TUFTS MEDICAL CENTER PARENT, INC.
This application addresses broad Challenge Area 04, Clinical Research, and Specific Challenge Topic 04-HL-114, Using existing datasets to plan effectiveness trials in pediatric cardiology. This challenge topic specifically identifies a critical need for the development of novel, computational theoretical models or the adaptation of existing procedures to promote guidelines development and comparative effectiveness research in pediatrics. As an example of the type of work appropriate to this challenge topic, the NHLBI cites the use of decision analysis to assess the role of electrocardiograph screening (ECG) in identifying previously undiagnosed cardiac disorders that cause Sudden Cardiac Death (SCD) among youth with Attention Deficit Hyperactivity Disorder (ADHD) prior to beginning stimulant medications. This application specifically targets this challenge topic and proposes to employ evidence-based synthesis, decision analysis, and preference elicitation to examine the risks and benefits (both clinical and fiscal) of alternative screening and management protocols for youth with ADHD with no known cardiac risks for SCD. Our overarching goal is to use existing data to its best advantage to clarify the comparative effectiveness of three different screening and management approaches: (1) comprehensive screening (i.e., all children receive a history, physical and ECG), (2) targeted screening (i.e., all children receive a history and physical, and ECG screening is reserved for those children with risk factors identified on the history and/or physical), and (3) no screening. Because of the rarity of SCD in the pediatric population and the lack of a national, mandatory system for reporting adverse effects of medications, the evidentiary foundation for current policy statements or guidelines advanced by professional organizations regarding the comparative effectiveness of ECG screening protocols is severely compromised by data gaps that cannot be resolved quickly by traditional analytic approaches. Decision analysis produces mathematical models that account for data limitations and can incorporate fiscal cost estimates as well as estimates of parental and physician preferences. In addition, decision analysis permits quantification of the impact of uncertainty accompanying the available data that may affect estimates of the tradeoffs between different screening and management strategies and delineate areas of particular uncertainty, where targeted data collection and analysis in future research would most affect clinical decision-making. Formative research on physician and parental preferences regarding treatment will also be conducted and incorporated into the decision analysis models. The research team assembled for this application has previously published together on the application of decision analysis to the current controversy regarding the use of ECG screening in children with ADHD and is poised to address this critical research question immediately. Ultimately, study results will identify future areas of research that should be prioritized to further address this challenge area and provide professional organizations with urgently needed information on which to base pediatric practice guidelines.