Provider (PCP) program. They were randomized into either a UAV group or a non UAV group. The study scenario was based on a highway accident involving ten vehicles with seven hazards. Each group was given a 60 minute lecture on UAV technology, and a 30 minute lecture on hazards. Each subject entered the scene after receiving a brief narrative. Having been informed that there were 7 hazards to be identified, the UAV group remained at the UAV ground station while the non UAV group was able to approach the scene. After identifying all hazards, the time to identification and order was recorded. Primary outcome measures were the difference in time to identification, and difference in identification order. Results: The mean time (SD, range) to identify the hazards were 3'68" (1.62, 1'48"-6'48") and 2'43" (0.92, 1'43"-4'38") in UAV and non UAV groups respectively, corresponding to a mean difference of 58" (P = 0.11). A non parametric permutation test showed a significant (P = 0.04) difference in the hazard identification order driven by two hazards, fuel and workplace hazardous material information system placard. Conclusion: This study demonstrated that there is a statistical difference in the identification order of hazards. Interestingly, preliminary results were unable to identify a difference in time to hazard identification. Study/Objective: The study objective is to make the basis of a chemical emergency medical information system. Background: There are many database sets and websites which provide chemical databases in chemical accidents, but they don't have adequate roles for emergency medical support in Korea. Methods: We reviewed the database sets and websites, which provide chemical database and emergency medical records in prehospital transport to hospitals. After an analysis was done, an adequate database set was proposed, and the algorithm for elicitation of chemicals suitable for emergency medical support, accident cases. Results: By four steps of elicitation of chemicals, the number of chemicals of more than 100,000 was decreased to less than 1,000. The standard steps were accident preparedness, toxicity, and circulating amounts. We made an algorithm for the elici-tation of chemicals. Conclusion: When mass exposure by toxic chemical occurs, chemical emergency medical information systems will be helpful for acute identification of chemical and emergency medical response. Study/Objective: To determine the nationwide current status of hospital awareness in emergency and disaster preparedness. Background: Hospital awareness and preparedness is the cornerstone for community health management in emergency and disaster as it plays a critical role in taking care of injured patients. To assess the current system is the first necessary step to improve hospital readiness for emergency and disaster. Methods: A questionnaire was distributed to every provincial, general, and university hospital in Thailand. The data were extracted and reported as number and percentage. Single logistic regression analysis was used to ...