Predictors of Home Care Oral Medication Management (original) (raw)

Abstract

Aims: The aims of this study were to identify risk factors and clinician interventions from electronic health record data that predict improvement in oral medication management for home health care patients. Methods: This study is a retrospective cohort design analyzing OASIS assessment data, Omaha System interventions, and medications from electronic health records in 15 home health care agencies. Models were created to discover predictors for improvement in oral medication management using data mining techniques of discriminative pattern analysis and classification rules. Results: The 1,688 cases represented predominately older Caucasian adults with two-thirds females who frequently were admitted from the hospital. Oral medication management improved in 268 (16.1%) cases by discharge. Discriminative pattern analysis resulted in two rules involving four variables that accounted for 90% of all cases for improvement or no improvement. Classification rules correctly classified patient...

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