Supplementing claims data analysis using self-reported data to develop a probabilistic phenotype model for current smoking status

Journal of Biomedical Informatics
Jenna M RepsPatrick B Ryan

Abstract

Smoking status is poorly record in US claims data. IBM MarketScan Commercial is a claims database that can be linked to an additional health risk assessment with self-reported smoking status for a subset of 1,966,174 patients. We investigate whether this subset could be used to learn a smoking status phenotype model generalizable to all US claims data that calculates the probability of being a current smoker. 251,643 (12.8%) had self-reported their smoking status as 'current smoker'. A regularized logistic regression model, the Current Risk of Smoking Status (CROSS), was trained using the subset of patients with self-reported smoking status. CROSS considered 53,027 candidate covariates including demographics and conditions/drugs/measurements/procedures/observations recorded in the prior 365 days, The CROSS phenotype model was validated across multiple other claims data. The internal validation showed the CROSS model achieved an area under the receiver operating characteristic curve (AUC) of 0.76 and the calibration plots indicated it was well calibrated. The external validation across three US claims databases obtained AUCs ranging between 0.82 and 0.87 showing the model appears to be transportable across Claims data. CROSS pre...Continue Reading

Citations

Apr 27, 2020·Journal of Biomedical Informatics·Chunhua WengGeorge Hripcsak
Aug 29, 2021·Tobacco Control·Rui FuMichael Oliver Chaiton
Oct 7, 2021·Pharmacoepidemiology and Drug Safety·Sitwat AliRachel E Neale

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