KUAN-KAI HUANG2026-10-162026-10-162021-12-01Pure ID: 43367888Pure UUID: 7ab33bbc-b292-4d08-9ccb-fdd0efddbc75https://www.scopus.com/pages/publications/85124359251https://scholars.csmu.edu.tw/handle/123456789/24039In this study, inpatient falls, accidental tube removal, and examination / inspection / pathology events were selected to ascertain the relationships among the person, event, time, place, and severity from the data. The data samples were taken from 2016, 2017, and 2018 of the Taiwan Patient-Safety Reporting system by excluding the events without harm. The study used the Apriori algorithm to screen the process by setting up the lift of greater than 1, the confidence of 90%, and the support of 10%. The analysis results were classified according to the values of support with more than 30%, 20% to less than 30%, and 10% to less than 20%. The results showed that the incident with the highest support value came from the patient in inspection and the majority of patients were without accompanying persons. The risk factor of the examination events of the medical laboratory was from the patient without accompanying persons. The risk factor of the accidental tube removal events of the nursing department was found to be male patients whose ages were 65 years old or more without accompanying persons along with the negligence of the reporting unit with the severity of one. The risk factor of a fall incident of the nursing department was associated with night shifts. Finally, the risk factor of the severity of two of the examination events was associated with the negligence of other units or the negligence of other units and the patient without accompanying persons.13enA PRELIMINARY STUDY ON THE ASSOCIATION RULES OF MEDICAL INCIDENT REPORT BY USING APRIORI ALGORITHMjournal article