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This project will redesign approaches for collecting and using allergy information with the goal of improving healthcare quality and safety, including completeness and accuracy of allergy data.
This project will study the impact of errors in medical documents on quality of care and develop innovative natural language processing methods to automatically detect errors so that physicians can correct the documents before finalizing them in the electronic health record.
The research team developed and evaluated a natural language processing allergy module that was used to study different types of allergies in an electronic health record.
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.
This study investigated the feasibility of extracting medication information from non-structured electronic clinical sources within an electronic health record.
This project documented, studied, and reported the engagement of six primary care practices that use electronic health records that were linked to the Secure Medical Records Transfer Network through a local data repository.
The project developed and evaluated an Internet-based patient Wellness Portal linked to Preventative Services Reminder System to facilitate patient-centered, preventive care in primary care practices.
Disseminated strategies targeted toward increasing immunizations and preventive care, including a computer reminder system to practices in a Practice-based Research Network (PBRN). Assessesed, using a randomized controlled trial methodology, the relative adoption success of academic detailing combined with and without practice facilitation and technology implementation assistance, on the delivery of preventive services.