The Development of the “Monitoring Application for Inappropriate Expressions in Nursing Records”for PsyNACS©

Lengthening periods of hospitalization, increasing numbers of patients with age-related complications, and a shortage of nursing staff have been of great concern in medical psychiatry in Japan. Under these circumstances, countries such as Japan that face a super-aging society and a decline in the working-age population, have been recommended for use of advanced information and communications technology (ICT) to improve the efficiency of medical treatment and care. This study aims to develop the “Monitoring Application for Inappropriate Expressions in Nursing Records” for using PsyNACS©, which will enable psychiatric nursing plans to harness the advantages of ICT. The functions considered necessary are as follows: 1) identification of users who enter information;2) a necessary database for lists of inappropriate expressions;3) development of a matching function to recommend proper writing input and a warning function;and 4) a management function for an inappropriate expression list database. A demonstration experiment for developing the application in this study was conducted at a specialized psychiatric hospital. To introduce them to the application, nurses and nurse managers were informed about the system developed in this study, and a survey regarding their opinions on the functions of the application was conducted with ten nurse managers. The results were evaluated in terms of usefulness for nursing care, documentation, and the education of nurses from an ethical perspective. This study suggests that matching their input with an inappropriate expression database will allow nurses to record more appropriate expressions. From an ethical perspective, the ability to use appropriate expressions makes records more likely to withstand disclosure requests from patients and their families.

A Multi-event Extraction Model for Nursing Records

Nursing records contain information on patients’treatment processes,which reflect the changes in patients’conditions and have legal effects.However,some of the written records of intensive care unit(ICU)nurses are incomplete according to our observations.This paper proposes an approach extracting structured nursing events from unstructured nursing records for detecting the missing items automatically.According to the PIO(problem,intervention,outcome)principle in the field of medical care,we propose event schemas for nursing records and annotate a Chinese nursing event extraction dataset(CNEED)on ICU nursing records.We find that several events may occur in a nursing record.Therefore,we present a multi-event extraction model for the nursing records.The experimental results demonstrate that our model achieves good results on CNEED and outperforms competitive methods on the multi-event argument attribution problem.By observing the results of automatic event extraction by our model,we detect missing items in the existing nursing records.This proves that our model can be used to help nurses check and improve the method of recording nursing processes.