, there is growing international interest in, and use of, online symptom checkers (OSCs). However, the evidence surrounding the triage and diagnostic accuracy of these tools remains inconclusive.

OBJECTIVE

This systematic review aimed to summarize the existing peer-reviewed literature evaluating the triage accuracy (directing users to appropriate services based on their presenting symptoms) and diagnostic accuracy of OSCs aimed at lay users for general health concerns.

METHODS

Searches were conducted in MEDLINE, Embase, CINAHL, Health Management Information Consortium (HMIC), and Web of Science, as well as the citations of the studies selected for full-text screening. We included peer-reviewed studies published in English between January 1, 2010, and February 16, 2022, with a controlled and quantitative assessment of either or both triage and diagnostic accuracy of OSCs directed at lay users. We excluded tools supporting health care professionals, as well as disease- or specialty-specific OSCs. Screening and data extraction were carried out independently by 2 reviewers for each study. We performed a descriptive narrative synthesis.

RESULTS

A total of 21,296 studies were identified, of which 14 (0.07%) were included. The included studies used clinical vignettes, medical records, or direct input by patients. Of the 14 studies, 6 (43%) reported on triage and diagnostic accuracy, 7 (50%) focused on triage accuracy, and 1 (7%) focused on diagnostic accuracy. These outcomes were assessed based on the diagnostic and triage recommendations attached to the vignette in the case of vignette studies or on those provided by nurses or general practitioners, including through face-to-face and telephone consultations. Both diagnostic accuracy and triage accuracy varied greatly among OSCs. Overall diagnostic accuracy was deemed to be low and was almost always lower than that of the comparator. Similarly, most of the studies (9/13, 69 %) showed suboptimal triage accuracy overall, with a few exceptions (4/13, 31%). The main variables affecting the levels of diagnostic and triage accuracy were the severity and urgency of the condition, the use of artificial intelligence algorithms, and demographic questions. However, the impact of each variable differed across tools and studies, making it difficult to draw any solid conclusions. All included studies had at least one area with unclear risk of bias according to the revised Quality Assessment of Diagnostic Accuracy Studies-2 tool.

CONCLUSIONS

Although OSCs have potential to provide accessible and accurate health advice and triage recommendations to users, more research is needed to validate their triage and diagnostic accuracy before widescale adoption in community and health care settings. Future studies should aim to use a common methodology and agreed standard for evaluation to facilitate objective benchmarking and validation.

TRIAL REGISTRATION

PROSPERO CRD42020215210; https://tinyurl.com/3949zw83.

摘要

背景

在全球卫生工作者短缺加剧的背景下,特别是在 COVID-19 大流行期间,国际社会对面向普通用户的在线症状检查器(OSC)越来越感兴趣并加以利用。然而,这些工具在分诊和诊断准确性方面的证据仍不明确。

目的

本系统评价旨在总结现有的同行评议文献,评估面向普通用户的在线症状检查器的分诊准确性(根据患者的症状将其引导至合适的服务)和诊断准确性。

方法

在 MEDLINE、Embase、CINAHL、卫生管理信息联合会(HMIC)和 Web of Science 中进行检索,并对入选的进行全文筛选的研究进行了参考文献检索。我们纳入了 2010 年 1 月 1 日至 2022 年 2 月 16 日期间以英文发表的、针对普通用户的、对 OSC 的分诊和诊断准确性进行了控制和定量评估的同行评议研究。我们排除了支持医疗保健专业人员的工具以及针对特定疾病或专科的 OSC。每个研究均由 2 名评审员独立进行筛选和数据提取。我们进行了描述性叙述性综合。

结果

共确定了 21296 项研究,其中有 14 项(0.07%)被纳入。纳入的研究使用了临床病例、医疗记录或患者的直接输入。在 14 项研究中,有 6 项(43%)报告了分诊和诊断准确性,7 项(50%)专注于分诊准确性,1 项(7%)专注于诊断准确性。在病例研究中,根据病例中附带的诊断和分诊建议来评估这些结果,或者根据护士或全科医生提供的建议来评估,包括面对面和电话咨询。OSC 的诊断准确性和分诊准确性差异很大。总体诊断准确性被认为较低,而且几乎总是低于对照。同样,大多数研究(9/13,69%)总体分诊准确性欠佳,仅有少数例外(4/13,31%)。影响诊断和分诊准确性的主要变量是病情的严重程度和紧急程度、人工智能算法的使用以及人口统计学问题。然而,每个变量对不同工具和研究的影响不同,因此难以得出任何确凿的结论。所有纳入的研究根据修订后的诊断准确性研究质量评估工具-2 均至少有一个领域存在偏倚风险不明确。

结论

尽管 OSC 有可能为用户提供可及且准确的健康建议和分诊建议,但在社区和医疗保健环境中广泛采用之前,还需要更多的研究来验证其分诊和诊断准确性。未来的研究应旨在使用共同的方法和商定的评估标准,以促进客观的基准测试和验证。

试验注册

PROSPERO CRD42020215210;https://tinyurl.com/3949zw83。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf86/10276326/7bc91696bb0e/jmir_v25i1e43803_fig1.jpg

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