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提高司法管辖区内 COVID-19 综合病例和死亡监测数据传输效率:应用程序编程接口 (API) 的当前和未来作用。

Improving efficiency of COVID-19 aggregate case and death surveillance data transmission for jurisdictions: current and future role of application programming interfaces (APIs).

机构信息

Coronavirus Disease Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

California Department of Public Health, Sacramento, California, USA.

出版信息

J Am Med Inform Assoc. 2022 Sep 12;29(10):1807-1809. doi: 10.1093/jamia/ocac090.

Abstract

During the coronavirus disease-2019 (COVID-19) pandemic, the Centers for Disease Control and Prevention (CDC) supplemented traditional COVID-19 case and death reporting with COVID-19 aggregate case and death surveillance (ACS) to track daily cumulative numbers. Later, as public health jurisdictions (PHJs) revised the historical COVID-19 case and death data due to data reconciliation and updates, CDC devised a manual process to update these records in the ACS dataset for improving the accuracy of COVID-19 case and death data. Automatic data transfer via an application programming interface (API), an intermediary that enables software applications to communicate, reduces the time and effort in transferring data from PHJs to CDC. However, APIs must meet specific content requirements for use by CDC. As of March 2022, CDC has integrated APIs from 3 jurisdictions for COVID-19 ACS. Expanded use of APIs may provide efficiencies for COVID-19 and other emergency response planning efforts as evidenced by this proof-of-concept. In this article, we share the utility of APIs in COVID-19 ACS.

摘要

在 2019 冠状病毒病(COVID-19)大流行期间,疾病控制与预防中心(CDC)补充了传统的 COVID-19 病例和死亡报告,采用 COVID-19 综合病例和死亡监测(ACS)来跟踪每日累计数量。后来,由于公共卫生管辖区(PHJ)对历史 COVID-19 病例和死亡数据进行数据核对和更新,CDC 设计了一个手动流程来更新 ACS 数据集中的这些记录,以提高 COVID-19 病例和死亡数据的准确性。通过应用程序编程接口(API)自动传输数据,这是一种允许软件应用程序进行通信的中间件,可以减少 PHJ 向 CDC 传输数据的时间和工作量。然而,API 必须满足 CDC 使用的特定内容要求。截至 2022 年 3 月,CDC 已经为 COVID-19 ACS 整合了 3 个管辖区的 API。正如这一概念验证所证明的那样,API 的广泛使用可能为 COVID-19 和其他应急规划工作提供效率。本文介绍了 API 在 COVID-19 ACS 中的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/204a/9471715/0106019a13db/ocac090f1.jpg

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