Objectives: Comparisons of no-show rates between virtual and in-person models of care are commonly reported during evaluation, indicating how coveted improvements in attendance are to health service providers. This study seeks to synthesise the data from studies that make these comparisons, providing a more accurate indication of what may expected from the use of virtual care models for clinicians and administrators.

Study design: Systematic review and meta-analysis of 45 retrospective cohort studies.

Methods: A literature review involving five databases was conducted, identifying 441 articles for screening. 45 were included for further analysis. A Random effects model was used to calculate the effect size, with further analysis conducted to determine heterogeneity and publication bias.

Results: The Random effects model estimated a reduced likelihood non-attendance in patients receiving virtual care compared to in-person groups (OR = 0.61). An I² indicated a high degree of heterogeneity among the studies analysed. The Fail-Safe N suggested that the results are robust and not significantly influenced by publication bias.

Conclusions: The meta-analysis indicated that on average, telehealth models of care implemented since COVID-19 provide a moderate reduction in risk of patient non-attendance when compared to in-person alternatives.

Keywords: Attendance; Fail to attend; No show; Non-attendance; Telehealth; Telemedicine; Virtual care.

© 2025. Crown.

目标: 就诊率在虚拟护理模式和面对面护理模式之间的比较通常会在评估中被报告，这表明提高出席率对医疗服务提供者有多么重要。本研究旨在综合这些对比的研究数据，为临床医生和管理者使用虚拟护理模型的预期效果提供更准确的指标。

研究设计: 45项回顾性队列研究的系统评价和元分析。

方法: 进行了涉及五个数据库的文献综述，共筛选出441篇文章。其中45篇被纳入进一步分析。使用随机效应模型来计算效应大小，并进行进一步分析以确定异质性和发表偏倚。

结果: 随机效应模型估计患者在接受虚拟护理时的未出席概率比面对面群体低（OR = 0.61）。I²值表明各研究之间存在较高的异质性。Fail-Safe N值表明，结果具有鲁棒性和不受发表偏倚显著影响。

结论: 元分析结果显示，在平均情况下，自COVID-19以来实施的远程医疗护理模式相比面对面替代方案提供了中等程度的风险降低患者未出席率。

关键词: 出勤；缺席；未出现；不出席；远程医疗；远程医疗服务；虚拟护理。