关键词: Ethical considerations Healthcare integration Large language models Neuro-oncology care Patient engagement Shared decision making

Mesh : Humans Health Personnel Informed Consent Language Patient Participation Decision Support Techniques

来  源:   DOI:10.1007/s00432-024-05673-x   PDF(Pubmed)

Abstract:
Shared decision-making (SDM) is crucial in neuro-oncology, fostering collaborations between patients and healthcare professionals to navigate treatment options. However, the complexity of neuro-oncological conditions and the cognitive and emotional burdens on patients present significant barriers to achieving effective SDM. This discussion explores the potential of large language models (LLMs) such as OpenAI\'s ChatGPT and Google\'s Bard to overcome these barriers, offering a means to enhance patient understanding and engagement in their care. LLMs, by providing accessible, personalized information, could support but not supplant the critical insights of healthcare professionals. The hypothesis suggests that patients, better informed through LLMs, may participate more actively in their treatment choices. Integrating LLMs into neuro-oncology requires navigating ethical considerations, including safeguarding patient data and ensuring informed consent, alongside the judicious use of AI technologies. Future efforts should focus on establishing ethical guidelines, adapting healthcare workflows, promoting patient-oriented research, and developing training programs for clinicians on the use of LLMs. Continuous evaluation of LLM applications will be vital to maintain their effectiveness and alignment with patient needs. Ultimately, this exploration contends that the thoughtful integration of LLMs into SDM processes could significantly enhance patient involvement and strengthen the patient-physician relationship in neuro-oncology care.
摘要:
共享决策(SDM)在神经肿瘤学中至关重要,促进患者和医疗保健专业人员之间的合作,以导航治疗方案。然而,神经肿瘤疾病的复杂性以及患者的认知和情感负担对实现有效的SDM构成了重大障碍。本讨论探讨了大型语言模型(LLM)的潜力,例如OpenAI的ChatGPT和Google的Bard,以克服这些障碍。提供一种方法,以提高患者的理解和参与他们的护理。LLM,通过提供可访问性,个性化信息,可以支持但不能取代医疗保健专业人员的重要见解。该假设表明,患者,通过LLM更好地了解信息,可以更积极地参与他们的治疗选择。将LLM整合到神经肿瘤学中需要进行伦理考虑,包括保护患者数据和确保知情同意,同时明智地使用AI技术。未来的努力应该集中在建立道德准则上,适应医疗保健工作流程,促进以患者为导向的研究,anddevelopingtrainingprogramsforclinicaldocumentsontheuseofLLM.ContinuousevaluationofLLMapplicationswillbevitaltomaintaintheireffectivenessandalignmentwithpatientneeds.最终,这项探索认为,将LLM周到地整合到SDM流程中,可以显著提高患者参与程度,并加强神经肿瘤护理中的医患关系.
公众号