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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 will evaluate and compare different tools within electronic health records to assist pediatric primary care clinicians with providing higher quality childhood obesity care to help slow weight gain in children with obesity.
The research team designed and developed “Invention INC,” an interactive nutrition comic for dietary self-management, focused on reducing childhood obesity risk in urban minority youth.
This project applied a user-centered design process to understand the needs and attitudes for sharing patient-collected lifelog data with providers to improve management and decision making.
This study will compare the use of personalized HPV vaccine text message reminders to conventional text message reminders among minority adolescents in a randomized trial.
This project implemented an electronic health record-based weight loss maintenance intervention and found medium-term success for patients assigned to the intervention.
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.
The goal of this study was to develop and evaluate electronic health record-based tools to improve diagnosis and treatment of overweight and obesity in primary care.
This project built and evaluated an interactive social media Web site devoted to vaccines with a blog, discussion forum, chat room, and an anonymous portal through which parents were able to ask questions.
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.