APPLICATION OF BIG DATA MANEGEMENT TO MONITOR BACTERIA SPREAD IN HOSPITAL

Tan Duc Ha1, , Thi Dieu Truong1, Thi Dieu Hien Nguyen1, Quang Minh Le1, Minh Vu Nguyen1, Minh Nghiem Nguyen1, Thanh Phong Pham1, Hoang Phuc Le1, Van Khoa Nguyen1, Ngoc Hoang My Nguyen1
1 Can Tho Central General Hospital

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Abstract

Background: Managing and minimizing the spread of bacteria in hospitals can reduce mortality risk, length of hospital stays and treatment costs. Objectives: To use data from the hospital inpatient management system. Materials and methods: To summarize trends and frequencies of new bacterial strains in the hospital. Results: The frequency of infections was presented for the entire hospital, for treatment departments, for bacterial phenotypes. Additionally, software was developed to model the predicted weekly incidence based on factors: the treatment department, average number of patients per week, cumulative treatment days per week and cumulative mechanical ventilation days per week. The correlation coefficient between the predicted incidence from the model and the observed incidence from the data was 0.698 (p < 0.0001, Pearson correlation). Conclusion: Data from the hospital inpatient management system can be utilized to develop software for effective management of bacterial incidence rates and transmission trends.

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References

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