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通过对行政计费数据进行回顾性分析,了解安大略省新冠病毒病病例高风险密切接触者的语言概况所获得的机遇与经验教训。

Opportunities and lessons learned from a retrospective analysis of administrative billing data to understand the language profile of high-risk close contacts of COVID-19 cases in Ontario.

作者信息

Chambers Andrea, Cachia Mark A, Hopkins Jessica P

机构信息

Public Health Ontario, Toronto, ON.

Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON.

出版信息

Can Commun Dis Rep. 2024 Oct 3;50(10):375-380. doi: 10.14745/ccdr.v50i10a06. eCollection 2024 Oct.

Abstract

BACKGROUND

During a public health emergency, it is vital to have access to data sources that can identify communities disproportionately affected and to ensure public health communications are meeting the needs of diverse populations.

OBJECTIVE

To explore how administrative billing data for language interpretation services could be used as an additional source of information to understand the language profile of high-risk close contacts of COVID-19 cases.

METHODS

A retrospective descriptive analysis was conducted using administrative billing data from Public Health Ontario's Contact Tracing Initiative from May 2020 to February 2022. Data from the Contact Tracing Initiative were utilized to identify drivers that could have influenced patterns in language interpretation requests. Trends were compared with community language profiles using 2021 Canadian Census data.

RESULTS

Interpreters responded to 2,604 requests across 38,518 interpretation minutes and provided information in 50 different languages. The top five requested languages were French, Arabic, Spanish, Punjabi and Mandarin. Five distinct periods were identified of different language predominance including Spanish in spring/summer 2020, French in summer/fall 2020 and Arabic in spring 2021. Overall, these trends aligned with the language profile of health units contributing most submissions.

CONCLUSION

Public health agencies could benefit from using existing secondary data sources to understand the language interpretation needs of their communities. This study also demonstrated how existing data sources could be used to help assess how communities are being disproportionately affected by public health emergencies and how this might change over time.

摘要

背景

在突发公共卫生事件期间,获取能够识别受影响尤为严重的社区的数据源,并确保公共卫生通信满足不同人群的需求至关重要。

目的

探讨如何将语言口译服务的行政计费数据用作额外的信息来源,以了解新冠病毒病例高风险密切接触者的语言概况。

方法

利用安大略省公共卫生部门2020年5月至2022年2月接触者追踪倡议的行政计费数据进行回顾性描述分析。利用接触者追踪倡议的数据来确定可能影响语言口译请求模式的驱动因素。使用2021年加拿大人口普查数据将趋势与社区语言概况进行比较。

结果

口译员回应了2604次请求,累计口译时长38518分钟,并提供了50种不同语言的信息。需求排名前五的语言是法语、阿拉伯语、西班牙语、旁遮普语和普通话。确定了五个不同语言占主导的时期,包括2020年春夏季的西班牙语、2020年夏秋季的法语以及2021年春季的阿拉伯语。总体而言,这些趋势与提交数据最多的卫生单位的语言概况一致。

结论

公共卫生机构可以从利用现有的二手数据源来了解其社区的语言口译需求中受益。本研究还展示了如何利用现有数据源来帮助评估社区如何受到突发公共卫生事件的不成比例影响,以及这种影响可能如何随时间变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da94/11464010/5984b24fda07/501006-f1.jpg

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