Cluster/chronic disease early-stage automatic alarm, preliminary feature analysis and risk assessment system

Abstract

The invention discloses an early-stage automatic alarming, preliminary feature analysis and risk assessment system for clustered / chronic diseases in the field of public health. The early-stage automatic alarming, preliminary feature analysis and risk assessment system comprises a case information collection module, an activity track tracking module, an automatic alarming display module and a riskanalysis and evaluation module. Through regular scanning of a medical institution medical record database and automatic analysis of individual movement tracks of patients, automatic alarm of emergingclustered diseases can be realized, summarization and preliminary risk analysis and evaluation of the same cases in unit time can be realized, and through distribution characteristic analysis of the cases in unit time, the medical institution medical record database can be automatically monitored. And the formulation of chronic disease difference prevention and control measures in the region is guided.

Description

technical field [0001] The invention relates to the field of public health, in particular to early automatic alarm, preliminary feature analysis and risk assessment of cluster / chronic diseases. Background technique [0002] Sudden mass outbreaks of infectious diseases, such as Severe Acute Respiratory Syndrome (SARS), Influenza A HIN1, and New Coronary Pneumonia (COVID-19), pose a great threat to human life safety and social and economic stability Some chronic diseases, such as hypertension, rheumatoid arthritis, and trace element deficiency, are closely related to the geographical distribution and eating habits of patients. my country spends a lot of manpower and material resources on the prevention and treatment of cluster diseases and chronic diseases every year . In clinical practice, we found that traditional infectious disease surveillance relies heavily on the sensitivity and alertness of medical staff to these diseases, and it can only focus on infectious diseases tha...

AI Technical Summary

Problems solved by technology

In the existing technology, there is a lack of monitoring application systems for clustered case events that can be automatically identified, and it is difficult to detect clusters of suspicious patients in time, which is conducive to early response measures, and therefore it is also difficult to minimize the impact of such diseases on society

Images