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Lopponen H, Holma T, Sorri M, Jyrkinen L, Karhula V, Koivula A, Ilkko E, Laitinen J, Koivukangas J, Oikarinen J, Alamaki 0. Computed tomography tiattr based rapid prototyping model of the temporal bone before cochlear implant surgery. Acta Otolaryngol (Stockh) 1997; Suppl 529; 47-49.Rapid prototyping (RP) technique allows automatic fabrication of 3D model parts. This method was applied to make a temporal bone model before cochlear implant surgery. A helical CT scan is used to acquire high resolution data from the middle and the inner ear of the patient. From the scanning data bone structures and soft tissues can be separated because their different grayscale pixel values. By using a guided image processing tool the desired parts of the anatomy can be extracted and 3D data created. The segmented data are processed to the form suitable for creating a high accuracy RP model. The RP model is made in the stereolithography (SLA) process by means of a computer guided HeCd laser beam inducing polymerisation of acrylic solution as it passes layer by layer over the surface of the polymer solution. In this prototype model the anatomy of the temporal bone can be clearly visualised, including, e.g., mastoid cells, tympanic cavity, bony canal of facial nerve, and round and oval windows. The inner ear spaces including vestibule, semicircular canals and cochlear turn are also shaped. The transparent acrylic material allows bonelike mechanical handling. The RP model can be dissected and used in individual surgical planning and simulation prior to cochlear implantation.

Objective: The aim of the study is to test a new nurse movement route analysis (NMRA) method for measuring nurses’ traffic volume between rooms on wards. Background: The World Health Organization calls for urgent investment in nurses. On the other hand, the challenges in the availability, direct care activity, and staffing of registered nurses make increasing the quality of care by process improvement a central objective for nursing. Method: The method is based on cellular operations with from/to matrix that describes nurse movements between rooms on a ward. The NMRA can be implemented by traditional manual observation or with a novel internet-of-things solution named SKAnalysis. Results: The greatest nurse flows led to patient rooms, nurses’ stations, and medicine rooms. The manual NMRA recorded a total of 3,040 room visits by nurses; visits to patient rooms accounted for 33% of all room visits, while visits to nurses’ stations accounted for 28%, and visits to the medicine room for 10%. The internet-of-things NMRA recorded a total of 25,841 room visits by nurses; patient room visits accounted for about 43% of all room visits, while nurses’ station visits accounted for 26% and medicine room visits for about 8%. Based on the results, researchers present the development examples and priorities for nursing. Conclusions: NMRA works and is a new universal method for analyzing nurses’ traffic which is a basic premise for improving working methods and productivity on the wards. Internet-of-things solution makes the implementation of NMRA six times more efficient than by the manual NMRA.