Before-hospital first-aid method based on chest pain map

Abstract

The invention discloses a before-hospital first-aid method based on chest pain maps. The method can realize intelligent optimization of before-hospital first-aid and first-aid scheduling according tothe time space state map of a chest pain patient, wherein the chest pain maps mainly comprise four kinds of chest pain maps of body, knowledge, hospital and resource. The body chest pain map gathers information of body examination, medical record, daily chief complaint and the like of the patient. The information is transmitted to the knowledge chest pain map for per-determining a disease reason,risk reasoning and classification. A first-aid transportation target position of the high-risk chest pain patient is determined according to position information and clinic receiving capability presented in the hospital chest pain map. The resource chest pain map supplies position information of first-aid resources such as defibrillator, household doctor and first-aid medicaments in a field period, and supplies the position information of first-aid resources such as ambulance and hospital chest pain center in a transportation period. According to the before-hospital first-aid method, the fourkinds of chest pain maps of body, knowledge, hospital and resource are integrated for application, thereby facilitating guiding of optimized configuration of the first-aid resources, and supplying a scheduling plan with highest survival probability to the chest pain patient.

Description

technical field [0001] The invention relates to a pre-hospital first aid method based on a chest pain map, in particular to a method capable of performing early warning and resource optimization scheduling based on monitoring information of chest pain patients. Background technique [0002] According to the survey, there are 1.8 million people in my country every year, 3-4 people die of sudden death every minute, 92% of patients have symptomatic chest pain before sudden death, and 80% die outside the hospital. Compared with the rescue success rate of 8% in developed countries, the rescue success rate of sudden death in my country is only 0.6‰, which is less than one in a thousand. The probability of chest pain in the normal population is as high as 15.5%, and high-risk fatal chest pain such as myocardial infarction is only 1.2%. When the initial chest pain occurs, it is impossible to identify whether it is high-risk fatal chest pain. It is not until the emergency and severe ...

AI Technical Summary

Problems solved by technology

[0003] After the occurrence of high-risk chest pain such as myocardial infarction, the survival rate of patients will decrease by 2% every time the treatment is delayed for 1 hour. A 7-10% drop, this battle against the god of death urgently needs a combat map: Who are the high-risk groups within the coverage of first aid? Where is the nearest first responder after a chest pain? Where is the nearest first aid equipment? Where is the nearest chest pain center? At present, the optimization method of chest pain first aid is mainly concentrated after the patient is admitted to the hospital, but the information means before admission is lacking, and the information system of each node is limited by the spatial distribution and data format, so it cannot realize real-time sharing, and it is difficult to provide information services for timely diagnosis and treatment. It is difficult to provide real-time panoramic monitoring and dynamic decision support services for emergency management

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