Development of a Core Clinical Dataset to Characterize Serious Illness, Injuries, and Resource Requirements for Acute Medical Responses to Public Health Emergencies

作者：Murphy David J^*; Rubinson Lewis; Blum James; Isakov Alexander; Bhagwanjee Statish; Cairns Charles B; Cobb J Perren; Sevransky Jonathan E

来源：Critical Care Medicine, 2015, 43(11): 2403-2408.

DOI：10.1097/CCM.0000000000001274

• consensus
• data collection
• disasters
• emergencies
• intensive care units

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.

• 出版日期2015-11