Data on the number of in-hospital patient with central catheterization, which is defined using P4P (Hospital Quality Performance Measurement Index) and QIP (Quality Improvement Program) indicators, were extracted from the nursing records of E-Da Hospital for the period from January 2015 to the present. The main study purposes were to construct a data mining model, ensure the accuracy and stability of data sources, and implement improving human factors affecting indicator monitoring in the interest of consolidating the functions of indicator management to maintain healthcare quality and patient safety. Therefore, we uses five steps to increase the accuracy of the data collected on in-hospital patients with central catheterization. The five steps were as follows: 1. Confirm the definitions and standards applied to the indicators; 2. standardize the data collection method for the studied patients; 3. apply a foolproof mechanism to avoid repeating calculations; 4. provide subquery reports of central catheters to each station; and 5. perform real-time automatic data collection and validation. Mining data directly from nursing records is time efficient, allows for real-time physical evaluations, and simplifies the sampling process; furthermore, the use of IT-based indicators reduces the amount of missing data and the use of paper documents, thereby reducing emissions and creating more space. Through this study, we discovered that we should promote our automation system to all units and utilize graphic tools so it can be used to perform daily monitoring at all units and intelligently improve healthcare quality.
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