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.

Andrea Chambers, Mark A Cachia, Jessica P Hopkins
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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.

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通过对行政账单数据进行回顾性分析,了解安大略省 COVID-19 病例高风险密切接触者的语言概况,从中汲取机遇和教训。
背景:在公共卫生突发事件期间,获得能够识别受影响严重的社区的数据源并确保公共卫生传播满足不同人群的需求至关重要:探讨如何将语言翻译服务的行政收费数据作为额外的信息来源,以了解 COVID-19 病例高危密切接触者的语言概况:利用安大略省公共卫生局的 "接触追踪计划"(Contact Tracing Initiative)从 2020 年 5 月到 2022 年 2 月的行政收费数据进行了回顾性描述分析。利用 "联系追踪计划 "的数据来确定可能影响语言翻译请求模式的驱动因素。利用 2021 年加拿大人口普查数据将这一趋势与社区语言概况进行了比较:口译员在 38,518 分钟的口译时间内回应了 2,604 次请求,提供了 50 种不同语言的信息。请求最多的五种语言是法语、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地位的不同时期,包括 2020 年春/夏的西班牙语、2020 年夏/秋的法语和 2021 年春的阿拉伯语。总体而言,这些趋势与提交呈件最多的医疗单位的语言概况相吻合:公共卫生机构可以利用现有的二手数据来源来了解其社区的语言口译需求。本研究还展示了如何利用现有数据源来帮助评估各社区如何受到公共卫生突发事件的严重影响,以及这种情况可能随着时间的推移而发生的变化。
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