The growing population of aging Korean American nursing home residents underscores the need for culturally tailored care. This study developed and evaluated a clinical decision-support system (CDSS) based on the North American Nursing Diagnosis Association-International, Nursing Intervention Classification (NIC), and Nursing Outcome Classification (NOC) for US Korean American nursing home nurses. We used GPT-4.0 (OpenAI, San Francisco, CA) to generate 130 customized nursing care scenarios incorporating the relevant NANDA-I, NIC, and NOC elements. Subsequently, the RN Korean version CDSS' was developed using a large language model. System usability was evaluated using the Korean System Usability Scale; Korean Usefulness, Satisfaction, and Ease-of-Use questionnaire; and Korean Nielsen heuristic evaluation. The SUS results indicated favorable scores, while USE was rated positively. Ease of learning was rated the highest. Expert evaluations of heuristic principles revealed diverse ratings, with particularly favorable ratings for user control and freedom. However, principles such as flexibility and efficiency of use, and the match between the system and real-world contexts scored lower, highlighting areas of improvement. The proposed NNN CDSS can improve communication and care delivery, thereby enhancing care quality for diverse populations and supporting health equity among US nursing homes.
Development and Evaluation of the Korean Version of Clinical Decision Support System Integrating Standardized Nursing Language for Nursing Home Residents.
J. Shin,Chung Hyuk Park,Suhyun Park,Myungeun Lee,Jin-Hwa Park,Min Kyoung Han,Soo-Kyoung Lee,Melissa Batchelor
Published 2025 in Computers, Informatics, Nursing
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- Publication year
2025
- Venue
Computers, Informatics, Nursing
- Publication date
2025-12-23
- Fields of study
Medicine
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- External record
- Source metadata
Semantic Scholar, PubMed
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