Key Flow Processes on Wards.

Area of Science:

• Nursing Science
• Healthcare Operations Research
• Human Factors Engineering

Background:

• The World Health Organization emphasizes urgent investment in nursing.
• Challenges in nurse availability and staffing necessitate process improvements to enhance care quality.
• Optimizing nursing workflow is crucial for improving patient care delivery.

Purpose of the Study:

• To introduce and evaluate a novel Nurse Movement Route Analysis (NMRA) method.
• To quantify nurse traffic volume and movement patterns between rooms on hospital wards.
• To compare the efficiency of manual observation versus an Internet-of-Things (IoT) solution for NMRA.

Main Methods:

• Developed a Nurse Movement Route Analysis (NMRA) method utilizing a from/to matrix.
• Implemented NMRA through traditional manual observation.
• Utilized a novel Internet-of-Things (IoT) solution, SKAnalysis, for NMRA data collection.

Main Results:

• The greatest nurse traffic flows were observed between patient rooms, nurses' stations, and medicine rooms.
• Manual NMRA recorded 3,040 room visits, with patient rooms (33%), nurses' stations (28%), and medicine rooms (10%) being most frequent.
• IoT-based NMRA recorded 25,841 room visits, with patient rooms (43%), nurses' stations (26%), and medicine rooms (8%) being most frequent.

Conclusions:

• Nurse Movement Route Analysis (NMRA) is a validated, universal method for analyzing nurse traffic.
• NMRA provides a foundation for enhancing ward working methods and productivity.
• The IoT-based NMRA implementation is six times more efficient than manual observation, offering significant efficiency gains.