Flory James H, Roy Jason, Gagne Joshua J, Haynes Kevin, Herrinton Lisa, Lu Christine, Patorno Elisabetta, Shoaibi Azadeh, Raebel Marsha A
Weill Cornell Medicine, NY, USA.
University of Pennsylvania, Philadelphia, PA, 9103, USA.
J Comp Eff Res. 2017 Jan;6(1):25-32. doi: 10.2217/cer-2016-0033. Epub 2016 Dec 9.
Laboratory test (lab) results may be useful to detect incident diabetes in electronic health record and claims-based studies.
RESEARCH DESIGN & METHODS: Using the Mini-Sentinel distributed database, we assessed the value of lab results added to diagnosis codes and dispensing claims to identify incident diabetes.
Inclusion of lab results increased the number of diabetes outcomes identified by 21%. In settings where capture of lab results was relatively complete, the absence of lab results was associated with implausibly low rates of the outcome.
Lab results can increase sensitivity of algorithms for detecting diabetes, and missing lab results are associated with much lower rates of diabetes ascertainment regardless of algorithm. Patterns of missing lab results may identify ascertainment bias.
在基于电子健康记录和索赔的研究中，实验室检查（实验室）结果可能有助于检测新发糖尿病。
利用Mini-Sentinel分布式数据库，我们评估了添加到诊断代码和配药索赔中的实验室结果对识别新发糖尿病的价值。
纳入实验室结果使识别出的糖尿病结局数量增加了21%。在实验室结果获取相对完整的情况下，缺乏实验室结果与该结局发生率低得不合理相关。
实验室结果可提高糖尿病检测算法的敏感性，且无论采用何种算法，缺失的实验室结果都与糖尿病确诊率低得多相关。实验室结果缺失模式可能识别出确诊偏倚。
