As the number of medical welfare facilities for the elderly increases due to the rapid super-aging, elder abuse in facilities is also increasing. Therefore, this study used text mining and CONCOR techniques to identify the trend of academic research on elder abuse in elderly medical welfare facilities and to suggest implications for responding to elder abuse and the direction of academic research. For the analysis data, a total of 59 dissertations and academic papers published in Korea related to elder abuse in elderly medical welfare facilities were analyzed for about 20 years from 2005 to 2025. As a result of the study,ⅰ) the top keywords were elder abuse, the elderly, long-term care facilities, nursing care workers, perceptions, workers, abuse, impacts, facilities, and elderly human rights. ⅱ) TF-IDF results showed residents, elderly human rights, nursing care workers, CCTV, attack, burnout, workers, human rights awareness, and person-centered. ⅲ) 2-gram was found to be the main keywords for the elderly + long-term care facilities for the elderly, elder abuse + awareness, resident + abuse, job stress + elder abuse, elder abuse + prevention, senior long-term care facilities + workers, awareness + impact, abuse + behavior, CCTV + installation, and elder abuse + impact. As a result of the CONCOR analysis, cluster 1 was found to be 'prevention and policy for responding to elder abuse', cluster 2 was found to be 'care workers' job stress and improvement of working environment ', cluster 3 was 'elderly human rights and practice', and cluster 4 was 'elderly abuse perception and influencing factors'. Based on the analysis results of this study, multidisciplinary studies such as neglect prevention and Internet of Things research in medical welfare facilities for the elderly, studies to prevent abuse of the elderly with dementia and to prepare countermeasures, studies on elder abuse precedents, and studies to improve job stress and working environment for nursing care workers were presented.