Scoping Review on the Impact of Artificial Intelligence in Preventing Pressure Ulcers and Patient Falls

Background: Pressure ulcers and patient falls are major challenges in healthcare, particularly for hospitalized patients or individuals with mobility limitations. Preventing these issues requires advanced technologies to accurately assess risks and implement effective interventions. The ultimate goal is to enhance the quality of care and prevent these complications. Methods: This study is a scoping review examining the impact of advanced technologies on the prevention of pressure ulcers and patient falls. Data was collected by searching the databases Google Scholar, PubMed, Scopus, and Science Direct. Inclusion and Exclusion Criteria: Inclusion criteria: Full-text availability and articles in English. Exclusion criteria: Lack of direct relevance to the research topic. A total of seven articles that met the inclusion criteria were selected for review. Strategy search: ("Artificial Intelligence" OR "AI") AND ("Patient Fall" OR "Fall Prevention" OR "Pressure Ulcers" OR "Bedsores") AND ("Prevention" OR "Risk Assessment" OR "Interventions") AND ("Healthcare" OR "Clinical Practice" OR "Patient Safety") Results: The study found that the combination of AI technologies, such as measuring moisture, cytokine levels, and thermography, significantly contributed to early detection and prevention of pressure injuries. A fall detection system demonstrated better surveillance compared to standard systems, reducing fall rates by ۵۴.۱%. Additionally, the Ai Chi program improved pain perception, balance, and functional capacity in Parkinson’s disease patients. Conclusion: AI-based technologies show promise in preventing pressure injuries and falls. The Ai Chi program provides a feasible and effective approach to improving patient outcomes, especially for Parkinson’s disease patients.

کلیدواژه ها:

AI ، Patient Fall ، Bedsore ، Prevention