Abstract
Cost data may be missing from administrative claims data for several reasons, and multiple methods of cost imputation have been used over time. Machine learning techniques are being utilized with greater regularity across all of healthcare, and their use in cost imputation may allow for broader utility of previously incomplete data. To that end, we developed and compared several machine learning algorithms to impute missing pharmacy claims costs in a large US commercially insured population.
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