Comparing order entry subsequences related to CPOE correction factors

Computer physician order entry (CPOE) systems play an important role in hospital information systems to com-municate the orders from medical doctors to other medical staffs. However, there are still remaining order corrections and deletions, caused by both of changes of patients´ condition and operational problems between a system and doctors. In this paper, we analyzed factors of medication order corrections for each patient by using order sequences a day. From the whole of the order entry sequences, we extracted characteristic order entry sub-sequences by using an automatic term extraction method in natural language processing. By constructing datasets consisting of the subsequences and the other patients´ information, we obtained if-then rules. Then, we compare their accuracies of the if-then rule sets with/without the characteristic order entry subsequences for analyzing the order correction factors.