This study investigated the feasibility of extracting medication information from non-structured electronic clinical sources within an electronic health record.
This project developed nine obesity care quality measures and developed and validated the use of an automated method using natural language processing to utilize the measures.
This project designed and validated a new diabetes quality of care process measure.
This study was designed to reduce guideline ambiguities, improve efficiency, and create and evaluate tools to facilitate the writing of comprehensive and implementable guidelines.
This project refined a set of asthma care quality measures and developed and validated the use of an automated method using natural language processing to utilize the measures.
The overall goal of this study was to develop and assess a natural language processing application to facilitate medication reconciliation at the point of care.
The project team successfully developed and implemented an automated system for measuring the rate of adverse drug events in pediatric patients.
