Hospital coronavirus disease 2019 (COVID-19) public health reporting: Lessons from validation of an automated surveillance tool to facilitate data collection

被引:1
|
作者
Gamage, Shantini D. [1 ,2 ]
Evans, Martin E. [1 ,3 ,4 ]
McCauley, Brian P. [1 ]
Lipscomb, Karen R. [1 ]
Flarida, Linda [1 ]
Jones, Makoto M. [5 ,6 ]
Baza, Michael [5 ,6 ]
Barraza, Jeremy [5 ,6 ]
Simbartl, Loretta A. [1 ]
Roselle, Gary A. [1 ,2 ,7 ]
机构
[1] US Dept Vet Affairs, Natl Infect Dis Serv, Specialty Care Serv, Vet Hlth Adm, Washington, DC USA
[2] Univ Cincinnati, Dept Internal Med, Div Infect Dis, Coll Med, Cincinnati, OH USA
[3] Lexington Vet Affairs VA Healthcare Syst, Lexington, KY USA
[4] Univ Kentucky, Dept Internal Med, Div Infect Dis, Sch Med, Lexington, KY USA
[5] VA Salt Lake City Healthcare Syst, Salt Lake City, UT USA
[6] Univ Utah, Sch Med, Dept Internal Med, Div Epidemiol, Salt Lake City, UT USA
[7] Cincinnati Vet Affairs Med Ctr, Cincinnati, OH USA
来源
关键词
D O I
10.1017/ice.2022.55
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
A comparison of computer-extracted and facility-reported counts of hospitalized coronavirus disease 2019 (COVID-19) patients for public health reporting at 36 hospitals revealed 42% of days with matching counts between the data sources. Miscategorization of suspect cases was a primary driver of discordance. Clear reporting definitions and data validation facilitate emerging disease surveillance.
引用
收藏
页码:802 / 804
页数:3
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