Search found 13 items
This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.
This research evaluated the usability and usefulness of medication therapy management (MTM) alerts and made recommendations for improving MTM platform design.
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.
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.
This project expanded and modified the Child Health Improvement through Computer Automation (CHICA) system to assist pediatricians in identifying and managing four common medical-legal problems that may adversely impact child health, and found initial findings to be inconclusive.
This project implemented clinical decision support and clinical messaging to improve clinician reporting of notifiable conditions to public health agencies.
The project sought to determine if a computer decision support system integrated with routine care could improve standardized developmental screening during early well-child visits and surveillance for developmental disabilities at all pediatric visits.
The goal of this project was to design, develop, and evaluate a method of providing medication data from the Indiana Network for Patient Care to ambulatory primary care practices in order to enhance health care quality
This project analyzed a clinical decision support tool for colorectal cancer screening that was integrated into an ambulatory clinical workflow.
This project evaluated the Pharmaceutical Safety Tracking (PhaST) system, which monitors medication safety in children and adolescents who are taking antidepressants.