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急诊科入院时假设的 SARS-CoV-2 即时检测模型:快速成本效益分析。

Modelling of hypothetical SARS-CoV-2 point-of-care tests on admission to hospital from A&E: rapid cost-effectiveness analysis.

机构信息

School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK.

Leeds Institute of Health Sciences, University of Leeds, Leeds, UK.

出版信息

Health Technol Assess. 2021 Mar;25(21):1-68. doi: 10.3310/hta25210.

Abstract

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes coronavirus disease 2019. At the time of writing (October 2020), the number of cases of COVID-19 had been approaching 38 million and more than 1 million deaths were attributable to it. SARS-CoV-2 appears to be highly transmissible and could rapidly spread in hospital wards.

OBJECTIVE

The work undertaken aimed to estimate the clinical effectiveness and cost-effectiveness of viral detection point-of-care tests for detecting SARS-CoV-2 compared with laboratory-based tests. A further objective was to assess occupancy levels in hospital areas, such as waiting bays, before allocation to an appropriate bay.

PERSPECTIVE/SETTING: The perspective was that of the UK NHS in 2020. The setting was a hypothetical hospital with an accident and emergency department.

METHODS

An individual patient model was constructed that simulated the spread of disease and mortality within the hospital and recorded occupancy levels. Thirty-two strategies involving different hypothetical SARS-CoV-2 tests were modelled. Recently published desirable and acceptable target product profiles for SARS-CoV-2 point-of-care tests were modelled. Incremental analyses were undertaken using both incremental cost-effectiveness ratios and net monetary benefits, and key patient outcomes, such as death and intensive care unit care, caused directly by COVID-19 were recorded.

RESULTS

A SARS-CoV-2 point-of-care test with a desirable target product profile appears to have a relatively small number of infections, a low occupancy level within the waiting bays, and a high net monetary benefit. However, if hospital laboratory testing can produce results in 6 hours, then the benefits of point-of-care tests may be reduced. The acceptable target product profiles performed less well and had lower net monetary benefits than both a laboratory-based test with a 24-hour turnaround time and strategies using data from currently available SARS-CoV-2 point-of-care tests. The desirable and acceptable point-of-care test target product profiles had lower requirement for patients to be in waiting bays before being allocated to an appropriate bay than laboratory-based tests, which may be of high importance in some hospitals. Tests that appeared more cost-effective also had better patient outcomes.

LIMITATIONS

There is considerable uncertainty in the values for key parameters within the model, although calibration was undertaken in an attempt to mitigate this. The example hospital simulated will also not match those of decision-makers deciding on the clinical effectiveness and cost-effectiveness of introducing SARS-CoV-2 point-of-care tests. Given these limitations, the results should be taken as indicative rather than definitive, particularly cost-effectiveness results when the relative cost per SARS-CoV-2 point-of-care test is uncertain.

CONCLUSIONS

Should a SARS-CoV-2 point-of-care test with a desirable target product profile become available, this appears promising, particularly when the reduction on the requirements for waiting bays before allocation to a SARS-CoV-2-infected bay, or a non-SARS-CoV-2-infected bay, is considered. The results produced should be informative to decision-makers who can identify the results most pertinent to their specific circumstances.

FUTURE WORK

More accurate results could be obtained when there is more certainty on the diagnostic accuracy of, and the reduction in time to test result associated with, SARS-CoV-2 point-of-care tests, and on the impact of these tests on occupancy of waiting bays and isolation bays. These parameters are currently uncertain.

FUNDING

This report was commissioned by the National Institute for Health Research (NIHR) Evidence Synthesis programme as project number 132154. This project was funded by the NIHR Health Technology Assessment programme and will be published in full in ; Vol. 25, No. 21. See the NIHR Journals Library website for further project information.

摘要

背景

严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)是导致 2019 年冠状病毒病(COVID-19)的病毒。截至撰写本文(2020 年 10 月),COVID-19 病例数已接近 3800 万例,并有超过 100 万人死亡。SARS-CoV-2 似乎具有很强的传染性,并可能在医院病房中迅速传播。

目的

本研究旨在评估与实验室检测相比,用于检测 SARS-CoV-2 的病毒即时检测点检测的临床效果和成本效益。进一步的目标是评估医院区域(如等候区)的入住率,以便在分配到适当的区域之前进行评估。

观点/背景:该研究从英国国民保健制度(NHS)的角度出发,研究地点为一个假设的有急诊部的医院。

方法

构建了一个个体患者模型,模拟了医院内疾病的传播和死亡率,并记录了入住率。对 32 种不同的 SARS-CoV-2 检测方法进行了模拟。模拟了最近发表的 SARS-CoV-2 即时检测的理想和可接受的目标产品特性。使用增量成本效益比和净货币效益进行了增量分析,并记录了由 COVID-19 直接引起的关键患者结局,如死亡和重症监护治疗。

结果

具有理想目标产品特性的 SARS-CoV-2 即时检测似乎可以减少感染人数、降低等候区的入住率,并产生较高的净货币效益。然而,如果医院实验室检测可以在 6 小时内得出结果,那么即时检测的效益可能会降低。可接受的目标产品特性的表现不如实验室检测(24 小时检测)和使用现有 SARS-CoV-2 即时检测数据的策略,其净货币效益也较低。理想和可接受的即时检测目标产品特性与实验室检测相比,对患者在被分配到适当区域之前在等候区的停留时间要求较低,这在某些医院可能非常重要。表现出更高成本效益的检测方法也具有更好的患者结局。

局限性

模型中的关键参数存在很大的不确定性,尽管已经进行了校准以减轻这种影响。模拟的示例医院也可能与决策者对引入 SARS-CoV-2 即时检测的临床效果和成本效益的决策不一致。考虑到这些限制,结果应被视为指示性的,而不是确定性的,特别是当 SARS-CoV-2 即时检测的相对成本不确定时,其成本效益结果更应如此。

结论

如果出现具有理想目标产品特性的 SARS-CoV-2 即时检测,这似乎很有前景,特别是当考虑到在分配到 SARS-CoV-2 感染区或非 SARS-CoV-2 感染区之前,对等候区的入住要求的减少时。决策者可以从这些结果中获得信息,以确定最符合其特定情况的结果。

未来工作

当 SARS-CoV-2 即时检测的诊断准确性和检测结果时间的减少与这些检测对等候区和隔离区的入住率的影响更加确定时,将获得更准确的结果。这些参数目前还不确定。

资金

本报告由英国国家卫生研究所(NIHR)证据综合计划委托编写,项目编号为 132154。该项目由 NIHR 健康技术评估计划资助,将在 ; Vol. 25, No. 21. 中全文发表。请访问 NIHR 期刊库网站以获取更多项目信息。

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