Data mining in accurate calculation of the average length of stay in intensive care units

VernacularTitle:应用数据挖掘精确计算重症医学科平均住院日初探
Author: Caiyun TANG ¹
Author Information

1. 番禺区中心医院信息科信息统计中心
Keywords: Intensive care units; Inter-department transfer; Data mining; Length of stay
From: Chinese Journal of Hospital Administration 2018;34(12):1031-1033
CountryChina
Language:Chinese
Abstract: Objective To accurately calculate average length of stay in intensive care unit ( ICU) discipline in an objective and reasonable way. Methods Application of data mining language was used to extract all inpatient data during their hospital stay for accurate calculation of the average length of stay. Paired test analysis was used to calculate the difference between traditional average length of stay and the new one. Results The average length of ICU stay in 2017 was 6. 66 days, 5. 37 days shorter than 12. 03 days of the average length of stay, with the difference between the average length of stay and that in the ICUs being significant ( t= -13. 614, P<0. 05). Conclusions The average length of ICU stay can objectively reflect the actual working efficiency of the ICUs, especially fitting intensive care units of frequent patient admissions and discharges.