Creating Novel Interventions to Improve Prognostication for Patients with Hypoxic-Ischemic Brain Injury - Abstract Sudden cardiac arrest is a leading cause of global death and disability. Most patients who are resuscitated from cardiac arrest are initially comatose. These patients undergo neurological prognostication to estimate recovery potential and death after withdrawal of life-sustaining therapies (WLST) based on clinicians’ predictions of a poor prognosis for awakening and recovery is common. Accurate prognostication allows clinicians and surrogates to make informed decisions about WLST. Unfortunately, falsely pessimistic predictions are common and lead to preventable deaths. Conversely, falsely predicting recovery potential can result in prolonged, costly care and survival with unacceptable quality of life. Thus, preventing inaccurate prognostication is critical to improve patient outcomes. Current approaches for neurological prognostication after cardiac arrest are inadequate and in practice, clinicians perform poorly. Novel methods to improve prognostication are urgently needed. The overall scientific objective of this career development award is to use principles of decision science and organizational behavior to fill key knowledge gaps needed to create, refine, and test targeted, rigorously designed interventions to improve prognostication, such as a team-based approach. The career development objectives will allow the applicant to refine her expertise in decision sciences, organization behavior, innovative clinical trial design, and social determinants of decision-making. In doing so, this award will support a career of sustained high-impact science. The project leverages the strength of an outstanding mentorship team with world experts in medical anthropology, decision, team, and resuscitation sciences, a rich environment, and the applicant’s prior experience and academic successes. Aim 1 will use rigorous mixed methods (concept mapping) to identify key metrics of prognostication quality by engaging a diverse community of stakeholders of cardiac arrest (physicians, non-physician clinicians, survivors, co-survivors, and surrogates of decedents) and domain experts in ethics, legal/policy, and religion/spiritualism. Aim 2 will identify clinical situations where experts disagree about prognosis because in these challenging cases novel strategies are most urgently needed. Aim 3 will use a decision science approach (signal detection theory) to compare prognostication by individual experts and teams of varying compositions, providing preliminary data supporting the efficacy of a team-based approach and identifying which team composition characteristics need to be optimized to maximize efficacy. Taken together, this award will advance the applicant’s goal of becoming an independent clinician-investigator who transforms outcomes of patients with severe acute brain injury by creating and testing high-impact interventions that improve prognostication quality.
