David J Murphy1, Lewis Rubinson, James Blum, Alexander Isakov, Statish Bhagwanjee, Charles B Cairns, J Perren Cobb, Jonathan E Sevransky. 1. 1Division of Pulmonary, Allergy, Sleep, and Critical Care Medicine, Department of Medicine, Emory University, Atlanta, GA. 2Division of Trauma Critical Care, R. Adams Cowley Shock Trauma Center, School of Medicine, University of Maryland, Baltimore, MD. 3Department of Anesthesiology, Emory University, Atlanta, GA. 4Department of Emergency Medicine, Emory University, Atlanta, GA. 5Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA. 6Department of Emergency Medicine, College of Medicine, University of Arizona, Tucson, AZ. 7Department of Anesthesiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA. 8Department of Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA.
Abstract
OBJECTIVES: In developed countries, public health systems have become adept at rapidly identifying the etiology and impact of public health emergencies. However, within the time course of clinical responses, shortfalls in readily analyzable patient-level data limit capabilities to understand clinical course, predict outcomes, ensure resource availability, and evaluate the effectiveness of diagnostic and therapeutic strategies for seriously ill and injured patients. To be useful in the timeline of a public health emergency, multi-institutional clinical investigation systems must be in place to rapidly collect, analyze, and disseminate detailed clinical information regarding patients across prehospital, emergency department, and acute care hospital settings, including ICUs. As an initial step to near real-time clinical learning during public health emergencies, we sought to develop an "all-hazards" core dataset to characterize serious illness and injuries and the resource requirements for acute medical response across the care continuum. SUBJECTS: A multidisciplinary panel of clinicians, public health professionals, and researchers with expertise in public health emergencies. DESIGN: Group consensus process. INTERVENTIONS: The consensus process included regularly scheduled conference calls, electronic communications, and an in-person meeting to generate candidate variables. Candidate variables were then reviewed by the group to meet the competing criteria of utility and feasibility resulting in the core dataset. MEASUREMENTS AND MAIN RESULTS: The 40-member panel generated 215 candidate variables for potential dataset inclusion. The final dataset includes 140 patient-level variables in the domains of demographics and anthropometrics (7), prehospital (11), emergency department (13), diagnosis (8), severity of illness (54), medications and interventions (38), and outcomes (9). CONCLUSIONS: The resulting all-hazard core dataset for seriously ill and injured persons provides a foundation to facilitate rapid collection, analyses, and dissemination of information necessary for clinicians, public health officials, and policymakers to optimize public health emergency response. Further work is needed to validate the effectiveness of the dataset in a variety of emergency settings.
OBJECTIVES: In developed countries, public health systems have become adept at rapidly identifying the etiology and impact of public health emergencies. However, within the time course of clinical responses, shortfalls in readily analyzable patient-level data limit capabilities to understand clinical course, predict outcomes, ensure resource availability, and evaluate the effectiveness of diagnostic and therapeutic strategies for seriously ill and injured patients. To be useful in the timeline of a public health emergency, multi-institutional clinical investigation systems must be in place to rapidly collect, analyze, and disseminate detailed clinical information regarding patients across prehospital, emergency department, and acute care hospital settings, including ICUs. As an initial step to near real-time clinical learning during public health emergencies, we sought to develop an "all-hazards" core dataset to characterize serious illness and injuries and the resource requirements for acute medical response across the care continuum. SUBJECTS: A multidisciplinary panel of clinicians, public health professionals, and researchers with expertise in public health emergencies. DESIGN: Group consensus process. INTERVENTIONS: The consensus process included regularly scheduled conference calls, electronic communications, and an in-person meeting to generate candidate variables. Candidate variables were then reviewed by the group to meet the competing criteria of utility and feasibility resulting in the core dataset. MEASUREMENTS AND MAIN RESULTS: The 40-member panel generated 215 candidate variables for potential dataset inclusion. The final dataset includes 140 patient-level variables in the domains of demographics and anthropometrics (7), prehospital (11), emergency department (13), diagnosis (8), severity of illness (54), medications and interventions (38), and outcomes (9). CONCLUSIONS: The resulting all-hazard core dataset for seriously ill and injured persons provides a foundation to facilitate rapid collection, analyses, and dissemination of information necessary for clinicians, public health officials, and policymakers to optimize public health emergency response. Further work is needed to validate the effectiveness of the dataset in a variety of emergency settings.
Authors: Taylor Read; Elizabeth White; J Perren Cobb; Perry Mar; Mahesh Shanmugam; Roberto A Rocha; Sarah Collins Rossetti Journal: Online J Public Health Inform Date: 2019-09-19
Authors: Christianne Joy Lane; Manas Bhatnagar; Karen Lutrick; Ryan C Maves; Debra Weiner; Daisy Rios Olvera; Timothy M Uyeki; J Perren Cobb; Joan C Brown Journal: Crit Care Explor Date: 2022-01-05
Authors: Joan Brown; Manas Bhatnagar; Hugh Gordon; Karen Lutrick; Jared Goodner; James Blum; Raquel Bartz; Daniel Uslan; Ernesto David-DiMarino; Alfred Sorbello; Gregory Jackson; Jeremy Walsh; Lauren Neal; Marek Cyran; Henry Francis; J Perren Cobb Journal: Biomed Instrum Technol Date: 2021-07-01