An AI ‐Enabled Nursing Future With no Documentation Burden: A Vision for a New Reality

AIMS: To explore the potential of multimodal large language models in alleviating the documentation burden on nurses while enhancing the quality and efficiency of patient care. DESIGN: This position paper is informed by expert discussions and a literature review. METHODS: We extensively reviewed nursing documentation practices and advanced technologies, such as multimodal large language models. We analysed key challenges, solutions and impacts to propose a futuristic multimodal large language model-driven model for nursing documentation. RESULTS: Multimodal large language models offer transformative capabilities by integrating multimodal audio, video and text data during patient encounters to dynamically update patient records in real time. This reduces manual data entry, enabling nurses to focus more on direct patient care. These systems also enhance care personalisation through predictive analytics and interoperability, which support seamless workflows and better patient outcomes. While predictive analytics could improve patient care by identifying trends and risk factors from nursing documentation, further research is required to validate its accuracy and clinical utility in real-world settings. Ethical, legal and practical challenges, including privacy concerns and biases in artificial intelligence models, require careful consideration for successful implementation. CONCLUSION: Transitioning to multimodal large language model-driven documentation systems can significantly reduce administrative burdens, improve nurse satisfaction and enhance patient care. However, successful integration demands interdisciplinary collaboration, robust ethical frameworks and technological advancements. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: Implementing multimodal large language models could alleviate professional burnout, improve nurse-patient interactions, and provide dynamic, up-to-date patient records that facilitate informed decision making. These advancements align with the goals of patient-centred care by enabling more meaningful engagement between nurses and patients. IMPACT: The problem being addressed is the administrative burden of nursing documentation. We suggest that multimodal large language models minimise manual documentation, enhance patient care quality and significantly impact nurses and patients in diverse healthcare settings globally.