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Can I read Body Mass Index Variable Interpolation to Expand the Utility of Real-world Administrative Healthcare Claims Database Analyses on EtoBox?
Body Mass Index Variable Interpolation to Expand the Utility of Real-world Administrative Healthcare Claims Database Analyses by Bingcao Wu; Wing Chow; Monish Sakthivel; Onkar Kakade; Kartikeya Gupta; Debra Israel; Yen-Wen Chen; Aarti Susan Kuruvilla is a Medicine article available to read on EtoBox.
What is Body Mass Index Variable Interpolation to Expand the Utility of Real-world Administrative Healthcare Claims Database Analyses about?
## Introduction Administrative claims data provide an important source for real-world evidence (RWE) generation, but incomplete reporting, such as for body mass index (BMI), limits the sample sizes that can be analyzed to address certain research questions. The objective of this study was to construct models by implementing machine-learning (ML) algorithms to predict BMI classifications (≥ 30, ≥ 35, and ≥ 40 kg/m^2^) in administrative healthcare claims databases, and then internally and externally validate them. ## Methods Five advanced ML algorithms were implemented for each BMI classification on a random sampling of BMI readings from the Optum PanTher Electronic Health Record database (2%) and the Optum Clinformatics Date of Death (20%) database, while incorporating baseline demographic and clinical characteristics. Sensitivity analyses with oversampling ratios were conducted. Model performance was validated internally and externally. ## Results Models trained on the Super Learner ML algorithm (SLA) yielded the best BMI classification predictive performance. SLA model 1 utilized sociodemographic and clinical characteristics, including baseline BMI values; the area under the recei
Who reads Body Mass Index Variable Interpolation to Expand the Utility of Real-world Administrative Healthcare Claims Database Analyses?
It is typically read by researchers, students, and practitioners in Medicine.
- Author
- Bingcao Wu; Wing Chow; Monish Sakthivel; Onkar Kakade; Kartikeya Gupta; Debra Israel; Yen-Wen Chen; Aarti Susan Kuruvilla
- Publisher
- Springer Science and Business Media LLC
- Published
- 2021
- Language
- EN
- Field
- Medicine (Health Sciences)