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日本两个公共卫生中心辖区内的老年人监测系统(FESSy)的有效性:前瞻性观察研究。

Effectiveness of the Facility for Elderly Surveillance System (FESSy) in Two Public Health Center Jurisdictions in Japan: Prospective Observational Study.

作者信息

Kurita Junko, Hori Motomi, Yamaguchi Sumiyo, Ogiwara Aiko, Saito Yurina, Sugiyama Minako, Sunadori Asami, Hayashi Tomoko, Hara Akane, Kawana Yukari, Itoi Youichi, Sugawara Tamie, Sugishita Yoshiyuki, Irie Fujiko, Sakurai Naomi

机构信息

Department of Nursing, Faculty of Sports & Health Science, Daito Bunka University, Higashimatsuyama-shi, Japan.

Graduate School of Health Sciences (Nursing), Ibaraki Prefectural University of Health Sciences, Ami-machi, Japan.

出版信息

JMIR Med Inform. 2025 Jan 10;13:e58509. doi: 10.2196/58509.

Abstract

BACKGROUND

Residents of facilities for older people are vulnerable to COVID-19 outbreaks. Nevertheless, timely recognition of outbreaks at facilities for older people at public health centers has been impossible in Japan since May 8, 2023, when the Japanese government discontinued aggressive countermeasures against COVID-19 because of the waning severity of the dominant Omicron strain. The Facility for Elderly Surveillance System (FESSy) has been developed to improve information collection.

OBJECTIVE

This study examined FESSy experiences and effectiveness in two public health center jurisdictions in Japan.

METHODS

This study assessed the use by public health centers of the detection mode of an automated AI detection system (ie, FESSy AI), as well as manual detection by the public health centers' staff (ie, FESSy staff) and direct reporting by facilities to the public health centers. We considered the following aspects: (1) diagnoses or symptoms, (2) numbers of patients as of their detection date, and (3) ultimate numbers of patients involved in incidents. Subsequently, effectiveness was assessed and compared based on detection modes. The study lasted from June 1, 2023, through January 2024.

RESULTS

In both areas, this study examined 31 facilities at which 87 incidents were detected. FESSy (AI or staff) detected significantly fewer patients than non-FESSy methods, that is, direct reporting to the public health center of the detection date and ultimate number of patients.

CONCLUSIONS

FESSy was superior to direct reporting from facilities for the number of patients as of the detection date and for the ultimate outbreak size.

摘要

背景

老年人设施的居住者易受新冠疫情爆发的影响。然而,自2023年5月8日日本政府因占主导地位的奥密克戎毒株的严重程度减弱而停止对新冠疫情采取积极应对措施以来,日本公共卫生中心一直无法及时识别老年人设施中的疫情爆发情况。已开发出老年人监测系统(FESSy)以改善信息收集。

目的

本研究考察了FESSy在日本两个公共卫生中心辖区的应用经验和效果。

方法

本研究评估了公共卫生中心对自动人工智能检测系统(即FESSy AI)检测模式的使用情况,以及公共卫生中心工作人员的人工检测(即FESSy工作人员)和设施直接向公共卫生中心报告的情况。我们考虑了以下几个方面:(1)诊断或症状,(2)截至检测日期的患者数量,以及(3)事件中涉及的患者最终数量。随后,根据检测模式评估并比较效果。该研究从2023年6月1日持续到2024年1月。

结果

在这两个地区,本研究考察了31个设施,共检测到87起事件。FESSy(人工智能或工作人员)检测到的患者明显少于非FESSy方法,即直接向公共卫生中心报告检测日期和患者最终数量。

结论

就截至检测日期的患者数量和最终疫情规模而言,FESSy优于设施的直接报告。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4923/11741194/4d0dc69be1e2/medinform-v13-e58509-g001.jpg

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