Time Sequence Analysis of EMS Database
Date Issued
2015
Date
2015
Author(s)
Huang, Yung-Wen
Abstract
Emergency Medical Services (EMS) provide medical cares to seriously injured or illed patients, while they are being transported from the incident sites to the hospitals. Out-of-hospital acute medical interventions aims not only to reduce the mortality rate and the degree of disability of patients but also to minimize patients’ rehabilitation and medical costs. One critical issue in providing effective EMS is the quantities of resources to be allocated. It is conceivable that some types of EMS incidents should have periodical patterns and the public health agents should allocate the EMS resources accordingly. For example, drowning and hyperthermia incidents should peak during summer seasons, while stoke incidents should peak during winter seasons. The primary objective of the study presented in this thesis is to conduct comprehensive time series analyses based on the records in an EMS database in order to identify significant periodical patterns of EMS incidents. In this study, a novel analysis method designed to provide the user with a highly interpretable picture of the periodical patterns in the input time series has been employed. The analyses were then followed by carrying out the conventional statistical tests to provide the user with solid statistical metrics. The results derived from this study reveal that periodical patterns are commonly present in many types of EMS incidents.
Subjects
Time series analysis
Emergence medical services
Medical database
Periodical patterns
SDGs
Type
thesis
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