Development of AI-Based ‘Bedsore Stage Prediction Solution System’
Co-Developed by Samsung Medical Center & Fine Healthcare
Presented at the Conference Held by Healthcare Information and Management System Society
Support for Bedsore Patient Care Through an Automated System
A solution system technology that predicts the stage of bedsores from photos and recommends the appropriate dressings has been developed by Korean researchers.
Professor Mira Kang of Samsung Medical Center's Health and Medicine Division and research team Soyeon Shim, Minkyung Kim, and Mira Song from the Nursing Division partnered with Fine Healthcare and developed 'Skinex', an AI-based bedsore stage prediction solution system. This was announced at the 2022 Global Conference hosted by Healthcare Information and Management System Society (HIMSS).
Skinex (Skin Explainable AI) photographs the bedsore area, categorizes them into stages (stages 1 to 4, unclassified, deep tissue damage), predicts the level of tissue damage in real-time and recommends a dressing appropriate for treatment when information of the skin condition is entered into the system.
About 10,000 bedsore images collected through barcode point of care (BPOC) were labeled and developed by three nurses with more than 10 years of experience, resulting in high levels of reliability and accuracy in the solution.
With the introduction of Skinex, it is now expected to provide ‘high quality’ care to patients with bedsores, improve accuracy by minimizing errors during evaluation of bedsore stages, as well as providing adequate information on dressing material.
Currently, after 13 inpatient wards participated in the pilot program, it plans to advance the solution by including additional data collection and functions necessary for bedsore nursing and to also expand into the global markets.
Professor Mira Kang, who supervised this study, stated, “The AI-based management solution system for bedsore stage prediction will provide helpful guidelines for nurses to provide medical care services while simultaneously lessening the work burdens by providing information on real-time bedsore stage and treatment directions to nurses who need to manage bedsore patients.”
Furthermore, nurse Soyeon Shim, who co-developed the solution system, stated in a statement, “The solution system is installed in hospital mobile devices, so regardless of whether the nurses are new or experienced, they can all utilize the system to their advantage.”