Abstract
The global population is aging, and there is a concomitant increase in surgery for the elderly. In geriatric patients, where postoperative pain assessment is difficult, technological tools that perform automatic pain assessment are needed to alleviate the workload of nurses and to accurately assess patients' pain. This study offers a more reliable and rapid assessment tool for assessing the pain of elderly patients undergoing surgery. The study aimed to develop a machine learning–based pain assessment application for postoperative geriatric patients. A methodological study was conducted with 68 patients in the general surgery clinic of a hospital between October 2022 and June 2024. Data were collected using a Sociodemographic Data Collection Form, the Numeric Rating Scale, and the Wong-Baker FACES Pain Scale. Then, machine learning was used. Data are summarized using descriptive statistics and presented using narrations, tables, and graphs. The study reveals that nurses assigned lower scores to patients' pain levels. In the categorical classification, a high level of agreement was observed between the patient and the machine learning for each measurement. A machine learning–based pain assessment application is an efficacious method for assessing pain following geriatric surgery. It facilitates nursing care and supports the advancement of geriatric nursing.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call