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This study will test the hypothesis that low-income, disadvantaged patients can provide high-quality patient-generated health data and patient-reported outcomes through commercial technologies, and that these data can be used to improve healthcare quality and delivery.
This project developed a natural language processing electronic health record search tool that automatically identifies and ranks relevant clinical information based on a patient’s presenting complaint within the emergency department setting.
A computer support system for clinical decisionmaking and tailoring patient education called HeartSmartKids™, has been developed to facilitate the translation of recommendations into practice. This current study will employ a comparative-effectiveness trial to evaluate clinician decision support and tailored patient education on the implementation of the current guidelines at school based health clinics.
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 study looked at patients at high risk for cardiovascular disease who would benefit from treatment intensification.