This research will assess the validity of patient-level computable social factor phenotypes used to predict a patient’s risk of increased healthcare utilization and costs.
This research will compare the use of predictive modeling versus traditional questionnaires to identify those with unmet social needs, use the superior method to inform the development of a clinical decision support tool, and evaluate the tool’s impact on referrals to social providers.
This is a questionnaire designed to be completed by clinical and office staff in a pediatric setting. The tool includes questions to assess staff attitudes and assessment of a clinical decision support tool.
The research team will implement and evaluate an integration application that incorporates relevant health information exchange data directly into the electronic health record in the emergency department.
This research implemented and evaluated strategies to improve patient matching of health data from disparate sources improving accuracy of matching.
This research assessed the use of a health information exchange system in emergency department settings, finding that although overall usage is relatively low, additional functionalities such as single sign on add value to clinical decision making and enable faster retrieval of patient records from external sources compared to traditional methods when embedded into existing workflows.
This research team designed and tested an application called Power to the People to assist older patients to self-manage their chronic heart failure.
This research demonstrated primary care providers’ complementary use of “push” and “pull” health information exchange technologies to meet their information needs and provides evidence that “pull” exchange reduces potentially avoidable healthcare utilization.
This project integrated a validated anxiety-specific screening tool in an existing clinical decision support system and tested it with a randomized feasibility pilot that found the tool did not increase detection of anxiety in pediatric primary care.
In this study, researchers created new electronic health record-based decision support tools that guide clinicians’ perceptions and judgments of noncancer pain in ways that lead to increased use of guideline-based patient assessment and treatment of pain.
