Casey Bennett

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RxNorm was utilized as the basis for direct-capture of medication history data in a live EHR system deployed in a large, multi-state outpatient behavioral healthcare provider in the United States serving over 75,000 distinct patients each year across 130 clinical locations. This tool incorporated auto-complete search functionality for medications and proper(More)
—Electronic health records (EHR's) are only a first step in capturing and utilizing health-related data-the problem is turning that data into useful information. Models produced via data mining and predictive analysis profile inherited risks and environmental/behavioral factors associated with patient disorders, which can be utilized to generate predictions(More)
— The CDOI outcome measure – a patient-reported outcome (PRO) instrument utilizing direct client feedback – was implemented in a large, real-world behavioral healthcare setting in order to evaluate previous findings from smaller controlled studies. PROs provide an alternative window into treatment effectiveness based on client perception and facilitate(More)
Research highlights EHRs are increasingly likely to contain data and functionality that can support computational approaches to healthcare. Predictive modeling of EHR data has achieved 70-72% accuracy in predicting individualized treatment response at baseline. Clinical decision support can be conceptualized as a form of artificial intelligence embedded(More)
The effects of culture and context on perceptions of robotic facial expressions. Abstract 2 We report two experimental studies of human perceptions of robotic facial expressions while 3 systematically varying context effects and the cultural background of subjects (n=93). Except for 4 Fear, East Asian and Western subjects were not significantly different in(More)
An empirical investigation of the interaction of sample size and discretization – in this case the entropy-based method CAIM (Class-Attribute Interdependence Maximization) – was undertaken to evaluate the impact and potential bias introduced into data mining performance metrics due to variation in sample size as it impacts the discretization process. Of(More)
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