Steerling Emilie, Svedberg Petra, Nilsen Per, Siira Elin, Nygren Jens
School of Health and Welfare, Halmstad University, Halmstad, Sweden.
Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
Front Digit Health. 2025 May 20;7:1565080. doi: 10.3389/fdgth.2025.1565080. eCollection 2025.
Artificial intelligence (AI) has the potential to improve the quality and efficiency of medical triage in primary care. However, there are many uncertainties related to its use. Trust in these systems is important for successful integration and advancement into healthcare, yet this remains an understudied issue. Understanding the influences on trust in the actual use of AI is necessary for developing effective implementation strategies.
This study aimed to explore the influences on trust of healthcare professionals and patients in the use of AI-based triage in primary care in Sweden.
We applied qualitative study design using an inductive approach based on semi-structured interviews with 14 healthcare professionals and 12 patients in two regions in Sweden. The participants had experience of using AI-based triage in primary care. The interviews were transcribed verbatim and analyzed with reflexive thematic analysis to explore the influences on trust.
Healthcare professionals and patients experienced three types of influences on their trust in the use of AI-based triage in primary care: (1) provision of accurate patient information, (2) alignment with clinical expertise, and (3) supervision of patients' health and safety. Their experiences across these themes varied only in terms of the influence of experience-based knowledge. Both healthcare professionals and patients emphasized the importance of constructive dialogue, along with clear instructions for the use and storage of information.
The results demonstrate that building trust in AI requires improved interaction to ensure that the system is adapted to the users' competencies and level of expertise. The generalizability of these insights is limited to AI-based triage in primary care in Sweden. Future research should explore trust in AI across different healthcare settings to inform policy, as well as to ensure safe use and design of AI applications.
人工智能（AI）有潜力提高初级保健中医疗分诊的质量和效率。然而，其使用存在许多不确定性。对这些系统的信任对于成功融入医疗保健并取得进展至关重要，但这仍是一个研究不足的问题。了解对人工智能实际使用中信任的影响对于制定有效的实施策略是必要的。
本研究旨在探讨瑞典初级保健中医疗专业人员和患者对基于人工智能的分诊使用的信任影响因素。
我们采用定性研究设计，基于对瑞典两个地区14名医疗专业人员和12名患者的半结构化访谈，采用归纳法。参与者有在初级保健中使用基于人工智能的分诊的经验。访谈逐字记录，并通过反思性主题分析进行分析，以探讨信任的影响因素。
医疗专业人员和患者在初级保健中对基于人工智能的分诊使用的信任受到三种类型的影响：（1）提供准确的患者信息，（2）与临床专业知识一致，（3）监督患者的健康和安全。他们在这些主题上的经历仅在基于经验的知识影响方面有所不同。医疗专业人员和患者都强调建设性对话的重要性，以及对信息使用和存储的明确说明。
结果表明，建立对人工智能的信任需要改善互动，以确保系统适应用户的能力和专业水平。这些见解的普遍性仅限于瑞典初级保健中基于人工智能的分诊。未来的研究应探索不同医疗环境中对人工智能的信任，以为政策提供信息，并确保人工智能应用的安全使用和设计。
