Improving the workflow of nursing assistants at a general hospital in Japan

Abstract

Transferring non-specialised tasks from registered nurses to nursing assistants may help registered nurses focus on specialised tasks. Optimising the workflow of nursing assistants by making their tasks more efficient may improve problems associated with the shortage of registered nurses. The nursing assistants at our hospital were stressed about referring inpatients to outpatient specialty clinics. Therefore, we initiated a project to optimise the referral process and reduce the time spent by nursing assistants on this task, with the collaboration of physicians, registered nurses and administrative assistants. The Training for Effective & Efficient Action in Medical Service–Better Process (TEAMS-BP) method, which was developed by modifying the Japanese Training Within Industry–Job Method, was used for the optimisation process. TEAMS-BP teaches users how to break each task down into its individual components, to scrutinise the details, and then to develop new processes by eliminating, combining, rearranging and simplifying tasks. At baseline, each referral took 10 min and was performed 39 times over 10 days in six wards. The first TEAMS-BP cycle did not yield satisfactory results for the nursing assistants. In the second TEAMS-BP cycle, participants included inpatient and outpatient physicians, registered nurses and administrative assistants. As a result, we changed the referral process from paper to electronic records and streamlined referrals that were ordered by inpatient physicians to outpatient physicians. The use of this method saved the equivalent of 175 hours of nursing assistants’ time per year at no additional cost. If we had been able to define the referral process as an interdisciplinary task and show the merits to each department from the beginning, we may have been able to form the interprofessional team in the first TEAMS-BP. Improving the efficiency of nursing assistants can allow other professionals to focus on their specialised tasks more effectively.

Reduction in Door-to-Balloon Time with Training for Effective and Efficient Action in Medical Service-Better Process (TEAMS-BP) at a Community Hospital in Japan

“…We developed TEAMS-BP at the University of Tsukuba in 2012 with the co-operation of the Japan Industrial Training Association (Maeno 2016;Isono et al 2017). It is based on the Japanese Training Within Industry-Job Method (TWI-JM) (Graupp and Wrona 2006).…”

“…Further analysis of individual cases is required to identify the steps during which the delays occur and why they happen. A previous study of nursing assistants showed that an advantage of TEAMS-BP is its ability to elicit improvement by repeating the four-step cycle, and that improvements will continue to be made (Isono et al 2017).…”

“…Development of a new process to reduce DTB time which can accommodate the working conditions of Japanese hospitals is essential. We recently developed a new method that can be used to develop a wide variety of new processes, called Training for Effective and Efficient Action in Medical Service-Better Process (TEAMS-BP) (Isono et al 2017). As shown in Fig.…”

“…It consists of four steps that teach users how to break each task down into its individual components, scrutinize the details, and develop and implement a new process. We previously demonstrated the strengths of the steps and concept of TEAMS-BP in improving the workflow of nursing assistants at a general hospital in Japan (Isono et al 2017). In particular, Steps 1 and 2 of TEAMS-BP are simple but unique.…”

Determinants of the Flowchart Use by Registered Nurses and Associates in the Kasa-vubu Health Zone in Kinshasa, Democratic Republic of the Congo

“…A study conducted in Cameroon reported that the flowchart is a decision-making and vocational training tool. A good technique for handling flowcharts, observed in 10/16 nurses, is associated with their systematic initial use and with the standardization of care [4]. However, the inadequate reading skills of dichotomous trees hinder their application in the diagnostic decisionmaking.…”