Risk Stratification Using Physiologic Markers and Mobile Health-Facilitated Specialist Management to Improve Outcomes in Pediatric Concussion Patients

点击翻译按钮获取中文摘要

Candidate: My long-term career goal is to reduce the cognitive, physical, and emotional morbidity following pe- diatric concussion by implementing early interventions to those at highest risk for persistent post-concussion symptoms (PPCS). With 75% of my time dedicated to patient-oriented research and career development, my short-term goals are to develop a predictive model to most accurately identify those patients at highest risk of developing PPCS, and to use a novel mobile health (mHealth) intervention to improve specialist access from the emergency department (ED) setting. This proposal builds on my prior work in researching objective mark- ers of dysfunction following concussion, and will position me to gain skills in advanced predictive modeling to facilitate early risk stratification, utilizing advanced mHealth-based interventions to facilitate care continuity and positioning such interventions for adoption and sustainability, and designing and leading clinical trials from the ED setting that utilize innovative methods to create the evidence base for mHealth intervention adoption. Environment: This proposal leverages the substantial resources available to me at Children’s Hospital of Phila- delphia, through the Division of Emergency Medicine, Center for Injury Research and Prevention, Innovation Ecosystem, and Sports Medicine and Performance Center; at The University of Pennsylvania, through the Center for Clinical Epidemiology and Biostatistics, The Penn Injury Science Center, and the Leonard Davis In- stitute of Health Economics; and through the Pediatric Emergency Care Applied Research Network. The men- tored research experience and formal didactic training, in addition to the clinical experience of practicing in a quaternary care pediatric ED, create an ideal environment for my ongoing career development. Research: Concussions are prevalent injuries in the pediatric population. While the majority of symptoms in concussed youth resolve within 1 month, a significant proportion (30%) experience symptoms lasting months to even years. Several observational studies have identified risk factors associated with PPCS, however the best current methods to risk stratify concussed youth do so with only moderate discrimination, and are heavily reliant on subjective symptoms. In addition, while traditionally, pediatric concussions were managed with pas- sive rest, more recently, active therapies have become the standard of care in the specialty setting. However, the traditional referral model presents several barriers to care continuity and specialist access for ED concus- sion patients. Novel mHealth interventions have the potential to improve care continuity, serving as a bridge between care settings for concussed youth. In order to facilitate improved care and ultimately reduce symptom burden to highest risk children, this proposal aims to: (1) Improve accuracy of concussion risk stratification from the ED using physiologic markers of injury; and (2) Assess the feasibility of a mHealth tool to facilitate specialist access and care continuity. Study results will allow me to develop a R01 proposal of a clinical trial evaluating the effectiveness of mHealth-facilitated targeted referral to reduce the incidence of PPCS.