Patient adverse drug reaction warning method and system based on Naive Bayes

Abstract

The invention provides a patient adverse drug reaction warning method and system based on Naive Bayes. The method and system is characterized in that probability calculation is performed by specific algorithms according to existing information systems in hospitals, existing data in the systems, such as patient's basic information, clinical diagnosis, medication conditions, pathological signs and examination and inspection conditions, drug clinical test data and adverse drug reaction case report data; the time of probable high-probability adverse reactions is warned. The method and system can assist clinicians and pharmacists in medication safety analysis and medication scheme adjustment, so that the level of medical services is increased.

Description

technical field [0001] The invention relates to a naive Bayesian-based early warning method and system for adverse drug reactions of patients. Background technique [0002] Adverse Drug Reaction (ADR) refers to the unrelated or unexpected adverse reactions of qualified drugs under normal usage and dosage. The main body of the diagnosis and evaluation of adverse drug events is generally clinicians, but clinical pharmacists alone The diagnosis and evaluation of suspected adverse drug events requires high knowledge structure and clinical practice experience of clinical pharmacists, and mainly relies on the knowledge and experience of judges, so human factors interfere greatly. However, the current information system of medical institutions already contains a large amount of patient medication diagnosis and treatment data. Making full use of the information system data to do some statistical analysis can help clinicians and pharmacists to carry out medication reminders and safet...

AI Technical Summary

Problems solved by technology

[0002] Adverse Drug Reaction (ADR) refers to the unrelated or unexpected adverse reactions of qualified drugs under normal usage and dosage. The main body of the diagnosis and evaluation of adverse drug events is generally clinicians, but clinical pharmacists alone The diagnosis and evaluation of suspected adverse drug events requires high knowledge structure and clinical practice experience of clinical pharmacists, and mainly relies on the knowledge and experience of judges, so human factors interfere greatly

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