Pediatric in-hospital cardiac arrest most commonly occurs in the pediatric intensive care unit and carries extensive morbidity and mortality. This proposal describes a 5-year research and training program that will allow Dr. Maya Dewan to address the prevention of pediatric cardiac arrest through clinical decision support and implementation science. Having completed fellowship training in pediatric critical care medicine and building on a background of improvement science, epidemiology/biostatistics, and clinical informatics the applicant seeks to develop new knowledge and skills to use design informed clinical decision support and implementation science to improve the care and outcomes for critically ill children. This application seeks to address prevention of pediatric cardiac arrest. Prevention of cardiac arrest events is feasible because children often display warning signs prior to deterioration. The applicant?s preliminary studies demonstrate that prediction of pediatric patients at high-risk for clinical deterioration is feasible.
The specific aims of the proposed investigations are to: 1) To prospectively validate the PICU Warning Tool to predict clinical deterioration, 2) To evaluate the impact on prediction and situational awareness of adding manual high- risk criteria to the automated PICU Warning Tool, 3) To elucidate factors in system design that will improve implementation of the PICU Warning Tool. This work is significant as it focuses on the development and implementation of an effective health information technology intervention to improve health care quality. It leverages the capability of health information technology to improve quality, efficiency, and effectiveness of care for the highest risk pediatric patients. While this training grant focuses on the implementation of health IT in improvement science work, it also addresses the research areas of design, use, and impact on outcomes. Through a Type 1 effectiveness-implementation hybrid design, Dr. Dewan will identify barriers and facilitators to implementation to facilitate a successful translation from an academic research tool to a well implemented clinical decision support tool suitable for routine practice.
Pediatric in-hospital cardiac arrest most commonly occurs in pediatric intensive care units and carries extensive morbidity and mortality making prevention the best approach. Prevention of cardiac arrest events is feasible because children often display warning signs prior to deterioration. This application seeks to address prevention of pediatric in-hospital cardiac arrest through clinical decision support and implementation science.
