Development and performance characteristics of novel code-based algorithms to identify invasive Escherichia coli disease

被引:2
作者
Fortin, Stephen P. [1 ]
Pastor, Luis Hernandez [2 ]
Doua, Joachim [2 ]
Sarnecki, Michal [3 ]
Swerdel, Joel [1 ]
Colasurdo, Jamie [4 ]
Geurtsen, Jeroen [5 ]
机构
[1] Janssen Res & Dev, Observat Hlth Data Analyt, 920 US Highway 202, Raritan, NJ 08869 USA
[2] Janssen Res & Dev, Infect Dis & Vaccines, Beerse, Belgium
[3] Branch Cilag GmbH Int, Janssen Vaccines, Bern, Switzerland
[4] Janssen Res & Dev, Epidemiol, Raritan, NJ 08869 USA
[5] Janssen Vaccines & Prevent, Bacterial Vaccines Res & Early Dev, Leiden, Netherlands
关键词
code-based algorithms; electronic health record database; Escherichia coli; performance characteristics; phenotype; sepsis;
D O I
10.1002/pds.5505
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Purpose Evaluation of novel code-based algorithms to identify invasive Escherichia coli disease (IED) among patients in healthcare databases. Methods Inpatient visits with microbiological evidence of invasive bacterial disease were extracted from the Optum (c) electronic health record database between January 1, 2016 and June 30, 2020. Six algorithms, derived from diagnosis and drug exposure codes associated to infectious diseases and Escherichia coli, were developed to identify IED. The performance characteristics of algorithms were assessed using a reference standard derived from microbiology data. Results Among 97 194 eligible records, 25 310 (26.0%) were classified as IED. Algorithm 1 (diagnosis code for infectious invasive disease due to E. coli) had the highest positive predictive value (PPV; 96.0%) and lowest sensitivity (60.4%). Algorithm 2, which additionally included patients with diagnosis codes for infectious invasive disease due to an unspecified organism, had the highest sensitivity (95.5%) and lowest PPV (27.8%). Algorithm 4, which required patients with a diagnosis code for infectious invasive disease due to unspecified organism to have no diagnosis code for non-E. coli infections, achieved the most balanced performance characteristics (PPV, 93.6%; sensitivity, 78.1%; F-1 score, 85.1%). Finally, adding exposure to antibiotics in the treatment of E. coli had limited impact on performance algorithms 5 and 6. Conclusion Algorithm 4, which achieved the most balanced performance characteristics, offers a useful tool to identify patients with IED and assess the burden of IED in healthcare databases.
引用
收藏
页码:983 / 991
页数:9
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