Abstract:Predicting success on a new step in therapy currently relies upon clinical expertise and heuristics. Even after the transition to bolus insulin, many people with diabetes fail to achieve glycemic control. Our objective was to develop a predictive model to classify patients into expected levels of success upon bolus insulin initiation. Machine learning methods were applied to a large nationally representative insurance claims database. Commercially insured adults with T2DM were identified at first observed use … Show more
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